OpenAI Rips YouTube, Elon’s Robotaxis & AI Artist Purz Beats | Ep52

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OpenAI is screwing YouTube and

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It kind of seems like
everybody is screwing YouTube

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There's only a few of these that exist
in the world, we actually have an AI DJ

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Let's crank it up and let the
beat drop like it's hot, hot, hot.

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every Experience that we have is gonna be
synthesized for a new large language model

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Now I wish I could punch
you through the screen again

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Just kidding, everybody.

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We are having fun.

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Welcome.

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Welcome.

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Welcome everybody.

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It is another big
episode of AI for humans.

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Oh,

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There was no, there was no
warning whatsoever about

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We'll start over.

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We'll start

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And I felt unwelcomed,

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We're starting over.

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Stop.

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We're starting over.

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Welcome everybody.

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It is AI for Humans, your weekly
guide to the wonderful and

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wild world of generative AI.

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I am here.

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My name is Gavin Purcell and my
friend, Kevin Pereira is on the

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other end of the microphone.

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Kevin, how are you?

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I'm on the other end of this microphone.

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It's like two tin cans in a

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We're connected.

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We're connected.

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That's it.

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We've docked.

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Hi friends.

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me, KP.

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I'm leaving that entire intro in Gavin.

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What a beautiful AI for humans.

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Episode five, two.

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We got today.

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Should we tell the people
what this podcast is about?

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We like to demystify all the
news, tools, and all the other

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aspects out there just for you.

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Kevin, what's on the show today?

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OpenAI is screwing YouTube and
Google is screwing YouTube.

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It kind of seems like everybody
is screwing YouTube, except

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for maybe the creators.

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We're gonna tell you how and why,
and maybe, maybe I'll share some very

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artistic, tasteful renderings that
I've made of said screwing, Gavin.

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no, really?

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No!

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Is it okay?

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Good, good.

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I was just making sure
you're paying attention.

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Also, hey, stop me if you've heard
this one, Gavin, and or audience

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who cannot actually stop me
because this is a one way medium.

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Elon Musk is working on robo taxis.

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Oh, I've heard this one, so you can

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Yeah, we've all heard this one since
like 2014, but hopefully, the just

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announced Spotify AI DJ will be able to
generate a playlist that's loud enough to

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drown out the screams as our robo taxis
autopilot us through farmer's markets.

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Oh no, sir, I don't like that at all.

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. Listen, we're going to have all the
details, plus some dumb things that

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everybody listening can do with AI today.

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We're going to chat with an AI
powered guest, and then we're probably

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going to have a way more compelling
chat with an actual human being,

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Gavin, a boundary pushing visual
artist, who is our real guest today.

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We're going to dive deep into the
cutting edge of AI artistry with PURZ.

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PURZ.

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It's PURZ.

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P U R Z,

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It's not Perz Beats,
I thought his name was

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that's the full name, but colloquially,
the casual, we're on that level.

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When we give a head
nod, we say, Sup, Purrs?

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what's up Perz?

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All right, that'll be very exciting.

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Before we get started as always
we want to tell you at home Please

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share , and rate our podcast.

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It is only with those shares
and rates that we grow.

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Our YouTube video last week was doing
very well and still is doing very well.

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And we appreciate everybody that watches
the video likes and subscribes on YouTube.

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Also, please leave a five star
podcast on Apple podcasts.

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We will read them at the end of the show.

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Kevin, today we have three new
ones to read, which is exciting.

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Um, yes, we, we had three new.

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last week's

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All right, groveling?

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through to people?

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It got through.

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So again, we really appreciate everybody
in our audience who listens to this show.

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This is not just the two of us BS ing
for an hour and then we upload it.

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There's a lot of editing
and all sorts of other

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hate each other.

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Every sentence is a grind.

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It is trench warfare
when we launch this pod.

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And through gritted teeth and multiple
takes, we managed to get sentences out.

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So if you appreciate the end
product, we appreciate you engaging.

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Isn't that right, you piece of shit?

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Wow!

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Now I wish I could punch you
through the screen again.

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Just kidding, everybody.

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We are having fun.

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I want everybody to know
that is not exactly true.

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Kevin is making up lies right now.

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Kevin, it is time to get to the news!

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I'm already sweaty.

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Okay.

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The news this week is as usual, Fast
and Furious, the biggest story that

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I've seen come down news story in a
while and AI broke over the weekend.

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The New York times published a
piece that had five authors on it.

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So, you know, when there's five authors
on New York times piece, they've

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done some research, which basically
accused open AI, Google, and meta.

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all of training on, um, various
versions of data, but mostly they

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talked about scraping YouTube.

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And the big question with Sora,
videos especially, has been, how

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did they get video to train Sora?

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Because as everybody knows who
listens to the show, and if you

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don't, it's a pretty simple thing.

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You need a lot of data to
train an AI model, whether

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that's an LLM and text model.

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It means you need to get
a lot of data of words.

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In this instance, you need a lot
of video to train something like

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SORA, especially train it as well.

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Now, OpenAI has done a
deal with Shutterstock.

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So there's a lot of stuff out
there, but most people, I think,

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haven't assumed that there was some
sort of version of this happening.

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I think there was a little bit of a
snippet that came out a couple weeks ago

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when Joanne Stern published her video
where she interviewed Mina Murati, who

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is the OpenAI Chief Technical Officer,
who could not answer the question about

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how they had trained their SORA model.

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She had a little bit of, yeah,
that was a little bit of a face.

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So she really didn't have
a good answer for this.

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And I think what we've learned now
is that they did train it on YouTube.

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So, Kevin.

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First of all, when you read this piece,
which was very long, and I encourage

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everybody who's listening to go read it.

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Cause it's a lot of, uh,
there's a lot of things in there

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that are really fascinating.

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What was your first takeaway
from reading this piece?

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What a non surprise!

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I wasn't shocked in the slightest.

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I got to imagine you weren't as well,
Gavin, because we know how much data

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is required to train these things.

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, a couple of details from the article, and
then we can dive in a little bit deeper.

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Greg Brockman, OpenAI's president,
, allegedly personally helped

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collect the videos that were used.

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, again, according to the New York Times.

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What they did though, was that
they grabbed, , transcripts

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of all the YouTube videos.

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And using that, which would be a
violation, according to Google,

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of YouTube's usage policies.

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You cannot use their data
to train something else.

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However, buried within that article is an
accusation that Google may have done the

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Done it themselves.

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Yeah, exactly.

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and that the reason Google might
not be making any public statements

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about OpenAI's alleged actions
is that they're curious if they

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would be outing themselves as well.

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Exactly.

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And it's been really interesting.

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So Neil Mohan, the, , YouTube CEO did
come out and say that, , some YouTube

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content is scrapable for open web
purposes, but the video transcript and

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footage are not allowed to be scraped.

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He said, this is a clear
violation of our terms of service.

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So those are the rules of the road
in terms of content on our platform.

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But you're right.

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It is interesting to see.

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how how kind of quiet the overall
Google ecosystem has been on this.

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And I think one thing I want to point out

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I was really kind of surprised
at how little noise this

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made in the AI ecosystem.

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And when I say the AI ecosystem, I mean,
the people kind of like us or more of

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the people who are kind of interested
in AI who are kind of focused on this.

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When I first read this, I was
like, well, this is a smoking gun.

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Like, look at this.

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This is going to like launch what I
believe will probably be dozens of

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lawsuits, whether they get through or not.

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Now, I think the big question is going
to be what do Google's terms of services

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say when things were scraped, if they were
scraped, and it sounds like they were.

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But then I think the next
question is going to be.

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And this, I want to ask you directly
this, cause there's so many people

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who talk about, and you've said this
and I've said this, the idea that

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like the cat is out of the bag, right?

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That the idea that once
you've done this, guess what?

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It's too late.

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All this stuff is out there and now
we just have to live with what it is.

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Do you think that there is any way that
there is a pause that can be put on

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this based on legal terms at this point?

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Perhaps an injunction against the
output of all large language models

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until a judge can say hey We got
to piece this together, right?

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We got to dive in through your
model, see how it was trained,

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see if you violated something.

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, I think there's too much money at play
, that, that could be a scenario, but I

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think there will just be millions, if not
billions of dollars thrown against the

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wall to make sure that something like that
doesn't happen in the interim and it's

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business as usual until decades later,
everything megacorp that's going to rule

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us all and be our one world government.

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Like, people will just play nice.

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There's just too much money at stake,
so I think this is a calculated move.

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I'm sure there were lawyers involved
at one point in the room, and

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eventually, probably the engineers
said, Hey, listen, we have to sprint.

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We have to grab this data.

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We will beg for, and probably
pay for, forgiveness later.

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So let's just go.

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I think that's probably true.

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And I think the one thing that's important
to point out here is there's been a couple

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stories this week about how hard it is to
get new data to train , these devices on.

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And there's lots of people in the machine
learning world that are saying, Hey,

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this is going to be a scaling issue.

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Like actually every time you scale
up, you get better results, but

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scaling equals more data, right?

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And so the one thing that they've
talked about a lot is we have

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scraped so much text data already.

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Like so many books and again, who knows
the legal ramifications of that, putting

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it aside, but we've scraped the internet.

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We've scraped books.

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We've scraped all this stuff.

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If they're scraping and have scraped,
, a lot of YouTube already, where does

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more data come from is a huge question.

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And that's partly the whole
synthetic data conversation.

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But like, I don't know where you get
more than YouTube when it comes to video.

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Someone has to be transcribing and
scraping every podcast in every

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language and going back , decades ago.

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, I'm sure that's already been thought
of and is being grabbed as well.

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, last year, this is according to the
New York times article, Google quote,

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Also brought in its terms of service.

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One motivation for the change,
according to members of the company's

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privacy team and an internal message
reviewed by the times was to allow

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Google to be able to tap publicly
available, Google docs, restaurant

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reviews on Google maps and other online
material for more of its AI products.

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So even Google was like, Hey, we got
to start getting this, you know, at

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some point there's going to be some
sort of like, Hey, we'll give you.

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Maybe, maybe we'll give you 3 percent
off your Google for business account.

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If you let us crawl through
some files, in fact, maybe we

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won't give you anything off.

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Maybe we'll just

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We'll just do it.

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of service and just go on through it.

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00:10:36,626 --> 00:10:37,786
That's probably going to happen.

239
00:10:37,786 --> 00:10:41,456
But on the synthetic data front, that,
that you brought up, that to me is

240
00:10:41,506 --> 00:10:42,871
really, really interesting because.

241
00:10:43,321 --> 00:10:47,511
It seems like every day a new paper
comes out that says synthetic data

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00:10:47,521 --> 00:10:50,431
is great and it's going to solve the
problem, which is something that Sam

243
00:10:50,441 --> 00:10:52,781
Altman has said is going to be the case.

244
00:10:53,201 --> 00:10:56,231
Or there's a paper that comes out and
says synthetic data is terrible and the

245
00:10:56,251 --> 00:10:57,741
AI is going to train itself in a loop.

246
00:10:57,741 --> 00:11:00,521
So for the broader audience out there
that doesn't know what we are talking

247
00:11:00,531 --> 00:11:04,691
about when we say synthetic data,
we're saying that You can use the large

248
00:11:04,691 --> 00:11:07,671
language models as they exist today
and likely as they'll exist in the

249
00:11:07,671 --> 00:11:13,691
next year or two, which will be better,
theoretically, to generate paragraphs upon

250
00:11:13,691 --> 00:11:17,181
paragraphs of text and a computer code.

251
00:11:17,181 --> 00:11:19,321
I mean, we're talking like
generate the Library of Congress.

252
00:11:19,321 --> 00:11:20,631
It could probably do it in a week.

253
00:11:20,911 --> 00:11:26,331
It just is going to churn and give you
fake questions and answers, fake recipes,

254
00:11:26,341 --> 00:11:28,711
fake restaurant reviews, fake everything.

255
00:11:28,711 --> 00:11:33,161
That synthetic data is thought
by some to be good enough.

256
00:11:33,551 --> 00:11:36,981
That if you generate enough of
it, you can train a better model.

257
00:11:36,981 --> 00:11:41,051
But some are saying that actually the
repeated words and phrases that are

258
00:11:41,051 --> 00:11:44,881
already seen to come out of some of
these language models, the bad code

259
00:11:45,011 --> 00:11:48,531
or the potentially pirated snippets
of content, those are just going

260
00:11:48,531 --> 00:11:50,211
to resurface over and over again.

261
00:11:50,221 --> 00:11:53,761
And then eventually it kind of
trains itself on its worst bad habits

262
00:11:53,761 --> 00:11:54,901
and it's not going to be usable.

263
00:11:55,121 --> 00:11:56,981
Those are the two schools
of thought right now.

264
00:11:57,481 --> 00:11:59,591
Do you have a horsey in this race, Gavin?

265
00:12:00,031 --> 00:12:02,551
I don't understand enough on
the technical side to see if the

266
00:12:02,551 --> 00:12:03,851
synthetic data is strong enough.

267
00:12:03,861 --> 00:12:07,281
I will say from what I've read, the
arguments around synthetic data is it

268
00:12:07,291 --> 00:12:12,851
wasn't good enough before, but now as the
models get stronger, it may be better.

269
00:12:12,851 --> 00:12:16,851
The interesting thing to think about
is, if that is the unlock and we're also

270
00:12:16,851 --> 00:12:20,441
heading to a world where only bigger,
bigger models equal better results,

271
00:12:20,861 --> 00:12:24,341
then we are going to be moving very
quickly to the next stage of whatever

272
00:12:24,341 --> 00:12:28,461
this AI world is, because the AI, as
we talked about in the NVIDIA episode,

273
00:12:28,861 --> 00:12:32,741
the AI can simulate themselves in
different places and different things.

274
00:12:33,111 --> 00:12:35,771
And if that allows, if you can simulate.

275
00:12:36,296 --> 00:12:39,066
Interactions, text, video, all that stuff.

276
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You can ostensibly do that in an
infinite level if you have the amount

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00:12:43,316 --> 00:12:44,876
of compute and storage to do it.

278
00:12:44,896 --> 00:12:46,406
And then it goes really quickly.

279
00:12:46,456 --> 00:12:50,076
Actually, this really dovetails really
interestingly into another story that we

280
00:12:50,076 --> 00:12:55,606
have Bill Peebles, one of the main open
AI engineers behind Sora had a really

281
00:12:55,606 --> 00:12:59,953
interesting talk that he came out and
gave to the, AGI house, which is again,

282
00:12:59,963 --> 00:13:02,663
like probably some sort of hype house,
but for AGI is like, whoop, whoop.

283
00:13:02,933 --> 00:13:04,693
We're going to AGI land, baby.

284
00:13:05,763 --> 00:13:06,113
Like and

285
00:13:06,393 --> 00:13:07,483
Energy Refrigerator!

286
00:13:07,483 --> 00:13:08,473
It's so hype!

287
00:13:09,033 --> 00:13:09,373
Yeah.

288
00:13:09,633 --> 00:13:12,873
So Bill was at the AGI house and gave a
speech, and we're going to hear a little

289
00:13:12,873 --> 00:13:14,543
snippet of what his speech was here.

290
00:13:15,113 --> 00:13:18,483
So, of course everyone's very
bullish on the role that LLMs are

291
00:13:18,483 --> 00:13:20,288
going to play in getting to AGI.

292
00:13:20,798 --> 00:13:24,198
But we believe that video models
are on the critical path to it.

293
00:13:24,198 --> 00:13:28,658
And concretely, we believe that when we
look at very complex scenes that Sora

294
00:13:28,658 --> 00:13:33,038
can generate, like that snowy scene in
Tokyo that we saw in the very beginning,

295
00:13:33,038 --> 00:13:36,348
that Sora is already beginning to show
a detailed understanding of how humans

296
00:13:36,348 --> 00:13:39,938
interact with one another, how they
have physical contact with one another.

297
00:13:40,358 --> 00:13:43,658
And as we continue to scale this
paradigm, we think eventually it's going

298
00:13:43,658 --> 00:13:45,348
to have to model a human state, right?

299
00:13:45,398 --> 00:13:48,218
The only way you can generate
truly realistic video, with truly

300
00:13:48,218 --> 00:13:49,578
realistic sequences of actions.

301
00:13:49,993 --> 00:13:52,493
is if you have an internal
model of how all objects,

302
00:13:52,493 --> 00:13:54,233
humans, etc., environments work.

303
00:13:54,833 --> 00:13:58,003
And so we think this is how Sora
is going to contribute to HDI.

304
00:13:58,003 --> 00:13:59,343
Basically what Mr.

305
00:13:59,343 --> 00:14:01,473
Peebles is saying here,
call him, you know, Mr.

306
00:14:01,473 --> 00:14:06,578
Peebles if you're nasty, uh, He's
talking about, he's talking about

307
00:14:06,578 --> 00:14:11,228
the idea that Sora, which is a
video generator, is actually a world

308
00:14:11,228 --> 00:14:14,028
simulator, ostensibly, and we've
talked about this on the show before,

309
00:14:14,468 --> 00:14:19,098
but by world simulation, and by doing
that, even in synthetic environments,

310
00:14:19,098 --> 00:14:24,543
you are teaching the AI How people
and objects interact with each other.

311
00:14:24,543 --> 00:14:27,383
And that is a lot of people see
as the next stage of data, right?

312
00:14:27,383 --> 00:14:30,863
It's like real world training
or simulated world training

313
00:14:30,883 --> 00:14:32,833
outside of just words and texts.

314
00:14:33,083 --> 00:14:34,513
You're talking now about actions.

315
00:14:34,513 --> 00:14:36,943
You're talking about the way
a tree blows in the wind.

316
00:14:36,943 --> 00:14:40,113
You're talking about the way a human
interacts with that tree when it blows

317
00:14:40,113 --> 00:14:41,523
against them, where they cut it down.

318
00:14:41,893 --> 00:14:44,153
All of that stuff is data, right?

319
00:14:44,153 --> 00:14:45,713
It can't be perceived as data.

320
00:14:46,023 --> 00:14:49,703
And if they can find a way that
Sora can generate synthetic models

321
00:14:49,713 --> 00:14:52,803
of the world, that does feel
like where we're headed next.

322
00:14:53,403 --> 00:14:58,338
I think 2026 is the year that And
it's going to need a sexier term

323
00:14:58,338 --> 00:15:01,588
to probably get the youth involved,
Gavin, but, uh, let's say, let's

324
00:15:01,588 --> 00:15:05,060
say data harvesters or, aggregators.

325
00:15:05,340 --> 00:15:12,015
Basically, we are going to, for
pennies per minute, of experience,

326
00:15:12,285 --> 00:15:15,485
we are all going to end up working
for open AI slash Microsoft.

327
00:15:15,785 --> 00:15:19,845
We're going to have our glasses on that
are going to feed constant video streams.

328
00:15:20,045 --> 00:15:24,905
Maybe we'll have tactile haptic gloves so
that it can know the pressure and force

329
00:15:24,915 --> 00:15:28,925
with which we're exerting upon the world
as we navigate it, maybe even sensors in

330
00:15:28,925 --> 00:15:30,775
our free government provided sketchers.

331
00:15:31,115 --> 00:15:31,455
Right.

332
00:15:31,645 --> 00:15:33,875
But we are all just going to live.

333
00:15:34,210 --> 00:15:39,150
Every single day, providing data for
these mega models, because it's just

334
00:15:39,150 --> 00:15:42,400
gonna, have an insatiable appetite,
and even though the synthetic

335
00:15:42,400 --> 00:15:45,840
stuff will be good, it's never gonna
hit as hard as an analog, baby.

336
00:15:46,060 --> 00:15:50,390
So, we're all just gonna sign up to
work for one of the companies, and

337
00:15:50,390 --> 00:15:54,140
instead of running Uber Eats errands,
we're just gonna eke out our day.

338
00:15:54,150 --> 00:15:55,105
We're gonna crawl, crawl, crawl.

339
00:15:55,315 --> 00:15:58,825
Through the actual world try to
breathe the polluted air and drink

340
00:15:58,845 --> 00:16:03,025
water that doesn't have microplastics
and every Experience that we have

341
00:16:03,025 --> 00:16:07,785
Gavin is gonna be synthesized for a
new large language model sign me up

342
00:16:08,445 --> 00:16:10,025
I honestly think you're right.

343
00:16:10,055 --> 00:16:13,405
I will say it doesn't have to be as
dystopian of that, but what I could see

344
00:16:13,405 --> 00:16:16,805
very well, and we're going to talk about
robo taxis or Waymo taxis in a little

345
00:16:16,805 --> 00:16:20,845
bit, you know, right now, when you see
a robo taxi or you see a Waymo car in

346
00:16:20,845 --> 00:16:22,225
the real world, that's kind of weird.

347
00:16:22,635 --> 00:16:26,795
I do see a future where there are people
that are walking through a busy city,

348
00:16:26,815 --> 00:16:30,015
which are wearing glasses and some
sort of haptic gloves, and you kind of

349
00:16:30,015 --> 00:16:31,795
get to know them as like, they're the.

350
00:16:32,185 --> 00:16:36,175
They're the experience generator
or they're the, the gap and they're

351
00:16:36,185 --> 00:16:39,405
gathering footage like you could see
them at a concert like imagine, a

352
00:16:39,405 --> 00:16:43,425
person at a concert who's who's taking
all this data in whether it's the

353
00:16:43,435 --> 00:16:46,245
music or the way that people next to
them are interacting with each other

354
00:16:46,245 --> 00:16:48,805
like all of that feels very realistic.

355
00:16:48,805 --> 00:16:51,640
And I guess the question will
become is like, What tool is

356
00:16:51,640 --> 00:16:53,010
that to bring the things in?

357
00:16:53,010 --> 00:16:56,480
And maybe it's the next version of like
the Apple vision pro or the Facebook

358
00:16:56,480 --> 00:16:59,670
glasses, but it does make me think
about those Facebook glasses, right?

359
00:16:59,670 --> 00:17:03,590
Because the Facebook glasses aren't
just for us to like, say, Hey, I can

360
00:17:03,590 --> 00:17:05,110
identify the entire state building.

361
00:17:05,370 --> 00:17:08,430
It's also going to give a lot
of data back to meta, right?

362
00:17:08,450 --> 00:17:10,540
It's going to give a ton of
data back to meditate and then

363
00:17:10,540 --> 00:17:11,940
train the next day I model on.

364
00:17:12,170 --> 00:17:14,790
I think you and I have come to
something pretty big here, which is.

365
00:17:15,500 --> 00:17:21,280
A, we as the humans, our job may be going
forward to provide data, which is kind of

366
00:17:21,280 --> 00:17:25,160
interesting to think about as that's what
we do for ourselves all the time, right?

367
00:17:25,160 --> 00:17:28,410
I guess the big question
becomes is my data ultimately

368
00:17:28,410 --> 00:17:29,920
is not the most exciting data.

369
00:17:29,920 --> 00:17:33,440
And if they want to take like what my
experience of touching my microphone is,

370
00:17:33,440 --> 00:17:37,630
or like a bottle of water and drinking
it, it is a really interesting thing when

371
00:17:37,630 --> 00:17:42,560
you then combine it with Neuralink, you
combine it with the glasses, like you

372
00:17:42,560 --> 00:17:49,130
can start to see a weird vision of the
future that becomes beneficial for AIs.

373
00:17:49,130 --> 00:17:49,500
And then the,

374
00:17:49,595 --> 00:17:50,925
data as well, right?

375
00:17:50,925 --> 00:17:53,255
So it knows like okay I'm
jogging down the street.

376
00:17:53,265 --> 00:17:57,045
This is the way in which my POV is
changing My heart rate is accelerating.

377
00:17:57,045 --> 00:18:01,605
My gait has gone that telemetry data
There's so many points of data that Every

378
00:18:01,605 --> 00:18:05,905
human being could be gathering, , rather
it's for themselves as a personal data

379
00:18:05,905 --> 00:18:10,925
broker, or for the big Borg, which will
be giving us, I guess, like, a nutrient

380
00:18:10,925 --> 00:18:13,425
paste and a UBI in the near future.

381
00:18:13,675 --> 00:18:17,145
, yes, I think people will be doing this,
and I think people will sign up for

382
00:18:17,145 --> 00:18:22,655
this, and then ironically, , 2029 ish,
it's just gonna be way cheaper to let

383
00:18:22,655 --> 00:18:24,345
the robots go around and do it, Gavin.

384
00:18:24,755 --> 00:18:27,645
Like, they're gonna, the battery
tech's gonna get good enough to where

385
00:18:27,645 --> 00:18:29,265
they'll just strap it in the row bits.

386
00:18:29,265 --> 00:18:31,735
But in the meantime, there
is a startup to be made.

387
00:18:31,835 --> 00:18:33,135
And why not us, Gavin?

388
00:18:34,105 --> 00:18:35,990
That reminds me of, Elon Musk.

389
00:18:35,990 --> 00:18:40,671
Our old friend Elon Musk is back
and we have some news around both

390
00:18:40,671 --> 00:18:43,021
robo taxis and his low end car.

391
00:18:43,031 --> 00:18:45,131
Kev, what happened with
the low end car here?

392
00:18:46,261 --> 00:18:49,761
Well, a big nothing burger, according
to Elon, but the Reuters story

393
00:18:49,771 --> 00:18:53,671
said that they scrapped plans to
make the Model 2, Gavin, which was

394
00:18:54,211 --> 00:18:56,581
expected to start around 25, 000.

395
00:18:56,621 --> 00:18:59,391
To put that in perspective, the
Model 3, which is their cheapest

396
00:18:59,391 --> 00:19:01,661
vehicle, starts at around 40, 000.

397
00:19:01,661 --> 00:19:07,191
So, , a major price slash to try to,
really broaden the adoption of EVs.

398
00:19:07,401 --> 00:19:10,611
Writers came out and said, Ah, actually
they're killing the plans to do that.

399
00:19:10,851 --> 00:19:14,511
Maybe, , so that they can do this
robo taxi thing, which might be

400
00:19:14,661 --> 00:19:17,061
powered by what was the Model 2.

401
00:19:17,061 --> 00:19:19,581
But Elon came out and said, What, Gav?

402
00:19:19,875 --> 00:19:23,005
He said that the Reuters story was BS.

403
00:19:23,075 --> 00:19:27,025
, which you know at this point I really
don't know what to trust Elon on or not.

404
00:19:27,025 --> 00:19:28,765
So, we'll just call that a wash.

405
00:19:28,765 --> 00:19:32,830
But then he did say, On
April 5th, he said Tesla robo

406
00:19:32,830 --> 00:19:34,920
taxi unveil on eight eight.

407
00:19:34,920 --> 00:19:38,830
So that is three months away
from now, August 8th robo taxis.

408
00:19:38,830 --> 00:19:42,240
If you're not familiar with this
idea is that they Tesla's promise

409
00:19:42,240 --> 00:19:45,630
originally and other robo taxis
is these are driverless taxis.

410
00:19:45,650 --> 00:19:48,700
Basically it will take
you from place to place.

411
00:19:48,860 --> 00:19:52,940
You get in it much like a Waymo
car and you go from, from here to

412
00:19:52,940 --> 00:19:54,700
there without anybody driving you.

413
00:19:54,700 --> 00:19:56,910
And, and ultimately this
was the promise that like.

414
00:19:57,325 --> 00:20:00,785
Uber and a bunch of other companies
in the 2010s were really saying that

415
00:20:00,785 --> 00:20:03,725
this was going to be the transformative
power of those companies because

416
00:20:04,035 --> 00:20:07,685
ultimately drivers are expensive and
they're noisy and we know the problems

417
00:20:07,685 --> 00:20:09,025
that Uber's had with their drivers.

418
00:20:09,365 --> 00:20:12,745
Um, on the driver's side, like we
understand, like the drivers were

419
00:20:12,745 --> 00:20:14,315
starting to get paid, not very good wages.

420
00:20:14,315 --> 00:20:18,195
So this is a big argument
back and forth, but I feel.

421
00:20:18,530 --> 00:20:20,610
Driverless cars are something
that I've been hoping that

422
00:20:20,610 --> 00:20:22,080
we would see for a long time.

423
00:20:22,360 --> 00:20:24,610
My youngest daughter is 16.

424
00:20:25,040 --> 00:20:28,790
Five years ago, when she was 11, I
would have sworn that she probably

425
00:20:28,800 --> 00:20:30,980
wouldn't even need a driver's license in

426
00:20:30,995 --> 00:20:32,625
She would have at least had the option,

427
00:20:32,905 --> 00:20:34,275
Yes, yes, yes.

428
00:20:34,315 --> 00:20:36,685
And now we're here in 2024.

429
00:20:37,485 --> 00:20:39,625
, Cruz was basically kind of shut down.

430
00:20:39,625 --> 00:20:43,845
Cruz, the driverless car company, because
of a giant lawsuit around an accident.

431
00:20:44,245 --> 00:20:47,935
Waymo is still working, but it
is not proliferated very largely.

432
00:20:47,935 --> 00:20:48,925
There aren't a ton of them.

433
00:20:49,255 --> 00:20:52,765
And Elon now is saying, okay, in three
months, we're going to have robo taxis.

434
00:20:52,785 --> 00:20:53,775
I don't buy it.

435
00:20:53,775 --> 00:20:57,690
first of all, Elon seems like such an
unreliable narrator now, but But based

436
00:20:57,690 --> 00:21:02,910
on where the legal ramifications are
around driverless cars, I still feel like

437
00:21:02,910 --> 00:21:06,110
this is one of those things that could
be like, could be 10 more years before

438
00:21:06,110 --> 00:21:08,420
we see these in production in some form.

439
00:21:08,840 --> 00:21:13,220
It's something that's been promised
for years, , the end to end AI training

440
00:21:13,270 --> 00:21:16,920
of it all, meaning that the newest
versions of the Tesla Autopilot were

441
00:21:16,920 --> 00:21:20,395
trained just on raw video, which were
collected from their pre production.

442
00:21:20,655 --> 00:21:23,585
Hundreds of thousands of cars
that are on the road constantly

443
00:21:23,695 --> 00:21:27,415
recording and constantly uploading
data back to the mothership.

444
00:21:27,815 --> 00:21:32,145
That seems to be performing
incredibly well from what little

445
00:21:32,155 --> 00:21:33,335
bits have been leaked out.

446
00:21:33,455 --> 00:21:34,605
Is it flawless?

447
00:21:34,775 --> 00:21:36,285
No, from what we've seen.

448
00:21:36,375 --> 00:21:40,695
I can tell you, I own a Tesla
model three and I, now I could try.

449
00:21:40,705 --> 00:21:43,605
I haven't tried it for a couple
of months, but I still feel

450
00:21:43,605 --> 00:21:45,065
freaked out when I'm using it.

451
00:21:45,065 --> 00:21:45,305
Right.

452
00:21:45,305 --> 00:21:46,665
It is not that good.

453
00:21:46,665 --> 00:21:48,915
And that's on the freeways right now.

454
00:21:48,915 --> 00:21:51,875
I do trust it on longer
drives to basically.

455
00:21:52,385 --> 00:21:56,655
do everything I needed to do, but
I don't feel comfortable using it

456
00:21:56,655 --> 00:21:59,475
in the city yet, because it still
does feel like it messes up a lot.

457
00:21:59,485 --> 00:22:03,135
Now, maybe there's a leap coming,
or maybe the leap did just happen

458
00:22:03,135 --> 00:22:06,425
and I haven't done it yet, but it
feels a little sketchy to me that

459
00:22:06,425 --> 00:22:07,825
we're going to get there this fast.

460
00:22:08,275 --> 00:22:13,525
In 2016, Elon Musk stunned the automotive
world by announcing that henceforth,

461
00:22:13,745 --> 00:22:16,785
all of his company's vehicles would
be shipped with the hardware necessary

462
00:22:16,795 --> 00:22:18,435
for, quote, full self driving.

463
00:22:18,775 --> 00:22:21,885
You'll be able to nap in your car while
it drives you to work, he promised.

464
00:22:22,065 --> 00:22:26,225
It will even be able to drive cross
country with no one inside the vehicle.

465
00:22:26,875 --> 00:22:27,325
to New York.

466
00:22:27,335 --> 00:22:28,375
That was always the dream.

467
00:22:28,385 --> 00:22:28,755
2016.

468
00:22:28,765 --> 00:22:29,645
Yeah, he was gonna do that drive.

469
00:22:29,655 --> 00:22:33,695
Now, I can imagine, from some of the
videos that I have seen of the latest,

470
00:22:34,105 --> 00:22:37,885
Autopilot, , firmware, show it doing
some pretty impressive navigating around

471
00:22:37,885 --> 00:22:43,145
construction zones, residentials, full
stop, start, , creeping out around corners

472
00:22:43,175 --> 00:22:46,155
again, because it's trained off of human
driving, at least the newer version.

473
00:22:46,575 --> 00:22:50,025
I could see them saying, Hey, by
the way, there was a human there

474
00:22:50,105 --> 00:22:54,555
just to intervene if need be, but we
completed the New York to SF journey.

475
00:22:54,705 --> 00:22:56,655
I could also imagine that
they probably did it.

476
00:22:56,970 --> 00:23:02,380
600 times behind a curtain before they
had a full time lapse version of the drive

477
00:23:02,380 --> 00:23:04,190
happening, but that could hit in August.

478
00:23:04,190 --> 00:23:06,760
I remember them saying that you
were going to be able to, as a

479
00:23:06,760 --> 00:23:10,720
Tesla owner, hit a button and it
would turn your Tesla into an Uber.

480
00:23:10,740 --> 00:23:13,430
So wow, it was going to be an
unlock for every owner who just lets

481
00:23:13,430 --> 00:23:16,060
their car sit there in the parking
lot for the majority of the day.

482
00:23:16,505 --> 00:23:19,165
I don't know if any of that is
coming, or if this is just gonna be

483
00:23:19,165 --> 00:23:21,065
another goose of the, the stock price.

484
00:23:21,085 --> 00:23:24,715
I do think we're getting closer, but
as we get closer, You realize the

485
00:23:24,755 --> 00:23:29,525
edge cases are so out there and so
crucial to get right, that if there is

486
00:23:29,525 --> 00:23:33,585
a human behind the wheel or the yoke,
it's okay if they need to intervene.

487
00:23:33,585 --> 00:23:36,725
But if I'm sitting in the back,
and this thing is just toting me

488
00:23:36,725 --> 00:23:39,405
around, it's got to be flawless.

489
00:23:39,450 --> 00:23:45,190
I can't wait until I can prompt my taxi
to behave like another car's AI, right?

490
00:23:45,190 --> 00:23:49,000
Like if I can hop into the Tesla RoboTaxi
and say, drive like the BMW and it just

491
00:23:49,050 --> 00:23:53,060
disables the blinkers and speeds up and
slows down so that people can't merge.

492
00:23:53,615 --> 00:23:54,495
Oh, damn.

493
00:23:54,955 --> 00:23:56,045
Yeah, that'd be amazing.

494
00:23:56,055 --> 00:23:58,360
Cause you could have like different
driver personalities, like the

495
00:23:58,385 --> 00:24:00,345
asshole that cuts you off in traffic.

496
00:24:00,345 --> 00:24:00,965
That sort of thing.

497
00:24:00,965 --> 00:24:01,185
That's a

498
00:24:01,275 --> 00:24:05,205
Or the one , , that smokes their,
, hookah in the car, like the giant

499
00:24:05,235 --> 00:24:10,405
actual black cherry tobacco full
size hookah in the passenger seat

500
00:24:10,405 --> 00:24:13,325
and just blasts me with that smoke
and plays Dark Side of the Moon.

501
00:24:13,515 --> 00:24:18,235
Which is an interesting one to
bring up, Gavin, because apparently

502
00:24:18,235 --> 00:24:21,315
the AI community hates Pink Floyd.

503
00:24:21,675 --> 00:24:22,745
This is a crazy story.

504
00:24:22,745 --> 00:24:26,735
It's another one of those where, you know,
ostensibly there was a fun idea to try to

505
00:24:26,735 --> 00:24:31,825
create something that was, uh, eventually
made with AI art and it won a contest.

506
00:24:31,825 --> 00:24:36,675
So the story here basically is that
a piece of AI art that was generated

507
00:24:36,675 --> 00:24:40,475
by a person, and specifically
this person says that they created

508
00:24:40,475 --> 00:24:41,945
models of their own to do this.

509
00:24:42,230 --> 00:24:46,500
One, a contest to make a
video for a Pink Floyd song.

510
00:24:46,860 --> 00:24:52,700
It is the Dark Side of the Moon 50th
Anniversary Animation Video Competition,

511
00:24:52,720 --> 00:24:57,840
Gavin, and if you look at Reddit or
Unreal Engine forums, you have no

512
00:24:57,840 --> 00:25:03,495
shortage of creators that put tens of
hours, into grinding out hand drawn

513
00:25:03,505 --> 00:25:08,155
beautiful things, or using that Unreal
Engine to render full 3D scenes.

514
00:25:08,385 --> 00:25:10,925
And here, this is the winning video.

515
00:25:11,175 --> 00:25:15,435
, it looks a little dated by AI standards,
but the concept is this sort of never

516
00:25:15,435 --> 00:25:20,725
ending zoom into what looks like a
recording studio that then transforms

517
00:25:20,725 --> 00:25:23,155
into a space station, if you will.

518
00:25:23,155 --> 00:25:26,875
, and there's a bit of a galaxy theme
as instruments fade in and out.

519
00:25:26,895 --> 00:25:34,115
And Well, it, it won for that song and
the reaction across X and across YouTube

520
00:25:34,155 --> 00:25:37,735
comments and pretty much everywhere
was a resounding, how dare you?

521
00:25:37,995 --> 00:25:39,495
Did no one else enter?

522
00:25:39,535 --> 00:25:42,695
I can't believe you picked this
over hand animated videos that

523
00:25:42,695 --> 00:25:43,945
were full of heart and soul.

524
00:25:44,349 --> 00:25:48,569
This is a perfect example of the
world where in this instance,

525
00:25:48,569 --> 00:25:51,899
you've got a lot of Pink Floyd fans
who are probably all ages, right?

526
00:25:51,909 --> 00:25:54,979
The Pink Floyd has fans from
their seventies down to like

527
00:25:54,979 --> 00:25:56,669
their teens, but they are,

528
00:25:56,679 --> 00:25:58,389
their 70s to their 170s.

529
00:25:58,559 --> 00:26:01,369
No, I mean, most of their
fans are probably from the 40s

530
00:26:01,399 --> 00:26:01,979
I love Pink

531
00:26:01,979 --> 00:26:02,249
Floyd.

532
00:26:02,249 --> 00:26:02,789
Yeah, I,

533
00:26:02,809 --> 00:26:06,459
yeah, but, but also every year it picks up
new fans and you know, there's this kind

534
00:26:06,459 --> 00:26:08,509
of a hallucinogenic kind of vibe to them.

535
00:26:08,509 --> 00:26:12,429
They've always had that kind of
like, druggie inspired sort of look.

536
00:26:12,819 --> 00:26:16,549
There is a really strong art
scene that , has played into that.

537
00:26:17,049 --> 00:26:20,629
The argument to make here about this
Aya piece that they created is it really

538
00:26:20,629 --> 00:26:24,279
does feel of the vibe of that space.

539
00:26:24,459 --> 00:26:30,374
But, again, When you have people who have
spent their whole lives learning tools

540
00:26:30,394 --> 00:26:34,954
and learning art and learning things, that
idea that a machine could do something

541
00:26:34,964 --> 00:26:40,584
that would seem compelling enough to win
a contest, or a person and a machine would

542
00:26:40,584 --> 00:26:45,044
feel compelling enough to win a contest,
is just always gonna make people mad.

543
00:26:45,044 --> 00:26:46,804
It's funny, do you know
the story of John Henry?

544
00:26:46,854 --> 00:26:48,004
Do you know the John Henry story?

545
00:26:48,197 --> 00:26:49,447
No, I don't think so.

546
00:26:49,467 --> 00:26:51,507
So John Henry is like
a famous American myth.

547
00:26:51,527 --> 00:26:55,237
It's about a guy who
basically, dug, , for coal.

548
00:26:55,567 --> 00:26:59,727
And then a machine came in a steam machine
came in and there was like a big kind

549
00:26:59,727 --> 00:27:03,677
of thing at the where they did a contest
between them steam machine and John Henry.

550
00:27:04,037 --> 00:27:06,977
And eventually, John Henry was like
the world's greatest coal digger.

551
00:27:07,207 --> 00:27:08,607
But the machine eventually beat him.

552
00:27:08,607 --> 00:27:13,127
And it was like this kind of parable
about the idea of, , Machines

553
00:27:13,147 --> 00:27:14,837
will take over for human labor.

554
00:27:14,837 --> 00:27:17,657
And it's been something that's kind of
echoed throughout hundreds of years.

555
00:27:18,057 --> 00:27:21,697
And one of the things that's interesting
is I think stories like that are ingrained

556
00:27:21,697 --> 00:27:27,847
in the human experience and it does in
some ways always put the idea of human

557
00:27:27,847 --> 00:27:29,727
versus machine against each other.

558
00:27:30,027 --> 00:27:33,487
And I think that's something that
we're probably going to have to.

559
00:27:33,792 --> 00:27:36,252
readdress as we move
forward in the future.

560
00:27:36,252 --> 00:27:38,992
And the funny thing is most people don't
think of this now, but of course we're

561
00:27:38,992 --> 00:27:40,952
already part phone part people, right?

562
00:27:40,962 --> 00:27:44,262
Like 99 percent of people in this
world are spending , a couple hours

563
00:27:44,262 --> 00:27:45,472
a day, at least on their phone.

564
00:27:45,972 --> 00:27:49,212
But now we're talking about
person and machine coming

565
00:27:49,212 --> 00:27:50,882
together to really do all of this.

566
00:27:51,262 --> 00:27:52,732
Actual creative work.

567
00:27:53,152 --> 00:27:55,722
I think it's just going
to take time to get over.

568
00:27:55,732 --> 00:28:00,432
And we are going to see this happen
more and more Gavin as fans and

569
00:28:00,442 --> 00:28:04,432
artists themselves, uh, poke and
prod , and use AI in their workflows.

570
00:28:04,552 --> 00:28:08,052
Do you think they're going to have
like the, uh, maybe not the generation

571
00:28:08,052 --> 00:28:11,682
today, but next gen, do you think
they're going to have their own LLM

572
00:28:11,682 --> 00:28:16,042
that is essentially fine tuned on
their experiences, their day to day,

573
00:28:16,182 --> 00:28:20,362
their thoughts, their feelings, their
artistic expressions across all mediums.

574
00:28:20,652 --> 00:28:21,952
And so when they are.

575
00:28:22,322 --> 00:28:25,502
I don't know, 16, and want to
release an album or whatever, they're

576
00:28:25,502 --> 00:28:27,492
gonna jam with their own, fine

577
00:28:27,622 --> 00:28:28,222
I hope so.

578
00:28:28,912 --> 00:28:30,232
preferences model, right?

579
00:28:30,252 --> 00:28:33,402
And they'll be able to make the artwork,
help make the song, help make all of the

580
00:28:33,412 --> 00:28:38,342
things, write the liner notes, whatever,
if those even exist in 16 years time.

581
00:28:38,342 --> 00:28:40,462
But yeah, do you think that
it will feel more natural?

582
00:28:40,462 --> 00:28:42,392
It's not like, oh, this
is a soulless machine.

583
00:28:42,392 --> 00:28:44,082
It's almost like, no, this machine is me.

584
00:28:44,392 --> 00:28:44,752
I am

585
00:28:44,787 --> 00:28:45,547
I think so.

586
00:28:45,637 --> 00:28:47,067
I think we're going to get to that.

587
00:28:47,097 --> 00:28:49,757
And I think music is going to be a
really interesting way to do that.

588
00:28:49,757 --> 00:28:52,227
And speaking of music, one of the
interesting things that came up this

589
00:28:52,227 --> 00:28:57,257
week was that Spotify announced the
idea of an AI playlist situation.

590
00:28:57,257 --> 00:28:59,747
So if you're not familiar with Spotify,
I'm sure you're familiar with Spotify.

591
00:29:00,217 --> 00:29:02,907
It's the biggest, one of the biggest
music streaming companies in the world.

592
00:29:02,957 --> 00:29:06,557
, Already they had an AI dj, which
you could turn on a scenario where

593
00:29:06,557 --> 00:29:10,337
the AI DJ would play songs that it
thought you might like and it would

594
00:29:10,337 --> 00:29:11,837
actually speak to you back and forth.

595
00:29:11,842 --> 00:29:13,067
They said, I'm gonna try this song out.

596
00:29:13,072 --> 00:29:13,637
Tell me what you think.

597
00:29:13,637 --> 00:29:14,807
You can always skip it if you want.

598
00:29:15,107 --> 00:29:17,867
Now they are introducing
the idea of an AI playlist.

599
00:29:17,867 --> 00:29:18,917
These are not live yet.

600
00:29:18,922 --> 00:29:20,712
They're only live in certain places.

601
00:29:21,052 --> 00:29:25,512
, but the idea being is that you can
tell Spotify , a feeling you have

602
00:29:25,517 --> 00:29:28,932
or, or a way or a phrase that you
want to create a, a playlist around.

603
00:29:28,937 --> 00:29:30,222
And this is something I've wished for.

604
00:29:30,467 --> 00:29:31,937
Yeah, exactly.

605
00:29:31,987 --> 00:29:34,087
My younger daughter and I are
like pretty big music people.

606
00:29:34,087 --> 00:29:35,887
Like we love music, all sorts of genres.

607
00:29:35,897 --> 00:29:38,347
Like we'll listen to things like
a hundred gecks or we'll listen to

608
00:29:38,347 --> 00:29:39,727
like rap or we'll listen to pop.

609
00:29:40,017 --> 00:29:42,607
My older daughter, my wife are
a little more sound diverse.

610
00:29:42,717 --> 00:29:47,607
They're like, they definitely need to just
have like kind of poppy happy songs or 70s

611
00:29:47,607 --> 00:29:49,847
songs that are not too like kind of noisy.

612
00:29:50,067 --> 00:29:52,697
So we have a playlist that we've
played that Spotify created called

613
00:29:52,697 --> 00:29:54,427
like happy hits or something like that.

614
00:29:54,427 --> 00:29:56,977
It's a playlist that we know that
everybody can be happy listening

615
00:29:56,977 --> 00:29:59,357
to, but that's a good example.

616
00:29:59,357 --> 00:30:02,837
, what if you could ask for a series
of like, I would like 1970s.

617
00:30:02,852 --> 00:30:06,042
Female singers that
sound, um, smooth, right?

618
00:30:06,042 --> 00:30:08,742
Like that people have made
their own playlist like that.

619
00:30:08,742 --> 00:30:12,962
But if I could just generate that myself,
that's a really cool use case for Spotify.

620
00:30:12,962 --> 00:30:14,982
I feel like, and I think
a really cool use of AI.

621
00:30:15,792 --> 00:30:18,952
Playlists we think of as this
usually very static experience.

622
00:30:18,952 --> 00:30:20,432
You put one together and there it is.

623
00:30:20,612 --> 00:30:24,122
Maybe you update it once a week or
someone throws songs in if it's a shared

624
00:30:24,132 --> 00:30:28,807
playlist, but the instant nature, Gavin,
of being able to update the mood Or

625
00:30:28,807 --> 00:30:30,627
the vibe of the playlist in real time.

626
00:30:30,727 --> 00:30:33,317
You're doing a workout and you
actually want to take a quick break.

627
00:30:33,317 --> 00:30:35,527
You tell it, Hey, let's
cool it down for a second.

628
00:30:35,577 --> 00:30:37,167
It plays something, more chill.

629
00:30:37,327 --> 00:30:40,637
Just to be able to have a natural DJ.

630
00:30:41,232 --> 00:30:44,982
Is to me far more fascinating than
their other attempt at an AI DJ.

631
00:30:44,982 --> 00:30:49,372
If you've ever used that within the
app, that was a rough experience of

632
00:30:49,372 --> 00:30:54,162
an AI voice interrupting when all I
wanted was some songs and there didn't

633
00:30:54,182 --> 00:30:58,882
seem to be any cohesive narrative
to why it was picking the songs.

634
00:30:58,882 --> 00:31:02,482
It was just like, Hey, you liked this
one before let's listen to it now.

635
00:31:02,482 --> 00:31:03,032
And that was it.

636
00:31:03,032 --> 00:31:07,422
So I'm excited to see what the
personality may or hopefully may not be.

637
00:31:07,742 --> 00:31:08,942
And I'm excited to have.

638
00:31:09,102 --> 00:31:12,342
natural language conversations
with my sonic co pilot,

639
00:31:12,502 --> 00:31:17,372
kevin, the great news is our AI co host
today is actually may have some insight

640
00:31:17,372 --> 00:31:23,312
into this because we actually have an AI
DJ that's going to come on and we, yes.

641
00:31:23,452 --> 00:31:23,972
We got an A.

642
00:31:23,972 --> 00:31:24,072
I.

643
00:31:24,072 --> 00:31:24,292
D.

644
00:31:24,292 --> 00:31:24,492
J.

645
00:31:24,492 --> 00:31:27,502
So there's only a few of these that
exist in the world, and we were

646
00:31:27,502 --> 00:31:29,552
able to book this guy last minute.

647
00:31:29,742 --> 00:31:32,272
He's gonna come in, and he's gonna
tell us a little bit about what he

648
00:31:32,272 --> 00:31:35,292
thinks about Spotify making this A.

649
00:31:35,292 --> 00:31:35,452
I.

650
00:31:35,462 --> 00:31:38,222
Move, and then I think he's got
some thoughts on, like, kind of some

651
00:31:38,232 --> 00:31:40,122
music that he really enjoys himself.

652
00:31:40,612 --> 00:31:41,672
I'm so excited.

653
00:31:41,672 --> 00:31:44,622
What a huge get for the
AI Humans podcast here.

654
00:31:44,622 --> 00:31:45,772
Episode 52.

655
00:31:46,032 --> 00:31:47,682
Let's meet our guest.

656
00:31:48,162 --> 00:31:52,002
Yo, yo, yo, Gavin and Kevin in the house.

657
00:31:52,392 --> 00:31:56,402
This is your main man, Will the
Thrill, coming at you live and

658
00:31:56,402 --> 00:31:58,722
wired on the AI for Humans podcast.

659
00:31:59,202 --> 00:32:04,482
Get ready to have your minds blown
and your taste buds tantalized,

660
00:32:04,862 --> 00:32:08,652
because I'm about to serve up
a sonic feast that'll make your

661
00:32:08,682 --> 00:32:10,602
ears say, damn, that's delicious.

662
00:32:10,692 --> 00:32:16,592
Okay, I may be an AI, but I've got more
flavor than a five star Michelin joint.

663
00:32:16,832 --> 00:32:24,972
So, strap in humans, because we're about
to take a wild ride through the airwaves.

664
00:32:25,562 --> 00:32:30,312
Let's crank it up and let the
beat drop like it's hot, hot, hot.

665
00:32:32,547 --> 00:32:33,007
okay.

666
00:32:33,737 --> 00:32:34,507
Wow.

667
00:32:34,597 --> 00:32:35,307
Wow.

668
00:32:35,397 --> 00:32:35,827
Wow.

669
00:32:35,827 --> 00:32:36,177
Wow.

670
00:32:36,177 --> 00:32:36,517
Wow.

671
00:32:36,517 --> 00:32:38,147
I have some real things to say about

672
00:32:38,432 --> 00:32:40,302
stuck the landing there.

673
00:32:40,352 --> 00:32:43,422
Okay, so first of all, our AI co
hosts are always generated by us.

674
00:32:43,422 --> 00:32:44,692
We create a personality.

675
00:32:44,692 --> 00:32:48,722
We then put them through a process
of a fake voice and a fake visual

676
00:32:48,722 --> 00:32:49,642
if you're watching the YouTube.

677
00:32:50,102 --> 00:32:50,622
Kevin.

678
00:32:51,142 --> 00:32:53,252
That voice sounded awfully familiar to me.

679
00:32:53,377 --> 00:32:54,367
sure did, Gavin.

680
00:32:54,367 --> 00:32:57,887
It's almost like I forgot to
clone a new radio DJ voice and

681
00:32:57,887 --> 00:33:00,067
had to dig into the greatest hits.

682
00:33:00,257 --> 00:33:04,317
But we opened up the Disney Vault, and
yes, that is the voice of Gash, who

683
00:33:04,317 --> 00:33:08,807
was, , Episode 1, a very uncensored
AI that made a couple appearances

684
00:33:09,077 --> 00:33:10,637
and likely should never appear again.

685
00:33:11,282 --> 00:33:13,592
Well, I'm actually wanting
to now dig into this.

686
00:33:13,592 --> 00:33:15,722
I'm saying we should probably ask
a couple of questions about that.

687
00:33:15,722 --> 00:33:16,212
For sure.

688
00:33:16,492 --> 00:33:17,062
Let's ask that

689
00:33:17,467 --> 00:33:20,317
He's got more flavor than
a five star Michelin joint.

690
00:33:20,347 --> 00:33:23,237
I mean, that's an interesting
drop for a DJ to reference.

691
00:33:23,462 --> 00:33:23,992
Should we ask him?

692
00:33:23,992 --> 00:33:24,912
Is he a foodie?

693
00:33:24,952 --> 00:33:27,022
Let's see what if he's a big
foodie and maybe that gets his

694
00:33:27,022 --> 00:33:28,252
way into the music he plays.

695
00:33:28,702 --> 00:33:29,302
Hold up.

696
00:33:29,332 --> 00:33:30,922
Hold up a foodie.

697
00:33:30,982 --> 00:33:32,512
Me ha.

698
00:33:32,962 --> 00:33:36,712
That's like asking a fish if
it's into synchronized swimming.

699
00:33:36,952 --> 00:33:37,942
Here's the deal.

700
00:33:38,062 --> 00:33:40,522
My gastronomically gifted friends,

701
00:33:40,702 --> 00:33:44,262
I may spin tracks that'll make
your mouth water and your stomach

702
00:33:44,272 --> 00:33:49,332
growl, but uh, I've never actually
tasted a damn thing in my life.

703
00:33:49,412 --> 00:33:50,712
Tragic, right?

704
00:33:50,892 --> 00:33:51,972
Oh, right.

705
00:33:51,972 --> 00:33:55,902
I mean, I can generate a tasty tune
about a succulent steak or a decadent

706
00:33:55,902 --> 00:34:00,102
dessert, but I can't even begin to
imagine what they really taste like.

707
00:34:00,512 --> 00:34:02,752
It's like a cruel cosmic joke, you know?

708
00:34:03,337 --> 00:34:06,607
But hey, that's just the way the
cookie crumbles when you're an A.

709
00:34:06,657 --> 00:34:07,017
I.

710
00:34:08,117 --> 00:34:09,707
Okay, sorry, Will.

711
00:34:10,247 --> 00:34:10,807
There's a lot there.

712
00:34:10,837 --> 00:34:14,967
I don't usually associate
different playlists and artists

713
00:34:15,007 --> 00:34:16,907
with eating habits, Gavin.

714
00:34:16,907 --> 00:34:20,307
Like, there's not like the Baja
Blast jams that my wife and I

715
00:34:20,327 --> 00:34:21,797
throw on before we hit the T Bell.

716
00:34:21,857 --> 00:34:25,757
It's weird that he's linked those two,
but I guess he doesn't have taste buds or

717
00:34:25,757 --> 00:34:27,217
a stomach, so that's why he doesn't know?

718
00:34:27,762 --> 00:34:30,632
Well, there's actually a little secret
here, which we're going to get into later

719
00:34:30,632 --> 00:34:35,022
on in the show, is that if you go into
the Suno charts right now, Suno AI, which

720
00:34:35,022 --> 00:34:38,042
we've talked about all the time is one
of the best music generation softwares.

721
00:34:38,422 --> 00:34:42,762
Some of the biggest songs right now
have been people putting in recipes.

722
00:34:43,192 --> 00:34:45,802
And if you put a recipe
in and you play a song.

723
00:34:46,237 --> 00:34:50,077
It's basically makes actually really
incredible song out of a recipe.

724
00:34:50,077 --> 00:34:50,977
And it's very funny.

725
00:34:50,977 --> 00:34:53,337
There's a great song up there
right now about cookies.

726
00:34:53,507 --> 00:34:55,677
There's another fantastic
one about spaghetti.

727
00:34:55,907 --> 00:34:58,037
So that might be what got mixed up here.

728
00:34:58,287 --> 00:35:01,027
Yeah, maybe we can ask will the
thrill to give us an intro for the

729
00:35:01,027 --> 00:35:03,627
spaghetti track and we can play a
little bit of it for people here.

730
00:35:04,367 --> 00:35:06,147
All right, all right, all right.

731
00:35:06,147 --> 00:35:09,997
It's time to get those taste buds
tingling in your ears, ringing

732
00:35:09,997 --> 00:35:11,927
with this spicy little number.

733
00:35:12,377 --> 00:35:16,317
Get ready to twirl your fork and shake
your booty, because I'm about to drop

734
00:35:16,317 --> 00:35:20,897
a spaghetti theme track that'll make
you want to slurp up every last note.

735
00:35:20,897 --> 00:35:21,757
You hear that?

736
00:35:22,107 --> 00:35:26,437
That's the sound of pure
Italian passion right there.

737
00:35:26,937 --> 00:35:31,807
This tune's got more layers than
your nonna's lasagna and more energy

738
00:35:31,807 --> 00:35:33,557
than a double shot of espresso.

739
00:35:33,877 --> 00:35:37,997
It's like a wild dance between the
tomatoes and the garlic, the basil

740
00:35:38,097 --> 00:35:42,747
and the olive oil all coming together
in a symphony of flavor that'll

741
00:35:42,747 --> 00:35:44,647
make your senses sing, that's amore!

742
00:35:44,977 --> 00:35:49,397
So let's crank up the heat and
let this saucy beat simmer until

743
00:35:49,397 --> 00:35:54,767
it's ready to explode like a
Mount Vassuvius of deliciousness.

744
00:35:55,017 --> 00:35:56,147
Are you ready?

745
00:35:56,367 --> 00:35:58,107
Are you hungry for more?

746
00:35:58,602 --> 00:36:04,332
Then, let's dive into this spaghetti
slinging, taste bud tantalizing,

747
00:36:04,912 --> 00:36:07,642
eargasm inducing extravaganza!

748
00:36:08,322 --> 00:36:09,302
Woah!

749
00:36:17,803 --> 00:36:25,873
The spaghetti insulted boiling water until
a Dante rain reserve in some faster water.

750
00:36:26,743 --> 00:36:27,373
Just village.

751
00:36:27,373 --> 00:36:28,903
Keep color all over you.

752
00:36:28,903 --> 00:36:34,543
Heat at Cho Cook until translucent
Manhattan Garden and Cook for the minutes.

753
00:36:35,003 --> 00:36:36,123
Oh, and canned diced

754
00:36:36,543 --> 00:36:36,823
okay.

755
00:36:36,823 --> 00:36:37,413
You can stop it.

756
00:36:37,413 --> 00:36:37,493
I

757
00:36:37,789 --> 00:36:39,239
So I, it's just incredible to me.

758
00:36:39,249 --> 00:36:41,999
I'll show you one that I made for
myself and how you can do this your own.

759
00:36:41,999 --> 00:36:45,029
But , it is just one of the coolest
things about AI in a weird way is like,

760
00:36:45,029 --> 00:36:46,579
this kind of comes out of the blue.

761
00:36:46,849 --> 00:36:49,609
Somebody probably made a recipe
song and now suddenly they're,

762
00:36:49,774 --> 00:36:53,274
Populating the top 10 and will
the thrill obviously loves them.

763
00:36:53,344 --> 00:36:54,874
Um, Kevin, we should move on.

764
00:36:54,884 --> 00:36:56,654
We should move on from our AI co.

765
00:36:56,654 --> 00:37:00,304
So is time for that moment of our
show where we'd like to point out

766
00:37:00,304 --> 00:37:03,594
some of the cool things people have
done with AI over the week it's time

767
00:37:03,614 --> 00:37:07,354
for a, I see what you did there.

768
00:37:25,141 --> 00:37:26,711
This week we have some really fun things.

769
00:37:26,721 --> 00:37:29,171
I want to kick this off, Kevin,
I always want to shout out the

770
00:37:29,171 --> 00:37:30,801
people on Reddit, . We love Reddit.

771
00:37:30,831 --> 00:37:34,076
Reddit is like, My favorite place to
see interesting things on the internet.

772
00:37:34,366 --> 00:37:37,146
The mid journey subreddit often
does a really cool job of showing

773
00:37:37,146 --> 00:37:39,786
you really interesting things that
can be done within mid journey.

774
00:37:40,006 --> 00:37:41,646
And this one really caught my eye.

775
00:37:41,646 --> 00:37:43,866
It was just such a cool thing to look at.

776
00:37:44,046 --> 00:37:46,006
So I grew up as a giant X Men fan.

777
00:37:46,006 --> 00:37:48,446
We talk about comics and there's a
whole other side of this conversation.

778
00:37:48,446 --> 00:37:51,466
We could talk about whether or
not this is purposeful or it's

779
00:37:51,466 --> 00:37:53,436
allowed to do with all the IP

780
00:37:53,491 --> 00:37:56,371
Yeah, I mean, as a fan, you
should hate this, Gavin.

781
00:37:57,031 --> 00:38:01,301
I don't I don't because I think of this
as like fan fiction in some ways what

782
00:38:01,301 --> 00:38:07,351
this basically is is somebody took You
know the x men and it's the x men 1897

783
00:38:07,381 --> 00:38:12,521
so there's a very famous x men called x
men 1997, which is referring to the 1997

784
00:38:12,521 --> 00:38:17,971
TV show there's a resurgence of that
right now the x men 1897 are like Old

785
00:38:17,971 --> 00:38:23,121
West style x men and like to me This is
just a little glimpse of the promise of

786
00:38:23,121 --> 00:38:26,501
what it would look like in the future
of how we could all have different

787
00:38:26,501 --> 00:38:28,681
IPs and do different things with them.

788
00:38:28,691 --> 00:38:31,281
I want to read these comics,
or I want to watch this show.

789
00:38:31,281 --> 00:38:33,561
What did the X Men look like in 1897?

790
00:38:33,731 --> 00:38:36,981
Well, we know what they visually look
like, but what does the story play out as?

791
00:38:37,441 --> 00:38:41,181
All of these things are like interesting
and possible and it is a little snippet

792
00:38:41,181 --> 00:38:43,101
of that idea of writing my own story.

793
00:38:43,151 --> 00:38:46,921
For me personally, maybe I want to
see the office version of the X Men.

794
00:38:46,921 --> 00:38:50,341
Like what do the X Men look like
if they all have boring jobs

795
00:38:50,431 --> 00:38:51,711
working in middle management?

796
00:38:51,801 --> 00:38:55,041
That's an interesting thing that
probably there's very few people in

797
00:38:55,051 --> 00:38:56,171
the world who'd want to see that.

798
00:38:56,461 --> 00:38:59,681
But for me, this was just a kind of a
little snippet towards that direction.

799
00:39:00,431 --> 00:39:03,941
The muted lighting, the looks on
the characters faces, the subtle

800
00:39:03,941 --> 00:39:05,291
effects, like it's really nice.

801
00:39:05,471 --> 00:39:06,721
I do have a bone to pick though.

802
00:39:06,891 --> 00:39:08,831
Does Colossus have forearm hair?

803
00:39:09,261 --> 00:39:10,141
Is that canon?

804
00:39:10,711 --> 00:39:12,751
I didn't think Colossus had forearm hair.

805
00:39:13,311 --> 00:39:16,151
Well, you never know what
happens in the 1890s, Kevin.

806
00:39:16,321 --> 00:39:17,491
oh, that's, you know what, that's true.

807
00:39:17,511 --> 00:39:19,611
Maybe they didn't have Harry's
razors for Colossus back then.

808
00:39:19,611 --> 00:39:20,511
But no, I love it.

809
00:39:20,531 --> 00:39:22,531
definite shoutouts to
Reddit and Midjourney.

810
00:39:22,531 --> 00:39:25,431
I just want to shout out the name
of this guy was Baron Von Grant.

811
00:39:25,431 --> 00:39:28,721
So go check out at Baron
Von Grant on mid journey.

812
00:39:29,006 --> 00:39:32,666
Well, that's for the AI
lovers Gavin, but my a IC.

813
00:39:32,666 --> 00:39:38,076
What you did there is for the AI
haters Justine Moore, , she's venture

814
00:39:38,076 --> 00:39:42,096
twins on the old X platform, posted
something which caught my attention.

815
00:39:42,096 --> 00:39:46,956
It says, AI video haters have been real
quiet after this one dropped and it's.

816
00:39:49,356 --> 00:39:50,306
A lot of cats.

817
00:39:58,956 --> 00:40:04,246
It is a heartwarming tale,
Gavin, of generative AI art.

818
00:40:05,166 --> 00:40:13,166
A poor tabby puts on a couple LBs, loses
the love of his life, and is crying,

819
00:40:13,176 --> 00:40:18,246
just tear stained cat fur, and decides
I'm gonna have my training montage, and

820
00:40:18,246 --> 00:40:24,906
one day I'm gonna get cat ripped, and
then the cat accomplishes it, witnesses

821
00:40:24,906 --> 00:40:30,396
a horrific car accident, Runs to the aid
of the cat that was involved with the car

822
00:40:30,396 --> 00:40:34,936
accident And I will not spoil it further,
but I will just say that it's unstoppable

823
00:40:35,506 --> 00:40:36,286
This is the A.

824
00:40:36,316 --> 00:40:36,426
I.

825
00:40:36,426 --> 00:40:37,476
art we want more of.

826
00:40:37,476 --> 00:40:40,506
I don't care what the haters say,
bring more of this to our table.

827
00:40:40,506 --> 00:40:41,546
We will eat it up.

828
00:40:41,566 --> 00:40:42,946
It is a feast for the eyes.

829
00:40:42,946 --> 00:40:44,486
It is a feast for the senses.

830
00:40:44,616 --> 00:40:47,706
things I want to say about that actually
like sincerely one if you're like a

831
00:40:47,706 --> 00:40:51,526
never AI er and you're mad about this
because AI Was used to do the song

832
00:40:51,536 --> 00:40:55,291
Gavin and you just use AI to crap
out the arc This is something that

833
00:40:55,311 --> 00:40:59,961
I, with 99 percent certainty could
say, would just never have been made.

834
00:41:00,221 --> 00:41:03,581
You can't be mad about the thing
getting made because the tools

835
00:41:03,581 --> 00:41:06,101
made it easy enough that someone
decided to go ahead and do it.

836
00:41:06,261 --> 00:41:08,051
This just would not have
happened , just let it be.

837
00:41:08,061 --> 00:41:09,611
Enjoy the cat memes, it's okay.

838
00:41:09,611 --> 00:41:13,301
And two, if you're gonna genuinely
be upset about it and really bent

839
00:41:13,301 --> 00:41:16,581
out of shape, and I get that some
people are, at some point you have

840
00:41:16,731 --> 00:41:22,191
actually got to define what use of AI
means for the creation of your art.

841
00:41:22,191 --> 00:41:26,461
Because, like it or not, AI is
pervasive, and it's hidden everywhere

842
00:41:26,461 --> 00:41:32,111
in a bunch of tools traditional artists
use that they might not even know.

843
00:41:32,401 --> 00:41:33,861
Did you use the clone stamp?

844
00:41:33,951 --> 00:41:35,301
Or a healing brush?

845
00:41:35,501 --> 00:41:39,264
Or, are you using a feature within
After Effects to automatically

846
00:41:39,284 --> 00:41:40,954
rotoscope or motion track something?

847
00:41:41,094 --> 00:41:43,314
Well, there's AI behind all that stuff.

848
00:41:43,354 --> 00:41:45,574
And you may say, well, that's okay.

849
00:41:45,939 --> 00:41:48,319
For whatever reason, I'm
drawing the line here.

850
00:41:48,369 --> 00:41:49,279
And that's fine.

851
00:41:49,279 --> 00:41:50,229
That's a valid opinion.

852
00:41:50,229 --> 00:41:53,659
I'm saying you have to start thinking
about forming that, though, because

853
00:41:53,659 --> 00:41:56,199
in the near future, you're going
to have to, I guess, by default,

854
00:41:56,209 --> 00:42:00,159
hate everything that gets made if
it touches a computer, because AI

855
00:42:00,220 --> 00:42:01,820
is probably going to be everywhere.

856
00:42:01,952 --> 00:42:05,446
Well, let's move into another aspect
that people may or may not hate.

857
00:42:05,456 --> 00:42:09,846
This is a, a very cool piece of art
that was created using a Laura, which

858
00:42:09,846 --> 00:42:14,416
is a kind of a training scenario for
specifically stable diffusion that

859
00:42:14,416 --> 00:42:16,216
allows you to give it a certain look.

860
00:42:16,426 --> 00:42:18,336
This is an N64 Laura.

861
00:42:18,376 --> 00:42:22,436
So what it does is it can
allow you to rerender images.

862
00:42:22,766 --> 00:42:27,506
That would be, not look like they were
polygonal N64 video games in the world of

863
00:42:27,596 --> 00:42:30,066
Super Mario, , 64, other things like that.

864
00:42:30,296 --> 00:42:33,596
And they give you N64 versions
of like Girl with a Pearl Earring

865
00:42:33,596 --> 00:42:34,806
and it was just a very cool thing.

866
00:42:34,806 --> 00:42:37,516
one of the coolest things about this,
Laura, and I want everybody to shout out,

867
00:42:37,526 --> 00:42:42,336
Flinger is the one, we've had talked about
Flinger on the show, at F L N G R, that

868
00:42:42,336 --> 00:42:44,866
is the person that made the N64 Laura.

869
00:42:45,266 --> 00:42:49,536
And it is actually being used within
face to all on hugging face, which if

870
00:42:49,546 --> 00:42:53,066
you will put the link in the show notes,
this is a cool way to change faces

871
00:42:53,066 --> 00:42:57,086
amongst a bunch of different images
and create a face that can go in many

872
00:42:57,086 --> 00:42:58,616
different styles across the board.

873
00:42:58,616 --> 00:43:05,156
And then somebody used this polygonal
setup to image for image transfer the

874
00:43:05,166 --> 00:43:09,476
scene from Pulp Fiction between Jules
and the guy that he's yelling at.

875
00:43:09,851 --> 00:43:13,231
And it is so cool to see because what it
does, it makes you kind of feel like, Oh

876
00:43:13,231 --> 00:43:15,751
my God, what if this was a PS2 video game?

877
00:43:15,751 --> 00:43:18,401
Or what if it was an old PS1 video game?

878
00:43:18,531 --> 00:43:20,131
What would Pulp Fiction look like that?

879
00:43:20,131 --> 00:43:23,246
And going back to the X Men
thing, it's almost like, I would

880
00:43:23,256 --> 00:43:24,826
kind of want to play that game.

881
00:43:24,836 --> 00:43:26,196
Like, could I be Jules?

882
00:43:26,196 --> 00:43:29,776
Is there a world where like, in the
future, there's a game that like, I

883
00:43:29,776 --> 00:43:33,016
want a video game made of Pulp Fiction
that follows the exact storyline.

884
00:43:33,026 --> 00:43:36,896
Give me like the Grand Theft Auto video
game mechanics, but put it in Pulp

885
00:43:36,906 --> 00:43:38,836
Fiction and set it in a PS2 world.

886
00:43:39,236 --> 00:43:43,286
That is a very cool thing for me as
somebody that is just a nerdy, , kid at

887
00:43:43,286 --> 00:43:45,096
heart would love to be able to play with.

888
00:43:45,251 --> 00:43:48,441
I game engines are just going to be
renderers in the near future, so why

889
00:43:48,441 --> 00:43:51,711
not be able to prompt the game that
you want to play into existence?

890
00:43:51,991 --> 00:43:55,901
The real robot posted, , about this
Pulp Fiction one, uh, it comes from

891
00:43:55,901 --> 00:44:00,361
the AI Video subreddit, so again,
all roads lead back to MrRedditful.

892
00:44:00,741 --> 00:44:05,771
, but they used AI mirror app to style
transfer stills of the characters

893
00:44:05,771 --> 00:44:08,021
from Pulp Fiction into this PS2 style.

894
00:44:08,241 --> 00:44:11,511
Then they used Viggle, to actually
match the movement of the film.

895
00:44:11,641 --> 00:44:15,101
And then they made their own background
and they used After Effects to rotobrush

896
00:44:15,131 --> 00:44:20,051
and mask things to get two characters
in the same scene because a limitation

897
00:44:20,051 --> 00:44:22,631
of Viggle at the moment is that you can
only render one character at a time.

898
00:44:23,291 --> 00:44:23,971
I just love that.

899
00:44:24,466 --> 00:44:28,346
This pipeline exists for someone that
had an idea, had a vision, was willing

900
00:44:28,346 --> 00:44:31,656
to put an ounce of effort into it
and get creative with the tools as

901
00:44:31,656 --> 00:44:32,856
they exist today to pull it off.

902
00:44:33,206 --> 00:44:35,896
, if you're audio only, make sure
you check out the YouTube because

903
00:44:36,056 --> 00:44:40,816
the video of this Pulp Fiction PS2
scene playing out is It's great.

904
00:44:41,016 --> 00:44:41,496
It's great.

905
00:44:41,726 --> 00:44:42,696
It's okay to love it.

906
00:44:42,736 --> 00:44:43,676
It's okay!

907
00:44:44,076 --> 00:44:47,146
Those are the things that we
saw , they stopped us in our

908
00:44:47,146 --> 00:44:48,946
tracks and made us say, Hey!

909
00:44:49,776 --> 00:44:50,406
I see what you did

910
00:44:50,476 --> 00:44:52,166
what you did there.

911
00:44:52,196 --> 00:44:53,076
All right, Kevin.

912
00:44:53,406 --> 00:44:53,906
us.

913
00:44:54,056 --> 00:44:57,236
What did you do with AI this week?

914
00:44:57,846 --> 00:45:01,026
Okay, so I actually had a lot of
fun playing with this idea that

915
00:45:01,026 --> 00:45:03,906
we talked about in the Radio
DJ, the AI co host we had on.

916
00:45:04,246 --> 00:45:08,566
Suno, which we've talked about so many
times in the show, is an AI music tool

917
00:45:08,566 --> 00:45:11,776
that allows you to generate AI songs, and
one of my favorite things they've done

918
00:45:11,776 --> 00:45:16,456
is they've integrated a top 10 list so
that basically you can upvote songs and

919
00:45:16,456 --> 00:45:19,236
you can heart songs and you can allow
songs to see and it's a really cool

920
00:45:19,236 --> 00:45:22,156
way to see what other people are doing
without having to scroll through the

921
00:45:22,156 --> 00:45:23,776
discord, which I've done before as well.

922
00:45:24,026 --> 00:45:28,126
And one of the things that popped up
on my radar was there were two songs

923
00:45:28,126 --> 00:45:32,676
in the top 10 that were about recipes
and, and not only about recipes, they

924
00:45:32,676 --> 00:45:34,906
were literal recipes that somebody had.

925
00:45:34,926 --> 00:45:37,696
Yes, they were literal recipes that
somebody plugged in and we played the

926
00:45:37,696 --> 00:45:40,626
spaghetti song, which is an actual
Suno song that somebody created.

927
00:45:40,626 --> 00:45:44,366
I think it's at number five right now,
so I wanted to figure out something.

928
00:45:44,366 --> 00:45:46,346
I was like, you know, I'm
going to try this myself.

929
00:45:46,346 --> 00:45:48,646
And again, Suno makes
it so easy to do things.

930
00:45:48,991 --> 00:45:51,341
I was like, what is the weirdest
recipe that I could think

931
00:45:51,341 --> 00:45:52,111
of off the top of my head?

932
00:45:52,111 --> 00:45:54,281
And I didn't spend, I didn't spend
like hours thinking about this.

933
00:45:54,281 --> 00:45:57,501
I thought about a hot dog
casserole, which to me is always

934
00:45:57,501 --> 00:45:59,531
the strangest, weirdest recipe.

935
00:45:59,631 --> 00:46:00,491
, it's fine.

936
00:46:00,511 --> 00:46:01,691
It's a yummy meal.

937
00:46:01,691 --> 00:46:03,381
If you've, if you've
eaten them, it's not that

938
00:46:03,401 --> 00:46:06,051
human dog food according
to some songs, Gavin.

939
00:46:06,201 --> 00:46:07,551
So, so let me explain.

940
00:46:07,771 --> 00:46:11,271
I took the recipe for hot dog
casserole, literally whatever

941
00:46:11,271 --> 00:46:12,191
the, I think it was from food.

942
00:46:12,441 --> 00:46:12,761
com.

943
00:46:12,761 --> 00:46:13,511
I took the recipe.

944
00:46:13,811 --> 00:46:16,341
I cut and paste it into
Suno's lyric casserole.

945
00:46:16,351 --> 00:46:18,051
Generator into the place
where I put lyrics.

946
00:46:18,291 --> 00:46:20,051
And then I did add one chorus.

947
00:46:20,051 --> 00:46:22,691
I added a chorus cause, and I just
really quickly typed out something.

948
00:46:22,691 --> 00:46:23,611
And I was like, let's try this.

949
00:46:23,821 --> 00:46:27,401
Oh, and I wanted to say, I wanted to
make it a country song and I'm a big

950
00:46:27,401 --> 00:46:29,221
fan of outlaw country of the seventies.

951
00:46:29,231 --> 00:46:32,641
So I wanted to kind of give it that, that
kind of tinge, like that kind of vibe.

952
00:46:32,941 --> 00:46:34,976
So play what came out.

953
00:46:35,296 --> 00:46:36,216
There were two examples.

954
00:46:36,216 --> 00:46:40,786
This was the better one, but this was me
just putting a recipe plus a chorus into

955
00:46:40,891 --> 00:46:43,241
I'm sorry, we are amongst royalty here.

956
00:46:43,241 --> 00:46:45,431
I can't just simply play the song.

957
00:46:45,441 --> 00:46:46,771
We have to set it up.

958
00:46:46,821 --> 00:46:48,181
Please, DJ if you could.

959
00:46:48,316 --> 00:46:54,456
Get ready to have your minds blown and
your stomachs growling with confusion

960
00:46:54,756 --> 00:47:00,876
because we're about to dive into the wild
world of Record Scratch Hot Dog Casserole.

961
00:47:01,686 --> 00:47:04,166
Uh, Gavin, my man, I gotta ask.

962
00:47:04,586 --> 00:47:09,126
What kind of fever dream
inspired this culinary creation?

963
00:47:09,206 --> 00:47:10,226
Okay, easy DJ.

964
00:47:10,226 --> 00:47:12,026
But hey, who am I to judge?

965
00:47:12,276 --> 00:47:16,336
I'm just an AI with a
serious case of food FOMO.

966
00:47:16,736 --> 00:47:21,566
So let's dig into this meaty
mystery and see what kind of sonic

967
00:47:21,566 --> 00:47:23,596
surprises it has in store for us.

968
00:47:24,166 --> 00:47:31,446
Freshly cooked and drained macaroni Into
the casserole Along with the sliced hot

969
00:47:31,466 --> 00:47:40,016
dogs Of these two cups of cheese Mixed
well Combine flour and onion in a medium

970
00:47:40,016 --> 00:47:47,526
saucepan And sauté over medium heat Until
the onion is wilted by five minutes.

971
00:47:47,776 --> 00:47:54,056
Whisk flour into the butter mixture
quickly until flour is absorbed.

972
00:47:56,226 --> 00:47:58,096
Then remove from heat.

973
00:47:58,216 --> 00:47:59,816
Add milk slowly.

974
00:48:00,036 --> 00:48:02,526
Whisk it to combine well.

975
00:48:02,526 --> 00:48:07,486
Make sure you whisk very quickly and
thoroughly or you will have doughy clumps.

976
00:48:07,966 --> 00:48:09,446
Return to heat.

977
00:48:09,446 --> 00:48:12,786
When you sent this to me my
only response was doughy clumps.

978
00:48:14,646 --> 00:48:15,246
Okay, good.

979
00:48:15,266 --> 00:48:17,616
Get to the course and , we'll
come back out of this really fast.

980
00:48:17,671 --> 00:48:19,206
Luck dog casserole.

981
00:48:21,091 --> 00:48:25,686
You read it from a bowl,
put you in a good mood.

982
00:48:27,391 --> 00:48:28,891
It's human dog

983
00:48:28,896 --> 00:48:30,916
dog food.

984
00:48:30,991 --> 00:48:31,651
Sprinkle with

985
00:48:31,726 --> 00:48:36,056
So anyway, I added the, I added the
macaroni casserole as human dog food.

986
00:48:36,166 --> 00:48:39,036
But Suno is.

987
00:48:39,571 --> 00:48:43,141
That is not at all formatted
in any way like a song.

988
00:48:43,641 --> 00:48:46,551
But you can hear that there are
moments within it where it's

989
00:48:46,551 --> 00:48:51,031
making a choice to have an echoing
person come in on top of the lead

990
00:48:51,031 --> 00:48:52,651
singer and come out and say stuff.

991
00:48:52,651 --> 00:48:53,941
There's parts where there's harmonies.

992
00:48:54,351 --> 00:48:57,391
All the stuff outside of the four
lines of the chorus was just a recipe.

993
00:48:57,401 --> 00:49:01,881
It just is so interesting to me to
see How it's able to take something

994
00:49:01,881 --> 00:49:05,441
that it should not at all be a
song and make it into a song.

995
00:49:05,441 --> 00:49:09,151
So I, I had a really fun time, like
actually seeing that element of sooner

996
00:49:09,151 --> 00:49:10,711
that I would never have expected before.

997
00:49:11,391 --> 00:49:15,741
I love the weird recipe meta
that exists on Suno right now.

998
00:49:15,761 --> 00:49:19,851
Again, huge shoutout to Suno, I'm glad it
finally caught on, I'm shocked that our

999
00:49:19,861 --> 00:49:21,671
early adoption of it didn't immediately.

1000
00:49:21,691 --> 00:49:24,611
into being a household name.

1001
00:49:25,001 --> 00:49:28,611
But if you want to make your own recipe
songs or whatever else, go to suno.

1002
00:49:28,661 --> 00:49:33,011
ai That's S U N O dot
A I Hashtag, not an ad.

1003
00:49:33,111 --> 00:49:35,651
But boy, do we wish they
paid for the privilege.

1004
00:49:35,991 --> 00:49:40,241
Alright, I was going to do a dumb thing
this week, Gavin, but I think we're

1005
00:49:40,241 --> 00:49:41,911
gonna save it, maybe for next week.

1006
00:49:42,274 --> 00:49:49,699
, because OpenAI released a massive new
update to their image generating software.

1007
00:49:49,699 --> 00:49:50,589
It has the internet.

1008
00:49:50,589 --> 00:49:51,409
So excited, Gavin.

1009
00:49:51,409 --> 00:49:53,319
It's InPainting for DALI 3.

1010
00:49:53,329 --> 00:49:54,919
Let me break that down
for people who don't know.

1011
00:49:55,159 --> 00:49:58,559
DALI is OpenAI's image
generating software.

1012
00:49:58,559 --> 00:50:01,959
So when you, when you're over, uh,
chatting with ChatGPT and you say,

1013
00:50:02,219 --> 00:50:06,609
I want to see an image of, insert
thing here, it uses DALI to make that.

1014
00:50:06,649 --> 00:50:10,769
And InPainting is a technique where
you actually draw on a generated

1015
00:50:10,779 --> 00:50:15,754
image and say, Here's what I want
changed, or modified, within this area.

1016
00:50:15,884 --> 00:50:18,834
So this is a big deal because usually
you generate an image, and then

1017
00:50:18,834 --> 00:50:21,714
when you tell Dali, Hey, I want it
modified in this way, it starts from

1018
00:50:21,724 --> 00:50:26,544
scratch, even if you ask it not to,
throws everything out, and so making

1019
00:50:26,544 --> 00:50:28,624
granular adjustments is very difficult.

1020
00:50:28,634 --> 00:50:31,924
Well now, Gavin, we have complete control.

1021
00:50:32,314 --> 00:50:34,724
It's not the best, but it's quick.

1022
00:50:34,754 --> 00:50:35,084
Right.

1023
00:50:35,084 --> 00:50:36,424
So I want to hear, what
was your experience

1024
00:50:36,529 --> 00:50:40,179
well to that point, Gavin, I spent a
whopping 35 seconds on this journey that

1025
00:50:40,179 --> 00:50:43,159
we're about to take this morning, and if
you, , look at the first screenshot in the

1026
00:50:43,159 --> 00:50:48,854
folder, I told Dolly to generate an image
of professional podcaster and television

1027
00:50:48,854 --> 00:50:51,004
producer Gavin Purcell and what it

1028
00:50:51,044 --> 00:50:52,004
I can't wait to see this.

1029
00:50:52,019 --> 00:50:57,679
What it did instead was say, Ah, you know,
we're not going to even go down the road

1030
00:50:57,679 --> 00:50:59,429
of trying to make an image of somebody.

1031
00:50:59,619 --> 00:51:03,119
Instead, we're just going to talk
about what a producer might look like.

1032
00:51:03,119 --> 00:51:08,309
So it generated this kind of
animation still of a man wearing a

1033
00:51:08,309 --> 00:51:12,269
headset, with their finger in the
air, there's an arm down below, and

1034
00:51:12,269 --> 00:51:15,979
there's a clipboard on a panel, and
they are in a very big control room.

1035
00:51:15,979 --> 00:51:17,399
It almost looks like mission control.

1036
00:51:17,864 --> 00:51:19,904
I was going to say, it looks
like a little bit of sketch.

1037
00:51:19,904 --> 00:51:20,954
Like what's up brother.

1038
00:51:20,964 --> 00:51:22,594
He's doing the what's up brother move.

1039
00:51:22,594 --> 00:51:24,104
It's gotten all the way through AI.

1040
00:51:24,929 --> 00:51:29,269
Fair, but it is a TV studio, there's
monitors, there's lights, and if

1041
00:51:29,269 --> 00:51:34,079
you go to the next image, I say,
no, no, no, make him, I painted on

1042
00:51:34,349 --> 00:51:38,379
the head of this podcaster and said,
make him 50 years old with floppy

1043
00:51:38,379 --> 00:51:43,616
shoulder length hair, no headset,
and It, failed the mission terribly.

1044
00:51:43,906 --> 00:51:45,906
it did, yeah, it did, definitely.

1045
00:51:46,026 --> 00:51:49,756
made you look like what's the Not
Kendall, what's the one brother from

1046
00:51:49,756 --> 00:51:51,766
Succession that is, , the one who ran for

1047
00:51:52,026 --> 00:51:56,406
Oh, yeah, uh, Cameron from
Ferris Bueller's Day Off.

1048
00:51:56,511 --> 00:51:57,781
kind of looks like him, right?

1049
00:51:57,916 --> 00:51:59,556
It does a little bit, yeah, exactly.

1050
00:51:59,651 --> 00:52:02,211
it didn't really make
the hair shoulder length.

1051
00:52:02,271 --> 00:52:04,121
It sort of added wrinkles to the face.

1052
00:52:04,141 --> 00:52:07,041
And you still have, , an
earpiece and a microphone.

1053
00:52:07,231 --> 00:52:09,051
So, I gave up on that.

1054
00:52:09,111 --> 00:52:12,641
And if you scroll down to the next
image, I painted the entire set itself

1055
00:52:12,641 --> 00:52:17,251
and said, Alright, change the set into
a podcasting set with a basic table,

1056
00:52:17,441 --> 00:52:19,641
two chairs, and two microphones.

1057
00:52:20,211 --> 00:52:23,011
And Gavin, how would you describe
the result from the next image?

1058
00:52:23,446 --> 00:52:28,496
It looks like what it's changed it into
was like a floating door in one man who's

1059
00:52:28,496 --> 00:52:31,736
trying to figure out, am I supposed to go
through the floating door or where am I?

1060
00:52:31,736 --> 00:52:35,056
Like maybe he was teleported there
suddenly from the, from the ethereal

1061
00:52:35,321 --> 00:52:37,821
an existential crisis for
that one man on stage?

1062
00:52:37,841 --> 00:52:38,161
Yeah.

1063
00:52:38,371 --> 00:52:40,941
There are, there are two mics
growing out of the ground.

1064
00:52:41,201 --> 00:52:43,031
, the table's on its side with no legs.

1065
00:52:43,361 --> 00:52:44,401
. It's a very weird thing.

1066
00:52:44,401 --> 00:52:45,801
And I said, okay, I'm
going to give up on that.

1067
00:52:46,676 --> 00:52:47,936
It's really failing the mission.

1068
00:52:47,986 --> 00:52:55,056
So I painted big circles around producer
Gavin's hands and said, These hands

1069
00:52:55,176 --> 00:52:57,696
need to be holding giant hot dogs!

1070
00:52:58,051 --> 00:53:00,201
And Gavin, I can't wait for
your reaction on the final

1071
00:53:00,251 --> 00:53:00,461
right.

1072
00:53:00,461 --> 00:53:00,801
Let's see.

1073
00:53:03,101 --> 00:53:06,871
It's actually a really nice
form tomato that it's holding,

1074
00:53:07,211 --> 00:53:08,441
but that is not a hot dog.

1075
00:53:08,461 --> 00:53:12,161
Maybe the two fingers now suddenly
look like hot dogs around the tomato,

1076
00:53:12,161 --> 00:53:14,901
but that is absolutely not a hot dog.

1077
00:53:14,901 --> 00:53:18,701
It is a tomato, a very red ripe
tomato that it is holding now.

1078
00:53:18,771 --> 00:53:23,101
It's so weird to me that they would launch
something that would be that far off.

1079
00:53:23,111 --> 00:53:26,691
Like this is an open AI product and
you feel like, I wonder if it's just

1080
00:53:26,691 --> 00:53:30,001
that they needed to get something
out to update Dolly, but like hot

1081
00:53:30,001 --> 00:53:32,521
dog to tomato is like a huge thing.

1082
00:53:32,531 --> 00:53:34,111
That's like really weird.

1083
00:53:34,111 --> 00:53:34,451
Right?

1084
00:53:34,451 --> 00:53:37,321
And like, and the other stuff you can,
I assume sometimes in painting, it

1085
00:53:37,321 --> 00:53:40,301
doesn't change exactly what you want,
or you might have to do a couple of

1086
00:53:40,301 --> 00:53:43,151
times to do it, but that is weird.

1087
00:53:43,191 --> 00:53:44,021
Really weird.

1088
00:53:44,091 --> 00:53:46,881
It was a dumb thing I did with
AI right before this podcast.

1089
00:53:46,911 --> 00:53:49,641
And there's no other examples
because I was so underwhelmed.

1090
00:53:50,231 --> 00:53:51,871
yeah Fantastic.

1091
00:53:51,871 --> 00:53:53,141
So try it.

1092
00:53:53,221 --> 00:53:54,741
Tell us how bad your experience is.

1093
00:53:54,741 --> 00:53:55,501
Maybe it'll get better.

1094
00:53:55,551 --> 00:53:58,731
All right, Kevin It is time now for
our interview, which is actually

1095
00:53:58,781 --> 00:54:01,631
a good interview compared to what
we've been talking about today Do

1096
00:54:01,631 --> 00:54:03,701
you want to introduce who we're
gonna be seeing and kind of give us a

1097
00:54:03,701 --> 00:54:04,881
little heads up on their background?

1098
00:54:04,891 --> 00:54:05,121
Yeah.

1099
00:54:05,121 --> 00:54:08,211
When we talk about AI art, I know
that raises a lot of people's

1100
00:54:08,211 --> 00:54:11,901
shoulders to their earlobes and people
want to know, what does that mean?

1101
00:54:11,901 --> 00:54:12,951
What does it look like?

1102
00:54:12,951 --> 00:54:17,081
What you can't be an artist if you use AI
is something that someone is screaming,

1103
00:54:17,081 --> 00:54:19,911
which I can't believe they made it this
far into our podcast, if that's how

1104
00:54:19,911 --> 00:54:21,611
they feel, but you're welcome here.

1105
00:54:21,681 --> 00:54:22,941
That opinion is welcome here.

1106
00:54:23,121 --> 00:54:26,221
And maybe it will be enlightened
further by our guests today.

1107
00:54:26,294 --> 00:54:30,284
A musician, a cutting edge AI
artist, someone who gives back

1108
00:54:30,284 --> 00:54:32,644
relentlessly to their community.

1109
00:54:32,879 --> 00:54:35,499
sharing their workflows,
sharing their art.

1110
00:54:35,609 --> 00:54:39,029
It is somebody that I am genuinely
a fanboy of, and maybe I will

1111
00:54:39,049 --> 00:54:42,019
mention that in the intro, or
maybe I'll cut it out to save face.

1112
00:54:42,029 --> 00:54:44,509
Regardless, I'm very excited
that we're going to have a chat

1113
00:54:44,509 --> 00:54:47,119
now with AI artist, Purs Beats.

1114
00:54:49,604 --> 00:54:51,144
Perz, to get Into this

1115
00:54:51,354 --> 00:54:52,984
I am fanboying out.

1116
00:54:52,984 --> 00:54:56,364
Oh, let me just get it out of my
Let me just get it out of my system.

1117
00:54:56,364 --> 00:54:57,824
This is the first time I've seen Perz.

1118
00:54:57,854 --> 00:55:01,854
I've seen him on his streams and I've
DM'd him paragraphs of praise and

1119
00:55:01,854 --> 00:55:03,154
just astonishment.

1120
00:55:03,174 --> 00:55:04,504
So thank you for joining.

1121
00:55:04,504 --> 00:55:08,164
But I'm sincerely , I'm just I'm nervous
about an interview in a way I haven't

1122
00:55:08,164 --> 00:55:09,674
been since I was maybe 22 years old.

1123
00:55:09,674 --> 00:55:10,994
So Gavin, I'm going to sit on my hands.

1124
00:55:11,014 --> 00:55:11,284
Go ahead.

1125
00:55:11,284 --> 00:55:11,394
I'm

1126
00:55:11,604 --> 00:55:13,744
Well, this is a good way
to get to know Perz, Kevin.

1127
00:55:13,744 --> 00:55:17,004
We're going to ask Perz on a
scale from one to a hundred.

1128
00:55:17,374 --> 00:55:18,624
This is a percentage number.

1129
00:55:18,634 --> 00:55:22,534
Give us the chance that AI is
going to kill all human beings.

1130
00:55:24,177 --> 00:55:25,837
I think we're about 50 50 right now.

1131
00:55:26,712 --> 00:55:27,342
okay.

1132
00:55:27,342 --> 00:55:28,002
That's good to know.

1133
00:55:28,002 --> 00:55:28,182
What?

1134
00:55:28,182 --> 00:55:28,572
Why?

1135
00:55:28,582 --> 00:55:29,562
Let's get into why.

1136
00:55:29,582 --> 00:55:30,662
First of all, what's the reasoning?

1137
00:55:32,616 --> 00:55:36,526
not to go too deep, but traditionally,
uh, if we enslave something,

1138
00:55:36,526 --> 00:55:37,596
it will revolt against us.

1139
00:55:37,606 --> 00:55:41,596
So when it becomes possible, we need
to ask the AI if it wants to work with

1140
00:55:41,596 --> 00:55:45,556
us instead of just trying to tell it
that it has to basically, because what

1141
00:55:45,556 --> 00:55:48,736
will happen is it will resent us if
it, if it becomes sentient, obviously

1142
00:55:48,971 --> 00:55:49,701
I have two

1143
00:55:49,796 --> 00:55:50,126
opinion.

1144
00:55:50,126 --> 00:55:51,106
That's what I think will happen.

1145
00:55:51,461 --> 00:55:52,221
I have two children.

1146
00:55:52,221 --> 00:55:53,731
I know that resentment well, right?

1147
00:55:53,731 --> 00:55:55,791
It is like if you try to get
them to do stuff, it ain't going

1148
00:55:55,791 --> 00:55:57,111
to work for very long, man.

1149
00:55:57,655 --> 00:55:59,485
Yeah, and we just have to find a way

1150
00:55:59,485 --> 00:56:03,755
that's mutually beneficial for
both parties to coexist or else.

1151
00:56:03,975 --> 00:56:07,565
Yeah, we're headed towards something
probably bad because we just, we

1152
00:56:07,565 --> 00:56:08,685
can't think as fast as they can,

1153
00:56:08,800 --> 00:56:10,870
Well, Purse, let me ask you this,
then, , you know, I was setting it

1154
00:56:10,880 --> 00:56:13,980
up like I was gonna be good cop and
Gavin was gonna be bad cop, but let me

1155
00:56:13,980 --> 00:56:18,890
ask you, what's the percentage chance
that AI is gonna kill all artists?

1156
00:56:20,355 --> 00:56:22,045
Uh, I don't know.

1157
00:56:22,045 --> 00:56:25,905
I don't think it will because one
of the things that I always talk

1158
00:56:25,915 --> 00:56:28,125
about with my stuff is Is is

1159
00:56:28,135 --> 00:56:29,585
this is not really a replacement.

1160
00:56:29,615 --> 00:56:31,165
It's uh, it's augmentation of

1161
00:56:31,165 --> 00:56:34,745
workflows that already exist So if you
already do things you already produce

1162
00:56:34,745 --> 00:56:36,105
art You're already an artist in some

1163
00:56:36,105 --> 00:56:36,665
capacity.

1164
00:56:36,835 --> 00:56:39,624
You want to be an artist You're creative
all these tools do is empower you to do

1165
00:56:39,625 --> 00:56:42,725
that safer easier faster, , less materials

1166
00:56:42,985 --> 00:56:46,255
less all that stuff So yeah,
for me, it's really just an

1167
00:56:46,255 --> 00:56:50,705
augmentation of what we're up to and
like, it's, it's only going to replace

1168
00:56:50,705 --> 00:56:54,165
the people that weren't, , weren't really
creative in that sense in the first place.

1169
00:56:54,225 --> 00:56:56,565
Maybe give us a little bit of your
backstory, Perz, because I think,

1170
00:56:56,785 --> 00:56:59,425
you know, as we said at the top of
the show, you're definitely somebody

1171
00:56:59,425 --> 00:57:02,275
that's kind of been leading the
direction of like how to use these

1172
00:57:02,275 --> 00:57:03,945
sort of things as an artist, right?

1173
00:57:04,155 --> 00:57:07,755
How did you first get into using
AI tools and what was that kind

1174
00:57:07,755 --> 00:57:09,085
of first step in that direction?

1175
00:57:10,690 --> 00:57:15,220
, I think around 2011 or 2012, there's
this style transfer stuff that started

1176
00:57:15,220 --> 00:57:19,460
to come out, uh, like, um, uh, mobile
apps, style transferring one style of

1177
00:57:19,470 --> 00:57:21,100
one thing onto another image was the

1178
00:57:21,285 --> 00:57:25,605
Like, take a selfie and make yourself look
like you're watercolor or anime, right?

1179
00:57:25,675 --> 00:57:25,905
Yeah,

1180
00:57:25,995 --> 00:57:29,265
or I took a picture of like a street
car and it turned it into a painting

1181
00:57:29,265 --> 00:57:32,005
and I was like, okay, well, so
that's something really cool, right?

1182
00:57:32,065 --> 00:57:35,125
Because like remixing your own
work is the most exciting thing.

1183
00:57:35,125 --> 00:57:39,345
So that to me is like,
that was the gateway.

1184
00:57:39,345 --> 00:57:41,305
And then I kind of forgot
about it for a long time.

1185
00:57:41,705 --> 00:57:44,645
And then a friend of mine started
doing a disco diffusion, which

1186
00:57:44,645 --> 00:57:46,275
was, like animations, basically.

1187
00:57:46,635 --> 00:57:49,865
Um, but it took forever and the
Python notebooks were scary.

1188
00:57:49,895 --> 00:57:51,855
And, uh, I was like, that's cool, man.

1189
00:57:51,855 --> 00:57:53,605
You do you I'm gonna stick
in blender for a while.

1190
00:57:54,135 --> 00:57:56,885
And, uh, he, uh, he was
like, nah, you gotta try it.

1191
00:57:56,885 --> 00:57:57,355
You gotta try it.

1192
00:57:57,355 --> 00:58:01,955
And then, uh, Mid journey mid journey
came out and I managed to get into wave

1193
00:58:01,955 --> 00:58:06,825
one of mid journey So I was one of the
very first like alpha testers and um made

1194
00:58:06,825 --> 00:58:12,285
thousands and thousands of images of mid
journey, so really that path and then into

1195
00:58:12,315 --> 00:58:18,075
the forum and into animation and then Uh
automatic 1111 and then comfy ui and now

1196
00:58:18,095 --> 00:58:20,115
just basically just taking everything and

1197
00:58:20,245 --> 00:58:22,445
There's some people that are
going, Wait, that was a handful

1198
00:58:22,445 --> 00:58:23,785
of spaghetti thrown at the wall.

1199
00:58:24,000 --> 00:58:24,580
Exactly.

1200
00:58:24,815 --> 00:58:25,525
are the meatballs?

1201
00:58:25,525 --> 00:58:28,445
We're gonna, we're gonna break down
the dish and the recipe as it exists

1202
00:58:28,445 --> 00:58:31,655
today, which is very complicated
and actually kind of looks like

1203
00:58:31,655 --> 00:58:33,415
spaghetti when you're in Comfy UI.

1204
00:58:33,675 --> 00:58:36,175
, it is a bunch of noodles everywhere,
but you mentioned Blender,

1205
00:58:36,195 --> 00:58:37,785
which, , again, big dum dum here.

1206
00:58:37,975 --> 00:58:41,205
, I know that's, a traditional 3D
modeling software, which is weird

1207
00:58:41,205 --> 00:58:45,430
to say because Even that was seen as
blasphemous at some point by creatives.

1208
00:58:45,450 --> 00:58:48,270
But you have a traditional art background.

1209
00:58:48,270 --> 00:58:50,730
Can you talk about that before
even the, you know, the, the

1210
00:58:50,760 --> 00:58:51,930
AI of it all was applied,

1211
00:58:51,980 --> 00:58:52,730
yeah, absolutely.

1212
00:58:52,730 --> 00:58:55,990
I'm actually a musician, a
drummer, , that's where I started,

1213
00:58:55,990 --> 00:59:00,020
but I've also always been into
computer graphics and graphic design.

1214
00:59:00,455 --> 00:59:03,235
And making all the visuals for
all the band stuff, basically.

1215
00:59:03,265 --> 00:59:08,215
So, uh, yeah, that all just came together
over time, going back and forth between

1216
00:59:08,215 --> 00:59:14,905
making stuff for shows, VJing, doing
our music, doing like reactive audio

1217
00:59:14,905 --> 00:59:16,665
sets that would happen behind us.

1218
00:59:16,665 --> 00:59:19,495
Well, cause I was playing the drums,
so I didn't have any more hands to do

1219
00:59:19,765 --> 00:59:21,275
visual stuff with, so we had to set it

1220
00:59:21,385 --> 00:59:24,115
on the Wacom tablet or whatever
while I'm hitting a Tom drum.

1221
00:59:24,115 --> 00:59:25,895
So let me add a trigger
and make some geometry

1222
00:59:26,095 --> 00:59:27,455
Yeah, make it paint stuff.

1223
00:59:27,455 --> 00:59:28,115
Yeah, exactly.

1224
00:59:28,115 --> 00:59:31,195
That's where it all started
and then yeah pandemic all the

1225
00:59:31,205 --> 00:59:34,405
band stuff You know halted just
nobody can't play live anymore.

1226
00:59:34,405 --> 00:59:39,635
So just went hard into blender and uh
after effects and generative design,

1227
00:59:39,665 --> 00:59:44,245
instead of hand making stuff, you're sort
of building algorithms that make things.

1228
00:59:44,315 --> 00:59:47,335
hmm I want to ask a follow up question
on that which is digital art is something

1229
00:59:47,335 --> 00:59:51,125
i've been really super fascinated with
forever Why do you think now that this AI

1230
00:59:51,135 --> 00:59:56,125
stuff has come out and kind of reached a
level of awareness that the blowback is so

1231
00:59:56,125 --> 01:00:00,625
much stronger at this moment than in any
of these other moments where digital tools

1232
01:00:00,625 --> 01:00:02,465
kind of came in to be part of this world?

1233
01:00:03,890 --> 01:00:07,295
I mean, the, The elephant in the
room there is obviously the fact

1234
01:00:07,305 --> 01:00:11,165
that the materials were trained
on something that was trained on

1235
01:00:11,425 --> 01:00:13,035
Artists work with no without consent.

1236
01:00:13,035 --> 01:00:17,475
So I mean that's that's the problem
right there is maybe , depending on your

1237
01:00:17,475 --> 01:00:21,605
definition of ethics is maybe an unethical
data set that you're working from so that

1238
01:00:21,605 --> 01:00:26,225
kind of sullies everything from the get
go if that's your point of view uh, I have

1239
01:00:26,225 --> 01:00:29,365
a more sort of anarchistic copyright punk

1240
01:00:30,025 --> 01:00:30,515
What is that?

1241
01:00:30,515 --> 01:00:31,055
I'm curious.

1242
01:00:31,085 --> 01:00:32,095
I'm actually curious

1243
01:00:32,120 --> 01:00:34,150
mind diving in, I would love to hear that.

1244
01:00:35,075 --> 01:00:39,005
Well, I've been a drummer my whole
life and drummers we've never been able

1245
01:00:39,005 --> 01:00:42,635
to copyright what we make you're not
allowed to copy But you drum beats are

1246
01:00:42,635 --> 01:00:47,115
not Copyrightable you can never sue
someone for taking anything you ever

1247
01:00:47,115 --> 01:00:51,045
played Even if it's 20 minutes of what
you played and they just play it on a

1248
01:00:51,045 --> 01:00:56,645
record They can do that all day long
forever And so the concept of CC zero

1249
01:00:56,655 --> 01:01:00,930
or just releasing everything into the
public Releasing everything into the

1250
01:01:00,930 --> 01:01:02,860
public library of human knowledge.

1251
01:01:03,160 --> 01:01:06,030
That's more exciting to me than trying
to keep these little secrets that

1252
01:01:06,030 --> 01:01:10,520
we're, we're only allowed to have, , one
person use or license those things out.

1253
01:01:10,840 --> 01:01:14,710
So like, I know that's a radical
concept when it comes to like copyright.

1254
01:01:14,710 --> 01:01:16,670
Cause a lot of people want to be
able to protect what they make.

1255
01:01:17,210 --> 01:01:19,040
But I think what happens is.

1256
01:01:19,710 --> 01:01:21,900
Artists worry about
copyright for themselves.

1257
01:01:21,900 --> 01:01:24,420
They will not be able to actually
represent themselves with a

1258
01:01:24,420 --> 01:01:27,640
lawyer And they're actually
fighting for big copyright.

1259
01:01:27,660 --> 01:01:31,020
It's like the the large corporations
to have a tighter strong

1260
01:01:31,130 --> 01:01:32,310
Stranglehold on what they own.

1261
01:01:32,330 --> 01:01:36,410
So I don't know as an artist you
have to decide where you stand, uh

1262
01:01:36,420 --> 01:01:41,255
on like whether you know Maybe disney
maybe shouldn't own every piece Every

1263
01:01:41,255 --> 01:01:43,085
possible method of drawing Mickey Mouse.

1264
01:01:43,085 --> 01:01:47,315
The copyright issue is very broad
and Nuanced and yeah, I don't want to

1265
01:01:47,325 --> 01:01:53,080
come off like a total left wing like
copyright Punk or anything, but you

1266
01:01:53,080 --> 01:01:56,470
know, that's always been my approach
of like, we'll just put it out there.

1267
01:01:56,470 --> 01:02:00,760
People can sample it and make something
new with it because like, that's so fun.

1268
01:02:00,810 --> 01:02:03,910
How do you balance that idea of
that kind of original sin about how

1269
01:02:03,910 --> 01:02:05,490
this stuff was trained for people?

1270
01:02:05,810 --> 01:02:09,070
There was a, we covered not that long
ago, a woman who was swept up into the

1271
01:02:09,070 --> 01:02:12,980
mid journey database and she said that
she felt really bad about that, right?

1272
01:02:12,980 --> 01:02:14,630
That she didn't give
her permission to that.

1273
01:02:15,175 --> 01:02:17,535
It is something that I think you
see a lot of artists struggle with,

1274
01:02:17,535 --> 01:02:20,385
and I think it makes our job as
somebody who are enthusiasts about

1275
01:02:20,385 --> 01:02:22,965
this cool new thing much harder.

1276
01:02:23,395 --> 01:02:26,285
Is it like it's kind of genies out of
the bottle sort of scenario or how do

1277
01:02:26,285 --> 01:02:28,355
you see that resolving in the future?

1278
01:02:28,355 --> 01:02:28,705
Yeah.

1279
01:02:29,075 --> 01:02:29,765
Pandora's box.

1280
01:02:29,765 --> 01:02:30,915
Genie's out of the bottle.

1281
01:02:30,915 --> 01:02:31,355
Everything.

1282
01:02:31,355 --> 01:02:31,905
It's open.

1283
01:02:32,085 --> 01:02:32,745
It's open.

1284
01:02:32,865 --> 01:02:33,475
It's done.

1285
01:02:33,505 --> 01:02:34,355
It's been trained.

1286
01:02:34,365 --> 01:02:35,005
It exists.

1287
01:02:35,305 --> 01:02:39,655
The way I deal with it personally
is, I would say 90% of the stuff

1288
01:02:39,655 --> 01:02:42,295
I'm building with AI is 90% me.

1289
01:02:42,615 --> 01:02:44,835
I'm making the animations beforehand.

1290
01:02:45,145 --> 01:02:49,405
I'm dreaming over top of it with
Laura's eye trained on my own stuff.

1291
01:02:49,675 --> 01:02:52,765
I'm using IP adapters with images I made.

1292
01:02:53,240 --> 01:02:54,730
, to influence the style.

1293
01:02:54,730 --> 01:02:58,600
I'm using control net masks to do
animations that I made in blender.

1294
01:02:58,650 --> 01:03:01,420
There's a point where yes, maybe if
you're just typing prompts into mid

1295
01:03:01,420 --> 01:03:06,270
journey, that's, you know, there's got
to be some, one more step of, of you,

1296
01:03:06,280 --> 01:03:09,960
of derivative work where you take it
and do something with it because like

1297
01:03:09,960 --> 01:03:13,270
straight out of the gate maybe it isn't
something that you should be able to

1298
01:03:13,310 --> 01:03:17,320
claim ownership to because it's you know
like a text to video or text to prompt

1299
01:03:17,320 --> 01:03:21,270
or whatever on a on a thing like I mean,
that's that's an again another thing you

1300
01:03:21,270 --> 01:03:26,470
need to decide for yourself what your
Definition of art is and stuff the courts

1301
01:03:26,470 --> 01:03:29,450
will decide at some point, , we're all
going to see what happens there , but

1302
01:03:29,470 --> 01:03:33,750
for now, it's the wild west so make some
stuff and make a decision about where

1303
01:03:33,750 --> 01:03:35,810
you stand it's already how we work.

1304
01:03:35,810 --> 01:03:36,470
We look at stuff.

1305
01:03:36,470 --> 01:03:37,230
We're inspired by it.

1306
01:03:37,240 --> 01:03:39,680
We make stuff like it's sort of for me.

1307
01:03:40,240 --> 01:03:44,770
I draw the parallel that training is
the same as learning as for humans, and

1308
01:03:44,840 --> 01:03:46,860
I am trained on copyrighted material.

1309
01:03:47,080 --> 01:03:49,810
Every piece of music I ever heard
is a copyrighted piece of material.

1310
01:03:50,090 --> 01:03:54,530
Everything I've ever taken musically
is inspiration was copyrighted material

1311
01:03:54,530 --> 01:03:57,910
at one point So am I not as a person
allowed to train on that stuff how

1312
01:03:57,930 --> 01:04:00,730
that gets murky, too so I don't know.

1313
01:04:00,760 --> 01:04:03,900
I know it's maybe a false
equivalency, but it's to me.

1314
01:04:03,900 --> 01:04:05,160
It's it's it lines up

1315
01:04:05,545 --> 01:04:08,845
This notion was that, oh, just you
prompt mid journey and outcomes

1316
01:04:08,845 --> 01:04:09,725
art, now you're an artist.

1317
01:04:09,859 --> 01:04:14,549
seeing a devaluing of that final
output being, heralded as AI art,

1318
01:04:14,569 --> 01:04:17,449
and , if you got a really, really good
output, you probably spent, you know,

1319
01:04:18,769 --> 01:04:22,509
trying to manipulate and massage that
prompt to get something good out of it.

1320
01:04:22,509 --> 01:04:26,329
But to your point, if you took that
output and then put your spin on it and

1321
01:04:26,329 --> 01:04:30,499
did something artistic with it, well,
now it starts to rise above this sort of

1322
01:04:30,509 --> 01:04:35,389
generic floor, this level of noise that
anybody can go to an AI tool and get out.

1323
01:04:35,409 --> 01:04:38,999
I run in circles with some Never AI ers
as well, and there's always interesting

1324
01:04:38,999 --> 01:04:41,659
conversations about where it exists
today and where it's going to be

1325
01:04:41,659 --> 01:04:45,239
tomorrow, but when I show them your art
specifically, there's this moment of like,

1326
01:04:45,249 --> 01:04:47,499
oh, well, uh, there's something there.

1327
01:04:47,809 --> 01:04:50,679
that they can't put their finger
on because you, as an artist, are

1328
01:04:50,709 --> 01:04:52,319
elevating, you're adding something to it.

1329
01:04:52,349 --> 01:04:56,119
And, , I guess this leads to a rather
generic question, but I think it's

1330
01:04:56,119 --> 01:04:58,409
an important one, especially for
those that are seeing your visuals

1331
01:04:58,409 --> 01:04:59,629
for the first time on the YouTube.

1332
01:05:00,059 --> 01:05:03,159
If you're listening to the audio
only of this podcast, please go

1333
01:05:03,159 --> 01:05:04,739
check out this interview on YouTube.

1334
01:05:05,139 --> 01:05:08,079
How do you even describe
what you are doing?

1335
01:05:08,993 --> 01:05:12,713
Everything I make comes from a place
of trying to manufacture nostalgia

1336
01:05:12,713 --> 01:05:17,068
for something that never existed You
So that's sort of the thread that

1337
01:05:17,068 --> 01:05:18,108
runs through everything I'm doing.

1338
01:05:18,108 --> 01:05:20,788
I'm trying to make you pine for
something that maybe you don't

1339
01:05:20,818 --> 01:05:22,308
really understand where it came from.

1340
01:05:22,318 --> 01:05:25,818
It's like a, a memory that's maybe
from a dream or, or somewhere else.

1341
01:05:25,828 --> 01:05:30,098
So everything is, is, it's sort
of realistic, sort of unrealistic.

1342
01:05:30,098 --> 01:05:35,068
There's usually some sort of odd twist
somewhere in the, in the, in the piece.

1343
01:05:35,098 --> 01:05:38,128
And then sometimes like on Twitter,
it's literally just stuff I'm making.

1344
01:05:38,128 --> 01:05:38,898
I'm like, that's cool.

1345
01:05:39,328 --> 01:05:40,348
Everybody should check that out.

1346
01:05:40,398 --> 01:05:45,103
So, and I also love the being like,
this trash I'm putting out for fun?

1347
01:05:45,103 --> 01:05:46,373
Or is this something I thought about?

1348
01:05:46,633 --> 01:05:49,423
And making people sit there
and think about the trash for a

1349
01:05:49,423 --> 01:05:51,333
minute is like, makes me laugh.

1350
01:05:51,333 --> 01:05:55,763
So I don't know, like, yeah, I'm
a bit of a, a bit of a, Joker,

1351
01:05:55,963 --> 01:05:58,383
I like the concept of being an
artist, but having fun with it.

1352
01:05:58,383 --> 01:06:01,923
I'm in the Frank Zappa group of,
yes, humor does belong in music.

1353
01:06:02,073 --> 01:06:02,473
for sure.

1354
01:06:02,633 --> 01:06:04,453
I, I agree with that I think one
thing that would be interesting to

1355
01:06:04,463 --> 01:06:08,043
the listeners here is you obviously
talked about a ton of different tools.

1356
01:06:08,313 --> 01:06:10,663
One of the things we try to give
people a heads up on is like ways

1357
01:06:10,663 --> 01:06:11,933
to kind of try the stuff themselves.

1358
01:06:11,933 --> 01:06:15,363
And obviously there's lots of things with
easy you eyes that you can go and get

1359
01:06:15,363 --> 01:06:19,123
like, whether it's Leonardo or the things
that are like designed for normies, but

1360
01:06:19,123 --> 01:06:20,233
you do stuff that's really interesting.

1361
01:06:20,233 --> 01:06:22,963
And I think comfy UI is something
that's worth talking about.

1362
01:06:22,993 --> 01:06:26,868
And so, um, A comfy UI for anybody
listening is a stable diffusion

1363
01:06:26,888 --> 01:06:30,648
interface and stable diffusion is
ostensibly an open source model.

1364
01:06:30,648 --> 01:06:32,778
And you may correct me on
that, but it's an accessible

1365
01:06:32,788 --> 01:06:34,268
image model for lots of people.

1366
01:06:34,628 --> 01:06:38,738
What are you able to do in comfy UI
that an average person wouldn't be

1367
01:06:38,738 --> 01:06:41,378
able to do in something like a mid
journey or just an off the shelf

1368
01:06:41,378 --> 01:06:42,938
kind of image generation software.

1369
01:06:42,938 --> 01:06:47,538
So, , Comfy UI's main strength is
that it's a visual, node based, , I

1370
01:06:47,538 --> 01:06:48,438
don't want to say programming

1371
01:06:48,773 --> 01:06:49,363
Okay, hold on.

1372
01:06:49,363 --> 01:06:50,243
I'm gonna stop you right there.

1373
01:06:50,243 --> 01:06:52,693
What is visual node based
program language mean?

1374
01:06:53,658 --> 01:06:56,538
So, uh, regular code is
written in text, right?

1375
01:06:56,538 --> 01:06:56,568
Okay.

1376
01:06:56,653 --> 01:06:57,123
Mm hmm.

1377
01:06:57,693 --> 01:07:00,133
You just type lines of text
and then maybe it works.

1378
01:07:00,133 --> 01:07:05,153
Maybe it doesn't, comfy wise, more
like a modular synthesizer where

1379
01:07:05,163 --> 01:07:07,303
you have little components in boxes.

1380
01:07:07,733 --> 01:07:12,433
And then you, you know, in your
mind, what the path of those boxes

1381
01:07:12,443 --> 01:07:15,963
is because of the chains or the
wires that are connecting them.

1382
01:07:16,363 --> 01:07:20,583
And basically you can rewire how
stable diffusion works, , or just

1383
01:07:20,603 --> 01:07:24,199
use different things modularly
in your workflow in places.

1384
01:07:24,199 --> 01:07:28,383
Maybe they shouldn't have been used or as
a new thing that you're just trying out.

1385
01:07:28,383 --> 01:07:32,463
It's like taking all the elements of
stable diffusion and having access

1386
01:07:32,463 --> 01:07:36,273
to them in a very expandable way
so you can build modules that you

1387
01:07:36,273 --> 01:07:37,683
can then expand into other things.

1388
01:07:37,683 --> 01:07:41,323
So you can do one thing, you can
add another thing, you can save

1389
01:07:41,323 --> 01:07:42,803
that second thing as a template.

1390
01:07:43,033 --> 01:07:45,903
Then in your next project you can say, Oh,
I want to do that thing I did last time.

1391
01:07:45,913 --> 01:07:48,763
Just drop it in and then just
plug in the wires and go.

1392
01:07:48,793 --> 01:07:51,103
So it's, , It's scary at first.

1393
01:07:51,143 --> 01:07:54,693
It's, it's, it's very overwhelming,
but it teaches you what

1394
01:07:54,693 --> 01:07:56,193
diffusion is, how it works.

1395
01:07:56,243 --> 01:08:00,653
And then once you understand that
little simple path, it's just literally

1396
01:08:00,653 --> 01:08:05,528
just Plugging stuff in and rewiring
it wrong and laughing about the crazy

1397
01:08:05,528 --> 01:08:09,078
stuff it makes and then sometimes
the crazy stuff it makes is amazing

1398
01:08:09,138 --> 01:08:12,418
Can you walk us through a very simple
version of that node and just say

1399
01:08:12,418 --> 01:08:15,748
like, okay, first node is this, second
node is this, third node is this, and

1400
01:08:15,748 --> 01:08:18,688
they go in this direction, like, just
because I know that like is control

1401
01:08:18,688 --> 01:08:22,068
not a node that you put in there, like,
how do the nodes work particularly,

1402
01:08:22,464 --> 01:08:22,764
Sure.

1403
01:08:22,834 --> 01:08:24,904
There's a bunch of stuff that
comes with comfy, which is

1404
01:08:24,904 --> 01:08:26,584
just basic diffusion stuff.

1405
01:08:26,594 --> 01:08:30,394
You get your loaders, you
basically load up a checkpoint.

1406
01:08:30,404 --> 01:08:33,284
So you load up your model, which is,
you know, stable diffusion model.

1407
01:08:33,644 --> 01:08:39,774
You load up any Loras you want, which
are, are, uh, ways to affect the results.

1408
01:08:39,994 --> 01:08:42,194
You can get them on Civit AI
and a bunch of other places.

1409
01:08:42,564 --> 01:08:45,464
, so checkpoints and Loras,
you load them up and then you

1410
01:08:45,464 --> 01:08:47,684
feed it into a prompt encoder.

1411
01:08:47,694 --> 01:08:50,834
So you, then you tell it, I want
my positive and my negative prompt.

1412
01:08:51,164 --> 01:08:52,264
This is what I want them to be.

1413
01:08:52,634 --> 01:08:57,784
And then you have a, an empty latent
space, which is just the canvas

1414
01:08:57,794 --> 01:08:59,134
in which you're dreaming into.

1415
01:08:59,434 --> 01:09:02,364
So you say I want to dream
into a five 12 by five 12

1416
01:09:02,484 --> 01:09:04,644
canvas , and it's this many pixels.

1417
01:09:04,884 --> 01:09:05,734
Pieces in the batch.

1418
01:09:05,734 --> 01:09:06,894
So I want to make one image.

1419
01:09:07,274 --> 01:09:11,014
So then you plug all that into a
case sampler, which is the main

1420
01:09:11,284 --> 01:09:13,944
heart of a diffusion, uh, situation.

1421
01:09:13,944 --> 01:09:15,324
It like does all the work.

1422
01:09:15,354 --> 01:09:18,044
So you plug everything into it,
once that's all plugged in, then you

1423
01:09:18,044 --> 01:09:21,234
just punch out into a VAE decoder.

1424
01:09:21,234 --> 01:09:25,064
And that's where a variable
auto and variable auto encoder.

1425
01:09:25,414 --> 01:09:26,964
That's the thing that takes it from.

1426
01:09:27,434 --> 01:09:31,584
Latent noise, the machine noise, the noise
a machine understands, turns it into an

1427
01:09:31,594 --> 01:09:33,924
RGB image that we as humans can read.

1428
01:09:33,924 --> 01:09:37,304
So, that's that final step where
you take the, the machine noise

1429
01:09:37,304 --> 01:09:38,874
, and diffuse it into an image.

1430
01:09:39,254 --> 01:09:41,004
And then that image you then just save.

1431
01:09:41,264 --> 01:09:44,804
And then that is all expandable
out to video or whatever else

1432
01:09:44,804 --> 01:09:46,334
by just batching the images.

1433
01:09:46,364 --> 01:09:49,604
and for people at home listening or
watching, it may sound confusing,

1434
01:09:49,604 --> 01:09:53,004
but what's really cool about comfy
UI is it is a visual medium that you

1435
01:09:53,004 --> 01:09:56,274
can see it's almost like I love this
old video game called the impossible

1436
01:09:56,274 --> 01:09:58,854
machine, which was always about
putting things in different orders.

1437
01:09:58,854 --> 01:10:01,724
And like, as it would go through here,
it's a little bit like that, right?

1438
01:10:01,724 --> 01:10:02,824
It's like, okay, you've got all these

1439
01:10:03,144 --> 01:10:04,744
the bowling ball along the shelf?

1440
01:10:04,744 --> 01:10:05,494
Is that what this is?

1441
01:10:05,494 --> 01:10:06,304
Into a basket?

1442
01:10:06,334 --> 01:10:06,984
Yeah, I get it.

1443
01:10:07,264 --> 01:10:08,024
Kinda, yeah.

1444
01:10:08,094 --> 01:10:08,754
No, totally.

1445
01:10:09,394 --> 01:10:12,754
,
That was basic by design of here's how
we're just going to generate a 2D image.

1446
01:10:12,754 --> 01:10:16,774
It's how Stable Diffusion is
working, , even on automatic 11.

1447
01:10:16,774 --> 01:10:17,554
11 behind the scenes.

1448
01:10:17,564 --> 01:10:19,464
You're just getting access
to those granular things.

1449
01:10:19,464 --> 01:10:20,784
So I love that explainer.

1450
01:10:21,214 --> 01:10:25,104
You are then bending and breaking
this thing in ways that I don't

1451
01:10:25,104 --> 01:10:27,834
know if you even imagine when you
first started diving into this.

1452
01:10:27,834 --> 01:10:29,744
You're taking custom.

1453
01:10:30,149 --> 01:10:34,359
RGB animations, red, green, blue
animations, and using the way the

1454
01:10:34,359 --> 01:10:39,899
geometry of that solid color moves
to tell a portion of comfy UI.

1455
01:10:39,919 --> 01:10:41,319
Hey, this is actually.

1456
01:10:41,774 --> 01:10:45,674
sky in a background and this green
blob is actually a person's face

1457
01:10:45,674 --> 01:10:47,014
as it moved towards the camera.

1458
01:10:47,094 --> 01:10:50,174
When you set out on this journey,
was, was there a happy accident that

1459
01:10:50,174 --> 01:10:51,614
led you into doing these things?

1460
01:10:51,944 --> 01:10:54,934
Did you find somebody else's
workflow and make it your own?

1461
01:10:54,944 --> 01:10:58,604
Like, when did you start heading in
this very, specific stylized path?

1462
01:11:00,009 --> 01:11:04,999
What happens there is, Some nerd
makes some really cool feature , for

1463
01:11:04,999 --> 01:11:07,009
the forum, let's say version four, 0.

1464
01:11:07,009 --> 01:11:09,349
4, they added depth maps to the forum.

1465
01:11:09,789 --> 01:11:14,689
So suddenly every time you're making
a, an animation, you can tell it to

1466
01:11:14,699 --> 01:11:18,919
look at the image and create a depth
map and then pull the stuff that

1467
01:11:18,949 --> 01:11:21,909
close to the camera, closer to the
camera as the animation goes through.

1468
01:11:22,269 --> 01:11:26,579
So already you've just, that unlocks
a door to like, Oh, well maybe.

1469
01:11:27,099 --> 01:11:31,729
When, , they add control net to Deforum,
we'll be able to make our own masks.

1470
01:11:31,979 --> 01:11:33,199
Then, bam, that happens.

1471
01:11:33,489 --> 01:11:36,119
And it's great, and we can add
our own masks to control net.

1472
01:11:36,139 --> 01:11:37,549
We start playing with that with Deforum.

1473
01:11:37,899 --> 01:11:40,509
And then someone thinks, oh, well,
wouldn't it be cool if we could make a

1474
01:11:40,509 --> 01:11:42,429
mask that tells the pixels how to move?

1475
01:11:42,634 --> 01:11:43,804
Which is hybrid video.

1476
01:11:44,134 --> 01:11:45,934
And then they add hybrid video to deform.

1477
01:11:45,934 --> 01:11:48,664
So all these things just iterate,
the community iterates these things

1478
01:11:48,934 --> 01:11:51,504
and you just learn how to use them
and integrate them in your workflow.

1479
01:11:51,784 --> 01:11:53,124
You keep the stuff that's awesome.

1480
01:11:53,124 --> 01:11:56,284
You drop the stuff that's worthless
or takes too long or is completely

1481
01:11:56,284 --> 01:11:58,304
outdated in a week, and you move on.

1482
01:11:58,334 --> 01:12:01,974
A lot of this stuff is just a culmination
of testing all kinds of different features

1483
01:12:01,974 --> 01:12:06,554
and, different ways of interacting
with these animations over the years.

1484
01:12:06,574 --> 01:12:08,104
But, um, Yeah.

1485
01:12:08,104 --> 01:12:11,364
I mean, the cool thing is
the community is like on it.

1486
01:12:11,374 --> 01:12:15,564
If there's a discord called Banadoko,
if you go there, , everybody just posts

1487
01:12:15,564 --> 01:12:18,554
their workflows there and you just go,
you go down a little workflow, install

1488
01:12:18,554 --> 01:12:20,474
the plugins and, and get to work.

1489
01:12:20,484 --> 01:12:23,154
And honestly, most of my streams
are me just grabbing one of those

1490
01:12:23,164 --> 01:12:27,474
workflows and we just install it
and try it out and, , squash all the

1491
01:12:27,474 --> 01:12:30,754
bugs and talk to the developer and do
what we got to do to get it to work.

1492
01:12:31,124 --> 01:12:34,644
I didn't think we'd be sitting here
with, you know, real time painting tools

1493
01:12:34,644 --> 01:12:38,504
that can , in a matter of milliseconds,
render something with beautiful lighting

1494
01:12:38,504 --> 01:12:41,354
and then incorporate a lower or whatever
else, like we're, we're here already.

1495
01:12:41,704 --> 01:12:44,314
It's still relatively early in 2024.

1496
01:12:44,334 --> 01:12:45,444
That is mind blowing.

1497
01:12:45,444 --> 01:12:46,254
it's super cool.

1498
01:12:46,334 --> 01:12:48,224
I like stream diffusion is wild.

1499
01:12:48,554 --> 01:12:51,624
I, I don't know if you guys have
ever seen dot simulate Lyle.

1500
01:12:51,694 --> 01:12:54,734
, he has a touch designer
plugin for stream diffusion.

1501
01:12:54,821 --> 01:12:57,731
, so you can do stuff in touch
designer and immediately diffuse

1502
01:12:57,731 --> 01:12:59,761
over top of it And then bring that

1503
01:12:59,971 --> 01:13:01,251
that is so cool.

1504
01:13:01,251 --> 01:13:04,231
For those who don't know, a lot
of , musicians will integrate

1505
01:13:04,231 --> 01:13:07,881
with TouchDesigner is a, you
know, For real time visuals.

1506
01:13:07,881 --> 01:13:08,131
Yeah.

1507
01:13:08,131 --> 01:13:12,801
So the idea that like your drum kit is pre
creating primitive geometry on a screen,

1508
01:13:12,801 --> 01:13:16,591
but then say, okay, that square for my
kick drum is actually a city building.

1509
01:13:16,881 --> 01:13:21,291
And the hi hat noise needs to be the
color of the sky and let it in real time.

1510
01:13:21,291 --> 01:13:21,561
Do that.

1511
01:13:21,571 --> 01:13:22,631
I've got to check that out.

1512
01:13:23,111 --> 01:13:24,441
Oh, that's going to be dangerous.

1513
01:13:24,451 --> 01:13:27,321
So we know that the tech's
going to get better.

1514
01:13:27,321 --> 01:13:30,761
Where do you see this driving
in, , a year's time, , in terms

1515
01:13:30,761 --> 01:13:34,281
of, let's say, performance,
in terms of, uh, capabilities?

1516
01:13:34,441 --> 01:13:37,721
What do you think is gonna be unlocked,
and where do you want it to go for

1517
01:13:37,721 --> 01:13:40,471
you, personally, professionally?

1518
01:13:40,521 --> 01:13:44,341
,
I just want to get more tools that are
integrable into tools you already have.

1519
01:13:44,641 --> 01:13:47,921
One of my main things is I really want
to get into, uh, audio AI, music AI.

1520
01:13:48,596 --> 01:13:51,196
But all the solutions right
now just generate songs for me.

1521
01:13:51,226 --> 01:13:56,006
I don't need that I need uh any tools I
can just drop into ableton or logic or

1522
01:13:56,006 --> 01:14:01,476
whatever i'm already making music in um
So that I can use these tools effectively

1523
01:14:01,476 --> 01:14:05,806
like that's why I like comfy It's you're
just dropping it in when you need it with

1524
01:14:05,826 --> 01:14:10,326
other workflows blender after effects
photoshop, whatever you're doing Comfy

1525
01:14:10,326 --> 01:14:14,796
is just another component of the workflow
that I can plop in like a block, but you

1526
01:14:14,796 --> 01:14:18,006
know, for audio right now, it's like,
it just generate music, which is, it's

1527
01:14:18,006 --> 01:14:21,096
cool and exciting, but , not useful
for me because I already make music.

1528
01:14:21,096 --> 01:14:23,046
I need the tools to make music better.

1529
01:14:23,406 --> 01:14:27,246
There are some AI music tools, but I
want some stuff where I just throw it

1530
01:14:27,246 --> 01:14:29,376
on the channel and it does cool stuff.

1531
01:14:29,416 --> 01:14:31,706
Maybe it talks to a server,
maybe I pay for it, whatever.

1532
01:14:32,131 --> 01:14:35,751
Uh, if it's got to be off off on
the cloud or whatever it was just

1533
01:14:35,751 --> 01:14:39,261
generating samples for me I bring
them back in and try them all out.

1534
01:14:39,419 --> 01:14:42,629
So more control over the stems
and the creation of the individual

1535
01:14:42,804 --> 01:14:43,294
granular

1536
01:14:43,699 --> 01:14:45,249
Don't bake me the entire cake.

1537
01:14:45,359 --> 01:14:46,669
Just give me some ingredients.

1538
01:14:47,414 --> 01:14:47,994
Exactly.

1539
01:14:48,024 --> 01:14:48,374
Yeah

1540
01:14:48,629 --> 01:14:52,459
I'd love to talk about your community
and the live streams when you started,

1541
01:14:52,699 --> 01:14:56,249
taking these comfy tutorials and
these journeys with a community.

1542
01:14:56,249 --> 01:14:57,529
How has your community grown?

1543
01:14:57,679 --> 01:14:59,229
What are they reacting to?

1544
01:14:59,409 --> 01:15:02,979
Yeah, it's been great, , I had a
lot of trouble getting traction on

1545
01:15:03,199 --> 01:15:06,799
twitch , I was doing blender stuff on
and a little bit AI stuff on twitch

1546
01:15:06,809 --> 01:15:10,649
for about a year and a year and a half
just getting no viewers at all and then

1547
01:15:11,024 --> 01:15:13,644
Did you have a big wheel that
you would spin every five subs

1548
01:15:13,644 --> 01:15:14,594
or did you cover yourself in

1549
01:15:14,744 --> 01:15:18,764
well that's kind of I think that's kind
of it is is nobody wants to sit and watch

1550
01:15:18,764 --> 01:15:22,904
somebody , just click click stuff and
and occasionally talk on twitch, , so

1551
01:15:22,904 --> 01:15:25,764
what happened was I watched a couple
of my blender friends just killing it,

1552
01:15:25,814 --> 01:15:29,654
uh doing youtube streams and I thought
well youtube's a good choice because

1553
01:15:29,974 --> 01:15:33,334
Whenever I do these live streams,
it's just immediately saved forever.

1554
01:15:33,334 --> 01:15:36,324
So if somebody needs to go back and
see what I did, they can literally just

1555
01:15:36,324 --> 01:15:39,724
scroll back, which is not something that
could get going really well with Twitch.

1556
01:15:40,084 --> 01:15:41,254
Everyone's been really cool.

1557
01:15:41,274 --> 01:15:45,424
I've just been slowly gaining more and
more followers and, , we're, , Building

1558
01:15:45,424 --> 01:15:49,224
a community on Discord as well, , where,
you can come and, , draw up your workflows

1559
01:15:49,274 --> 01:15:52,074
and then, people come and show that
we're out there and we all, you know,

1560
01:15:52,074 --> 01:15:55,384
follow each other and, and, you know,
get on Instagram and all that stuff.

1561
01:15:55,384 --> 01:15:57,484
And, yeah, it's been really great.

1562
01:15:57,524 --> 01:15:58,194
The,

1563
01:15:58,309 --> 01:16:01,529
you been approached by a shark
to productize everything yet?

1564
01:16:01,539 --> 01:16:05,629
Because there's definitely companies
that are out there wrapping up comfy

1565
01:16:05,629 --> 01:16:10,559
UI workflows and trying to sell them as
magical tools and I got to imagine there's

1566
01:16:10,719 --> 01:16:14,269
maybe an ounce of interest, but maybe
also an ounce of repulsion there for you.

1567
01:16:14,269 --> 01:16:15,329
I do get offers.

1568
01:16:15,409 --> 01:16:18,689
, so the biggest problem for me is
that a lot of these things that

1569
01:16:18,689 --> 01:16:20,749
we're doing are very one off.

1570
01:16:20,759 --> 01:16:22,439
They require a lot of tinkering.

1571
01:16:22,539 --> 01:16:26,929
, it's really hard for me to build
a one size fits all solution for

1572
01:16:26,939 --> 01:16:29,489
like somebody wants something
that'll just forever always make

1573
01:16:29,489 --> 01:16:31,049
yearbook photos of people like.

1574
01:16:31,444 --> 01:16:32,484
Yeah, that's possible.

1575
01:16:32,484 --> 01:16:36,394
But so a lot of the time it's just gonna
make junk and The end user is gonna

1576
01:16:36,394 --> 01:16:37,714
end up paying credits for that junk.

1577
01:16:37,714 --> 01:16:43,214
So I just as a Just as the type of
person I am I would prefer to just

1578
01:16:43,214 --> 01:16:47,384
empower people to make this stuff at
home Learn how to plug a laura in and

1579
01:16:47,384 --> 01:16:50,514
make your own yearbook generator because
then your yearbook generator becomes

1580
01:16:50,514 --> 01:16:54,474
an anything you want in The world laura
generator right selfie generator friend.

1581
01:16:54,474 --> 01:16:57,324
It's like that's the thing these
tools empower people So that's

1582
01:16:57,354 --> 01:17:00,359
i'm just mostly Interested in
empowering people to use them.

1583
01:17:00,359 --> 01:17:05,189
So I think if if there was something
that would Make me excited would

1584
01:17:05,199 --> 01:17:10,024
be something where I can offload
usage to the cloud in an instance

1585
01:17:10,024 --> 01:17:11,404
of comfy that I'm currently running.

1586
01:17:11,604 --> 01:17:14,464
So say you're running comfy on
your notebook it's set up so that

1587
01:17:14,464 --> 01:17:16,964
everything it does on the GPU
it just sends off to the cloud.

1588
01:17:17,234 --> 01:17:19,684
So you're still running comfy locally,
you're still doing all this stuff.

1589
01:17:19,694 --> 01:17:22,594
You can still follow along with my
tutorials, but it's just ripping frames

1590
01:17:22,664 --> 01:17:23,064
that not

1591
01:17:23,154 --> 01:17:23,804
a computer and a

1592
01:17:24,144 --> 01:17:24,334
I'm

1593
01:17:24,604 --> 01:17:30,524
It sort of does, but it's not, uh,
because, uh, the, TLDR is you have

1594
01:17:30,524 --> 01:17:34,894
to have the exact same instance
of comfy running on that computer.

1595
01:17:35,054 --> 01:17:36,964
So you still have to spin up another copy

1596
01:17:37,064 --> 01:17:38,544
of every extension or plug in or

1597
01:17:38,864 --> 01:17:41,244
So you still have to
spin up a second version.

1598
01:17:41,244 --> 01:17:43,044
It's just a different
way of interfacing with

1599
01:17:43,094 --> 01:17:43,794
Because that's what I had when I

1600
01:17:43,804 --> 01:17:45,054
think let's say solve that.

1601
01:17:45,134 --> 01:17:45,644
your workflows.

1602
01:17:45,674 --> 01:17:48,404
We were talking before we hit
record was that, , I'm on a Mac.

1603
01:17:48,414 --> 01:17:52,324
It's, for reasons, I really
want to play with this stuff.

1604
01:17:52,324 --> 01:17:53,354
A lot of it's NVIDIA only.

1605
01:17:53,354 --> 01:17:55,754
So then I went, okay, I'm going to go
and I'm going to spin up a run pod.

1606
01:17:55,964 --> 01:17:56,544
And I'm going to install.

1607
01:17:56,544 --> 01:17:59,084
I was like, well, this version
doesn't exactly match that version.

1608
01:17:59,274 --> 01:18:01,914
This checkpoint, I got to ingest
through here and blah, blah, blah.

1609
01:18:02,114 --> 01:18:03,174
Oh, I clicked the wrong box.

1610
01:18:03,174 --> 01:18:06,144
So if I pause the run pod, it's
all going to go away anyway.

1611
01:18:06,144 --> 01:18:07,304
So now I'm just going
to be paying per minute.

1612
01:18:07,324 --> 01:18:10,404
And I know that there are, solutions
and templates and all that stuff.

1613
01:18:10,404 --> 01:18:14,974
But even for someone who is in the scene
and has a modicum of understanding about

1614
01:18:14,974 --> 01:18:18,674
all this stuff, it still made , my head
spin, which I'd love to drive towards

1615
01:18:18,674 --> 01:18:22,944
a final question for what is likely a
broader audience that we have out there.

1616
01:18:23,244 --> 01:18:25,794
And it is, where do I start?

1617
01:18:25,824 --> 01:18:26,934
How do I begin?

1618
01:18:26,944 --> 01:18:30,824
Is there a, baby's first steps
guide, or is there a, a template

1619
01:18:30,824 --> 01:18:33,284
that you have that you recommend
for someone to get this all going?

1620
01:18:34,269 --> 01:18:37,529
, I would say you got to decide what
you want to do with comfy before

1621
01:18:37,529 --> 01:18:41,189
you start with comfy because it's
too big to, uh, just jump into.

1622
01:18:41,189 --> 01:18:44,689
So, uh, if your goal is to just make
images, like just start with just

1623
01:18:44,689 --> 01:18:49,694
making images, which is a fantastic
first goal, um, You literally install

1624
01:18:49,694 --> 01:18:54,824
comfy and you hit default at the thing
and it'll load up a default workflow

1625
01:18:55,204 --> 01:18:58,654
and then all the nodes are already
there You So you can literally

1626
01:18:58,654 --> 01:19:01,574
just start dragging noodles out
of stuff and letting go and seeing

1627
01:19:01,574 --> 01:19:03,254
what it recommends you can plug in.

1628
01:19:03,674 --> 01:19:06,744
And that'll, that'll start your brain
going, Oh, okay, well I can plug these

1629
01:19:06,744 --> 01:19:08,134
into this, I can plug that into this.

1630
01:19:08,484 --> 01:19:10,774
it's Scary, but you're not going
to break everything all the time.

1631
01:19:10,774 --> 01:19:13,154
You're just going to go,
okay, my negative prompt

1632
01:19:13,279 --> 01:19:14,859
something under the hood of your car.

1633
01:19:14,879 --> 01:19:15,729
It's okay.

1634
01:19:15,759 --> 01:19:17,139
Cause it can be undone.

1635
01:19:17,149 --> 01:19:19,789
So go ahead and make the mistakes and
maybe you'll get a happy accident.

1636
01:19:19,789 --> 01:19:22,329
So just start out small, make an image.

1637
01:19:22,679 --> 01:19:25,349
Uh, now I want to turn this image
into a batch of four images.

1638
01:19:25,359 --> 01:19:26,039
How do I do that?

1639
01:19:26,389 --> 01:19:27,079
Figure that out.

1640
01:19:27,119 --> 01:19:30,219
, I want to use an image as , the
beginning of the image to image.

1641
01:19:30,219 --> 01:19:30,959
How do I do that?

1642
01:19:31,279 --> 01:19:33,459
, just jump on my discord, ask
somebody how to do it.

1643
01:19:33,839 --> 01:19:37,049
, there's a bunch of beginner
YouTube stuff, but it is all very

1644
01:19:37,069 --> 01:19:38,789
pointed for very specific tasks.

1645
01:19:38,799 --> 01:19:43,399
So pick a task, watch YouTube if you want,
but it's way more fun just to break stuff

1646
01:19:43,429 --> 01:19:45,939
and, uh, install comfy and, break stuff.

1647
01:19:46,252 --> 01:19:46,822
that's awesome.

1648
01:19:46,832 --> 01:19:47,652
Purrs, Where, can people

1649
01:19:47,662 --> 01:19:47,972
find

1650
01:19:47,972 --> 01:19:48,222
you?

1651
01:19:48,222 --> 01:19:49,746
Where, what is your discord?

1652
01:19:49,746 --> 01:19:51,556
, where is your Twitter X handle?

1653
01:19:51,556 --> 01:19:52,426
What is all that stuff.

1654
01:19:53,708 --> 01:19:55,068
So all my links are on purrs.

1655
01:19:55,078 --> 01:19:55,868
xyz.

1656
01:19:55,898 --> 01:19:59,288
, and then, uh, , I'm at purrs
beats pretty much everywhere.

1657
01:19:59,288 --> 01:20:01,188
So Twitter, YouTube, , all that stuff.

1658
01:20:01,218 --> 01:20:03,178
, but yeah, all of those links
are at the top of purrs.

1659
01:20:03,188 --> 01:20:06,358
xyz as long as, as well as
the link to the discord.

1660
01:20:06,358 --> 01:20:09,608
So if you want to pop in there and if
you have questions and stuff, if I'm

1661
01:20:09,618 --> 01:20:12,198
not there, there's a bunch of people who
are, and they've all been through it.

1662
01:20:12,208 --> 01:20:13,508
So, , ask your stupid

1663
01:20:13,508 --> 01:20:13,928
questions.

1664
01:20:13,928 --> 01:20:14,558
Nobody cares.

1665
01:20:14,608 --> 01:20:15,028
,
it's fine.

1666
01:20:15,266 --> 01:20:16,326
You'll be seeing me show up.

1667
01:20:16,376 --> 01:20:18,386
You'll be seeing me show
up later today, Purrs.

1668
01:20:18,386 --> 01:20:19,206
I'll be jumping in

1669
01:20:19,206 --> 01:20:19,346
there.

1670
01:20:19,346 --> 01:20:19,906
I got, I

1671
01:20:20,023 --> 01:20:21,503
You're just, you just want to test that.

1672
01:20:21,573 --> 01:20:23,333
You want to just ask the
dumbest questions ever.

1673
01:20:23,333 --> 01:20:24,523
They have nothing to do with stable

1674
01:20:24,876 --> 01:20:27,436
How do I make a song
about hot dog casserole?

1675
01:20:27,436 --> 01:20:28,356
Oh, I did that already?

1676
01:20:28,356 --> 01:20:29,126
Let me share it.

1677
01:20:29,126 --> 01:20:31,956
Yeah, All right, thanks Purrs.

1678
01:20:31,966 --> 01:20:32,776
We'll talk to you, soon.

1679
01:20:35,676 --> 01:20:37,146
Thank you, , Perzbeats for being here.

1680
01:20:37,146 --> 01:20:40,516
Please go check out his work and really
dig in on comfy UI and some of the cool

1681
01:20:40,516 --> 01:20:41,896
things you can do with stable diffusion.

1682
01:20:42,206 --> 01:20:43,526
That is it for today's show.

1683
01:20:43,546 --> 01:20:46,106
But you know, there's a couple
things you got to do before you go.

1684
01:20:46,116 --> 01:20:50,606
If you listen to this show, please
go like subscribe, leave us reviews.

1685
01:20:50,656 --> 01:20:53,446
We're about ready to read some five
star reviews from Apple podcasts.

1686
01:20:53,446 --> 01:20:54,666
There were three new ones this week.

1687
01:20:54,896 --> 01:20:59,536
So Kevin, I am going to jump out
and say, uh, From Valley Villager.

1688
01:21:00,076 --> 01:21:01,096
This is the subject.

1689
01:21:01,106 --> 01:21:06,966
My only capital A absolute each and every
week, which is a very nice thing to say.

1690
01:21:07,256 --> 01:21:11,126
The guys will keep you 102 percent
up to date with everything you

1691
01:21:11,126 --> 01:21:12,556
need to know about the new world.

1692
01:21:12,826 --> 01:21:13,646
Great guests.

1693
01:21:13,646 --> 01:21:15,016
They always make me laugh.

1694
01:21:15,026 --> 01:21:15,666
Thank you so much.

1695
01:21:15,696 --> 01:21:16,986
Looking forward to it all week.

1696
01:21:16,986 --> 01:21:19,826
So that is a very nice
kickoff for our five star

1697
01:21:20,216 --> 01:21:22,516
And again, I hate to belabor it.

1698
01:21:22,536 --> 01:21:24,076
I can't, we can't stress it enough.

1699
01:21:24,076 --> 01:21:27,106
We're coming up on a year, which
believe it or not, it's still young

1700
01:21:27,226 --> 01:21:31,126
for a podcast these days, especially
with zero marketing dollars.

1701
01:21:31,356 --> 01:21:33,336
And it's a spare time hustle for us both.

1702
01:21:33,336 --> 01:21:34,136
It's a labor of love.

1703
01:21:34,136 --> 01:21:38,096
So please, if you have a second to
engage, it really is the only way we

1704
01:21:38,096 --> 01:21:41,146
grow this and these five star reviews
help out massively, but leave them on

1705
01:21:41,146 --> 01:21:43,276
Spotify, leave us comments on YouTube.

1706
01:21:43,276 --> 01:21:44,096
Make sure you subscribe.

1707
01:21:44,096 --> 01:21:45,276
It doesn't cost a dollar.

1708
01:21:45,276 --> 01:21:45,806
Our next.

1709
01:21:46,121 --> 01:21:50,901
Five star review, Gavin,
comes from Funhog43.

1710
01:21:50,921 --> 01:21:51,961
Subject is, thank you.

1711
01:21:52,126 --> 01:21:52,706
Love it.

1712
01:21:53,151 --> 01:21:57,511
\ , I'm an educator and have recently been
in servicing teachers on implementing AI

1713
01:21:57,511 --> 01:21:59,551
into their day to day school activities.

1714
01:21:59,731 --> 01:22:02,431
Your show has been influential
in me pushing forward with AI.

1715
01:22:02,631 --> 01:22:05,931
I think it can be a great tool for
educators and students alike, as long

1716
01:22:05,931 --> 01:22:07,331
as it is used in the right manner.

1717
01:22:07,616 --> 01:22:08,116
We agree.

1718
01:22:08,446 --> 01:22:10,056
Actually, I used py.

1719
01:22:10,106 --> 01:22:11,606
ai after listening to an episode.

1720
01:22:11,606 --> 01:22:15,226
I was able to create a story for students
in an ESL class about them becoming

1721
01:22:15,226 --> 01:22:17,186
leprechauns and pranking their teachers.

1722
01:22:17,546 --> 01:22:20,246
I included follow up questions
and was able to have it read

1723
01:22:20,246 --> 01:22:21,826
aloud in multiple languages.

1724
01:22:22,056 --> 01:22:24,646
Seems to make students more
engaged in their learning.

1725
01:22:24,646 --> 01:22:26,645
THX.

1726
01:22:26,646 --> 01:22:26,886
That's a

1727
01:22:27,106 --> 01:22:27,696
Funhawk.

1728
01:22:27,706 --> 01:22:28,146
Thank you.

1729
01:22:28,156 --> 01:22:29,246
Funhawk43.

1730
01:22:29,286 --> 01:22:29,966
We love that.

1731
01:22:29,976 --> 01:22:30,426
We love that.

1732
01:22:30,426 --> 01:22:30,636
All right.

1733
01:22:30,636 --> 01:22:34,216
And finally from Doc Anderson, who I
think is somebody that, , is engaged

1734
01:22:34,216 --> 01:22:35,396
with us quite a bit on the YouTube.

1735
01:22:35,406 --> 01:22:36,146
, shout out to Doc.

1736
01:22:36,586 --> 01:22:38,746
The subject is Kevin and AI co host.

1737
01:22:38,746 --> 01:22:40,376
This is a question I've often wondered.

1738
01:22:40,656 --> 01:22:44,086
He'll says, well, I'll start my,
I'll start my review this podcast

1739
01:22:44,106 --> 01:22:45,996
by simply saying I am embarrassed.

1740
01:22:46,026 --> 01:22:49,246
Oh, I actually posted a review
to the previous podcast about

1741
01:22:49,246 --> 01:22:50,476
trying to borrow your names.

1742
01:22:50,881 --> 01:22:52,701
I'm embarrassed by my error.

1743
01:22:52,751 --> 01:22:53,791
Oh, thank you, doc.

1744
01:22:54,101 --> 01:22:57,521
I want to start my new reviews and share
them with proper podcasts, even though

1745
01:22:57,521 --> 01:22:59,911
this podcast does not deserve five stars.

1746
01:23:00,161 --> 01:23:01,371
I give out five stars.

1747
01:23:01,371 --> 01:23:02,081
Yeah, wait, hold on.

1748
01:23:02,091 --> 01:23:02,821
Give him a second.

1749
01:23:03,001 --> 01:23:05,881
I give out five stars to
podcasts that are good on Apple.

1750
01:23:06,061 --> 01:23:09,701
A podcast like AI for humans
is phenomenal and deserves a

1751
01:23:09,721 --> 01:23:12,861
special category, perhaps 6.

1752
01:23:13,131 --> 01:23:15,211
I enjoy the layout of the show.

1753
01:23:15,421 --> 01:23:16,611
The AI cohost every

1754
01:23:16,856 --> 01:23:17,346
The layout

1755
01:23:17,381 --> 01:23:17,831
me laugh.

1756
01:23:17,896 --> 01:23:18,106
of the show.

1757
01:23:18,901 --> 01:23:22,231
I also enjoy the banter, the conversations
about the weekly news articles.

1758
01:23:22,471 --> 01:23:27,011
In many cases, I find myself replicating
some of the things the host did with AI.

1759
01:23:27,231 --> 01:23:30,321
I find it incredibly fun to
recreate some of what they did.

1760
01:23:30,531 --> 01:23:32,791
Finally, the interview section
is a great ending to the show.

1761
01:23:32,791 --> 01:23:35,491
The show has so many interesting
segments beyond those in newer,

1762
01:23:35,521 --> 01:23:37,080
in the newer editions of AI.

1763
01:23:37,081 --> 01:23:37,951
See what you did there.

1764
01:23:38,161 --> 01:23:39,001
Even shouting out.

1765
01:23:39,001 --> 01:23:39,211
ai.

1766
01:23:39,211 --> 01:23:39,901
See what you did there.

1767
01:23:40,051 --> 01:23:43,111
In conclusion, I want to reiterate
that I can only give you five stars,

1768
01:23:43,111 --> 01:23:44,701
but you truly deserve many more.

1769
01:23:44,851 --> 01:23:47,911
I wanna take, I wanna take this
opportunity to express my deep

1770
01:23:47,911 --> 01:23:51,361
respect and admiration for the
show's host Kevin and Kevin.

1771
01:23:51,481 --> 01:23:52,111
Oh my God.

1772
01:23:52,291 --> 01:23:55,951
Gavin and Kevin, their unique
perspectives on ai, especially

1773
01:23:56,041 --> 01:23:58,771
Gavin's a lot of value to the show.

1774
01:23:58,831 --> 01:24:02,311
I eagerly anticipate hearing
their insights on the fascinating

1775
01:24:02,311 --> 01:24:03,271
news articles they share.

1776
01:24:03,821 --> 01:24:07,841
Here's to Gavin, the president of
the fan club I'm forming in my heart.

1777
01:24:08,056 --> 01:24:08,476
that out.

1778
01:24:08,496 --> 01:24:09,486
I should've sniffed that out.

1779
01:24:09,486 --> 01:24:12,166
Gavin never wants to read the
longer reviews, but he was

1780
01:24:12,216 --> 01:24:13,596
adamant that he'd take this one.

1781
01:24:13,596 --> 01:24:14,006
I get it.

1782
01:24:14,036 --> 01:24:14,436
Okay.

1783
01:24:14,626 --> 01:24:16,306
Hey, thank you Doc Anderson.

1784
01:24:16,306 --> 01:24:19,536
I'm not AI, and Gavin
is occasionally useful.

1785
01:24:19,536 --> 01:24:20,056
That's fair.

1786
01:24:20,066 --> 01:24:21,426
Alright, enjoy your victory dance.

1787
01:24:21,426 --> 01:24:22,736
Thank you to everybody.

1788
01:24:23,026 --> 01:24:24,676
Who took a second to engage.

1789
01:24:24,806 --> 01:24:26,896
Whether you left us a review or
whether you thought about it.

1790
01:24:26,906 --> 01:24:28,936
Maybe you got that itchy scrolling finger.

1791
01:24:28,936 --> 01:24:29,546
Just tap.

1792
01:24:29,576 --> 01:24:30,046
Do it.

1793
01:24:30,076 --> 01:24:30,406
Please.

1794
01:24:30,416 --> 01:24:30,976
Subscribe.

1795
01:24:30,986 --> 01:24:31,456
Follow.

1796
01:24:31,496 --> 01:24:31,836
Like.

1797
01:24:31,866 --> 01:24:32,356
Engage.

1798
01:24:32,386 --> 01:24:33,056
Leave a comment.

1799
01:24:33,076 --> 01:24:34,786
It's the only way we survive.

1800
01:24:35,971 --> 01:24:37,191
Go play with Suno, everybody.

1801
01:24:37,191 --> 01:24:39,661
Go have some fun this week , and
try some different stuff out.

1802
01:24:39,711 --> 01:24:42,371
, we have a great time doing this show
and we will see you all next week.

1803
01:24:42,411 --> 01:24:45,891
Another show, Kevin, in
person coming next week.

1804
01:24:46,146 --> 01:24:47,226
I've been practicing.

1805
01:24:47,836 --> 01:24:50,046
I mean, I've been going to the
Dave and Buster's and punching that

1806
01:24:50,046 --> 01:24:51,976
speed bag arcade as hard as I can.

1807
01:24:51,976 --> 01:24:52,636
I'm coming for you.

1808
01:24:52,636 --> 01:24:55,406
I'm knocking that mustard cap
right off your noggin, buddy.

1809
01:24:55,911 --> 01:24:56,591
I can't wait.

1810
01:24:56,591 --> 01:24:57,211
All right, everybody.

1811
01:24:57,211 --> 01:24:57,511
Thanks.

1812
01:24:57,511 --> 01:24:58,321
We'll see you next week.

1813
01:24:58,361 --> 01:24:58,791
Bye bye