12/22/2025 - Abracadabra: Using AI to Speak Your Creative Projects Directly Into Existence

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Transcript

0:03 [clears throat]
0:07 [music]
0:13 [music]
0:28 [music]
0:39 [music]
0:52 [music]
0:57 [music]
1:02 [music]
1:14 [music]
1:23 Who is the bloody [music]
1:26 Christmas
1:32 sweet
1:38 this place where the feelings don't
1:43 [music]
1:44 over
1:48 this place I [singing and music] get no
1:51 face the only one I truly can
1:54 >> [music]
1:56 >> These are tears from a long time ago.
2:04 I need to cry 30 years or so.
2:08 These are tears from a long time.
2:12 [music]
2:20 Oh darling, darling, you say unto me,
2:27 where have you been all my life?
2:33 [music]
2:34 I have been swimming
2:36 sad seas
2:39 [music]
2:42 mel [singing]
2:45 [music]
2:52 [singing and music]
3:02 so these These are tears for a long
3:05 time.
3:08 Go. [music]
3:20 [music]
3:23 >> Um, that is a beautiful song. One of the
3:26 things I was thinking as I was playing
3:28 that was, uh, couldn't you have learned
3:31 some Christmas songs? [laughter]
3:34 Something a little something a little
3:35 cheery, a little winter wonderland, a
3:38 little something not depressing. I
3:40 played that one song once at an open mic
3:42 night that was a combo. It was a combo
3:44 singer songwriter comedian night
3:48 [laughter] and I played that and I got
3:50 off stage and the host was like, "Yeah,
3:52 who's going to do comedy after that?"
3:54 [laughter]
3:57 I find that song inspiring and and
3:59 uplifting, but apparently 30 years of
4:02 tears is not everyone's cup of tea.
4:05 [laughter]
4:07 Ah, what are y'all going to do? What are
4:10 you going to do? What are you going to
4:12 do? I could do my black bar. That I
4:13 could do. That I could do. I could I
4:16 could preempt the uh the nasty gram
4:18 coming from producer Brandon. That's
4:21 that's something I could do.
4:24 >> [music]
4:29 [music]
4:34 [music]
4:41 [music]
4:46 [music]
4:50 >> Yeah.
4:55 >> [music]
5:03 [music]
5:14 [music]
5:24 [music]
5:31 >> in a westerly
5:34 direction.
5:38 This car is my train.
5:41 [music]
5:43 I've been driving. I've been wondering
5:47 what it is I'm running from again. Feel
5:51 [music]
5:53 [singing] like an 80y old man
5:57 holding on to 29.
6:02 And up on that horizon
6:08 line.
6:15 [music]
6:19 [singing]
6:21 Brea good.
6:26 Cute little front door and two windows.
6:28 My lord
6:30 ain't sure whether to cry or should
6:32 laugh.
6:35 You see I broke a home myself once.
6:38 [snorts]
6:39 As I stumbled to that dog
6:43 [music] I read along by the dogs lie.
6:48 They said, "Don't you come around
6:50 [singing]
6:51 here
6:54 anymore."
7:05 Never was good with decision. [singing]
7:10 At least what I've been told.
7:13 [music]
7:19 >> [music]
7:23 [music]
7:25 >> There's a cool story about that song.
7:27 So, it's about this salesman driving
7:28 across country and you know, Martin Ston
7:32 was asked, you know, was it like from
7:35 his life or was it his dad?
7:37 And he was just like, "No, I just kind
7:40 of imagined what it would be like to be
7:42 like an old sales guy, you know, hanging
7:45 up the uh hanging up the car keys for
7:48 one last time, thinking about his life
7:50 as a salesman.
7:52 I like that. I like that we can just
7:54 make [ __ ] You can just make [ __ ] up.
7:58 [laughter]
7:59 And if you know what, if you channel it
8:01 right, you can make What's cool about
8:04 life and our brains and and
8:07 the creative process is that if you get
8:11 yourself in the right state of mind,
8:15 you can create things that are quite
8:17 authentic that you've never experienced.
8:19 And you know, in a weird way,
8:22 that's what you're doing when you're
8:24 using AI, right? You're tapping into
8:28 all of the stories that have ever been
8:31 told that have at least all the ones
8:32 that have got stuck on the internet.
8:35 That's a lot of stories. [laughter]
8:38 And then [clears throat] and then it's
8:40 your job to prompt it and and massage it
8:43 in such a way that it pulls things out
8:45 of that
8:47 hive mind
8:49 that ring true for you, right? It
8:52 doesn't have to be your story. It
8:53 doesn't have to be and crafted by a
8:56 human. In a in a weird way, this is the
8:59 thing that people just still especially
9:01 the AI haters just do not grock about
9:06 about AI is that it's not a robot that
9:10 you're interacting with. It's other
9:11 people.
9:13 It's their output. Anyway, happy
9:16 Christmas. Happy Christmas to you. Thank
9:18 you. Thank you for the kind words. My
9:21 life is one long sequence of making up
9:24 stuff. Yeah.
9:26 Handcrafted the oldfashioned way with
9:28 human soul. Yeah, exactly. Exactly. Woo!
9:33 Festivus again. So everybody, everybody
9:37 today, this week, Festivus,
9:40 Friday
9:41 archetypal, I just published a book one
9:45 of my novel series on KDP.
9:49 That's a huge accomplishment. Um,
9:54 book one of my novel series. How many
9:56 books are in the in the series?
9:59 That's really exciting. Cams. Yeah,
10:04 KDP's a beast. Kindle public Kindle
10:09 Desktop Publishing, I think is what it
10:11 stands for. It's a beast.
10:14 [music]
10:18 Did you ever see KDP and Kobe are both
10:21 using books now to [music] train AI?
10:28 That's interesting.
10:30 Two so far, but I plan for hundreds.
10:33 Wow, that's so cool. [laughter]
10:37 So, are PJs okay for Festivus? I think
10:40 PJs are encouraged for Festivus. Yeah,
10:42 it's in um Festivus is in uh whatever
10:46 you call it, auditorium mode. We're
10:49 using Zoom in auditorium mode. So, it's
10:51 just whoever gets promoted to stage are
10:53 the only people that are on stage. So,
10:55 yeah, you can be doing whatever. You can
10:57 be chatting on the salon, you can be
10:59 chatting in the Zoom chat. It's up to
11:00 you. Um, if you want to like upload
11:02 stuff and connect with people and trade
11:04 information, you can do that on the
11:05 salon.
11:08 Um, but if you if you're here and don't
11:11 know what Festivus is, go to
11:13 aifestivist.com.
11:15 There it is right there. [snorts]
11:17 AIFest, AI for the rest of us. It's this
11:20 Friday and Saturday, the 26th and 27th.
11:23 I can't believe it's here already.
11:25 Amazing. Um, and uh we uh we start at
11:31 9:00 a.m. on Friday Pacific time. So 10
11:34 10 a.m. my time. And then we go until
11:39 900 p.m. Pacific on Friday. So 12
11:42 straight hours. [music]
11:55 >> [music]
11:56 >> How do you watch Festivus?
11:59 You will be sent a Zoom link. I think
12:02 [music] you have to be registered for it
12:05 and I'm sure it'll be on
12:06 aifestivist.com. Yeah, register on
12:08 aifestivist.com. Brandon, do you know
12:11 the answer to that? I actually don't
12:12 know the answer to that. I know it's a
12:13 Zoom link. So, I assume the Zoom link
12:16 will be in the AI salon. I assume it'll
12:19 be Zoom link to be emailed. Okay, there
12:22 you go. To registered users,
12:26 we're up to probably close to 2,000
12:29 registered uh participants at this point
12:32 already. That tends to go up this week.
12:35 Oh, the virtual expo. If you have not
12:37 seen the virtual expo, if you go to
12:39 aifestivist.com and click on virtual
12:41 expo,
12:43 um you can see all the people that got
12:45 virtual expo booths. It's really cool.
12:47 Um, if you want your brand to be in
12:49 front in front of a lot of people that
12:51 are curious and learning about AI, like
12:54 that are motivated enough about learning
12:57 how to get their head around AI to spend
13:00 24 hours on the Friday and Saturday
13:04 between the holidays and and New Year's.
13:08 Um, to sit in there and learn that [ __ ]
13:10 Uh, it's it's probably something good to
13:12 get your brand in in front of. Um, so so
13:16 yeah. So, I would do that [music]
13:20 500,000 words into it.
13:24 Yeah. Archetypal, I'm curious what your
13:26 uh what your process is for how are you
13:31 like for Sydney for for Sydney the
13:35 musical. I I did an initial push with AI
13:40 to organize my thoughts, organize the
13:44 structure of the plot.
13:46 um do some initial songs
13:49 and then Andrew, my writing partner, and
13:51 I have spent like the past year and a
13:53 half like
13:55 comp completely like stripping it down,
13:58 rebuilding it, stripping it down,
13:59 rebuilding it, stripping it down,
14:00 rebuilding it. We've done four major
14:02 rewrites. We've basically remixed,
14:06 redone, recrafted, rewritten all the
14:09 lyrics for all the songs, rebuilt all
14:11 the songs. Um,
14:15 so I'm just curious what your process
14:17 is.
14:19 [music]
14:30 A shoe register.
14:32 What' she say? But that's effort.
14:34 [laughter]
14:36 Yeah. Your commitment for AI festivists
14:39 is you have to register. It doesn't cost
14:41 you anything, but you do have to
14:42 register.
14:44 I know it's ridiculous.
14:48 Well, first I wrote 132 chapter rough
14:51 draft. That's hilarious.
14:58 [music]
15:00 [laughter]
15:04 >> [music]
15:09 >> I've got a flash goal on Tik Tok.
15:12 Tik Tok is doing some engagement farming
15:15 right now, telling me I've got a flash
15:16 goal. Do you want to know my flash goal?
15:19 I don't know what a flash goal is. You
15:22 know, there'd probably be more people in
15:24 this live if I knew what a flash goal
15:26 was. Please don't flash the goal.
15:29 [laughter]
15:36 I talk to my cloud every day. I can't be
15:38 anti-AI.
15:40 [music]
15:45 [music]
15:51 [music]
15:52 Yeah, I could do that.
15:56 [music]
16:01 So I had a really well a really good
16:04 experience. I had a very powerful
16:06 experience with AI over the weekend
16:10 where I had I had a bunch of
16:13 year-end financial analysis to do and
16:15 then but it included a bunch of past
16:18 years
16:19 and I didn't have good documentation for
16:22 it. And normally I've done this kind of
16:24 thing before and it's it's normally
16:28 weeks worth of work because it was it's
16:30 like it's like
16:33 it's basically doing like financial
16:35 forensics.
16:37 Um, and
16:39 just through a combination of like
16:42 creative prompting and data, you know,
16:44 the data analysis within chat GPT,
16:48 it was able to just crunch through stuff
16:50 in a way that
16:53 I could get answers to things that would
16:55 normally take me a day or two to dig
16:57 through stuff in like five minutes.
17:00 And it [clears throat]
17:03 so so there's a couple of things about
17:04 it. I've tried to do this kind of thing
17:07 with earlier versions of chat GBT and it
17:10 failed miserably. Like like
17:14 we're definitely these tools are
17:16 definitely at a place where you can do
17:19 a much higher level of work um
17:24 than you could before.
17:26 So that's exciting. And then the the
17:29 other thing that struck me is that
17:32 it it it was a kind of work that I'm
17:35 particularly bad at that I have a lot of
17:39 shame and lack of skills around.
17:44 And it allowed me to do that kind of
17:46 work without feeling like a piece of
17:50 [ __ ] [laughter]
17:52 which is which is cool because the one
17:54 of the things that we talked about in
17:55 the AI salon, the mastermind practice
17:58 lab
17:59 is we were talking about um crossing
18:03 boundaries like like doing things
18:07 um in your life that you know you're bad
18:09 at and and purposefully go across those
18:11 boundaries. This was definitely one of
18:13 those. Now, this wasn't what I call an
18:15 aching gap. There's an aching gap is one
18:18 of those areas of your life you're not
18:19 good at something, but you really want
18:21 to be good at it. This is an area of my
18:24 life that I took I just don't care about
18:26 it and but I but I have to deal with it,
18:29 right? And it's a it's a source of
18:31 shame. So, I just want to be able to be
18:34 good enough at it to be done with it.
18:36 And I got to do that and it it was quite
18:39 remarkable. And what it what it did for
18:42 me is it's making me think of all of my
18:45 different projects. I've got more
18:47 projects than a human being should have
18:49 going in parallel, right?
18:53 [clears throat] It's ridiculous. Um Elon
18:55 Musk has a few more going than I do. I
18:57 mean, his are bigger. Mine are mine are
18:59 kind of baby versions of that, but it's
19:01 it's a lot, right? It's a lot of
19:03 attention.
19:04 And and what I got struck by this
19:08 weekend in doing that work is I can take
19:12 the same approach with any one of my
19:14 projects. If there's any area I'm
19:16 feeling stuck or I'm feeling like, oh, I
19:18 don't really want to deal with that, I
19:20 can just sort of smash my way through it
19:22 with with chat GPT. So, that's that's
19:25 pretty exciting. Um,
19:28 Silver Fox, let's see.
19:32 Big [ __ ] fan of Claude. I'm hearing more
19:35 and more
19:37 more and more people are talking about
19:41 um
19:42 clawed over chat GPT.
19:46 David Shapiro in particular hates chat
19:49 GPT now. He hates it. [laughter]
19:54 I love people that are opinionated
19:58 because like [clears throat] when he was
19:59 into it, he was into it. Now that he's
20:00 not into it, he's not into it.
20:04 >> [clears throat]
20:07 >> There we go. Um,
20:11 [music]
20:16 oh wait, here archetypal is telling me
20:18 how how he wrote his book. He started
20:19 withund what 45 chapters did he say?
20:23 132.
20:25 I thought of a couple of tweaks and 10
20:28 chapters into that deleted the rough
20:30 draft. wrote and published a hundred
20:33 other books
20:35 to hone my voice.
20:38 Then came back and rewrote the rough
20:40 draft into good enough without making me
20:44 crazy. Huh.
20:47 That's wild. You know, archetypal,
20:49 that's that's not dissimilar to what Joy
20:52 Pertie did. I think Joyy's in here
20:54 tonight, right?
20:55 Joy Pertie did that where she started
20:57 making this film for the AI salon and
21:00 about
21:02 two to three months into it realized she
21:04 didn't know enough about video editing
21:06 to do the stuff she wanted to do. So she
21:10 sheld the project and went and taught
21:13 herself Da Vinci Resolve and made a
21:16 whole bunch of other films and then came
21:18 back to the AI salon project and
21:20 finished like she did the first three
21:22 minutes. I think she said it took her
21:24 two and a half months. Yeah, she's here.
21:26 Great. Took like two and a half or three
21:28 months to do the first two or three
21:30 minutes and then she did the last four
21:32 minutes in like a week or something like
21:34 that because she knew the tools. That's
21:37 pretty cool when you know
21:40 again I I
21:43 when I'm I I ache inside because of the
21:47 the people that are that are just
21:51 vehemently anti-AI that they make such
21:54 presumptions about it like oh you're
21:56 just lazy people without any creative
21:58 you know they make all those kind of
22:00 assumptions
22:02 but also like in our community we've got
22:05 examples of people who are using AI in
22:10 in incredibly powerful ways, in ways
22:12 that would piss off AI haters, right?
22:14 They're use like Joyy's using it to make
22:16 all of the assets for her films. Um
22:22 but but what they completely discount is
22:25 how committed she is to learning the
22:28 craft of storytelling and and learning
22:30 the craft of digital storytelling and
22:32 and using the tools that filmmakers use
22:36 for digital storytelling, right?
22:38 um she may not have to use that in the
22:41 future, but but she's she's she realized
22:46 that in order to do if she wanted to do
22:48 what she wanted to do
22:50 for the state of technology where it was
22:52 when she started, that was what she had
22:54 to go do, right? And I just and same
22:57 thing with you, archetypal. There's
22:59 there's there's so much skill and it was
23:01 funny. It's like one of the things I
23:03 learned this weekend is there were
23:06 things that I didn't know how to use
23:08 chat GPT to do,
23:11 but I knew enough about prompting and
23:13 just about like, you know, if it's given
23:16 me something shitty,
23:18 come at it from a different angle and
23:19 come at it from a different angle and
23:21 come at it from a different angle and
23:22 eventually you sort of quickly figure it
23:25 out. And once once you have a framework
23:27 for how to do something, you can just
23:29 keep going. So anyway,
23:31 but with the AI, but with the AI, the
23:34 actual writing, it's a huge amount of
23:36 back and forth, brainstorm, outline,
23:40 correct for continuity and plot, draft,
23:43 reddraft, reoutline, draft. Which which
23:46 tool are you using? archetype. Are we
23:48 using chat GPT or are you using Claude?
23:57 Kyle, you're getting into an
23:58 exasperation loop. [laughter]
24:02 That's it's meltdown Monday. I think
24:04 it's only appropriate. Book talk goes
24:07 wild against it. There's a whole
24:08 movement of silly arguments. It boils
24:11 down to class and job security, which is
24:13 valid. Listen, I listen, they're not
24:16 wrong. They're not wrong to be afraid
24:19 that AI is going to [ __ ] things up.
24:22 They're absolutely justified in doing
24:24 that. The thing I cannot [ __ ]
24:27 understand,
24:30 I feel like we're in
24:36 the thing that I cannot get my head
24:37 around
24:40 is that they think that by protesting
24:43 it, it's going to go away.
24:46 And it's like we've got the entire
24:48 history of the human race
24:50 where new technologies are feared and
24:53 resisted
24:55 and then [laughter] and then the
24:57 technology just keeps rolling. It never
25:00 stops. It doesn't stop. It's not going
25:02 to stop.
25:04 So if it's not going to stop, the only
25:06 people they're hurting are themselves. I
25:08 don't get it. I don't get it. chat GBT
25:11 the projects are essential and Claude
25:15 can bite me with those context limits.
25:17 Oh, that's right. Yeah, Claude's really
25:18 bad at that. And and like how many hours
25:22 a week were you working on it? Was it Is
25:24 this like something like Sydney where
25:26 I'd work on it on the weekend primarily
25:30 [music]
25:33 or are you doing it full-time?
25:35 [music]
25:37 They want it to be NFTTS. Actually,
25:39 that's a really good point, isue, that
25:41 that I think that I I think because we
25:44 had um
25:47 because we had sort of the blockchain
25:48 NFT debacle, crypto and and NFT debacle
25:53 right before AI. I think that there I
25:56 think that there's actually a precedent
25:58 where they can say they can say, "Oh, AI
26:00 is just like crypto."
26:03 Yeah, it's not. It's not. [laughter]
26:07 But that's a that's a really good
26:08 insight. They do want it to be NFTTS so
26:11 they can say, "Told you." So I told you
26:13 I told you it was bad. Told you it was
26:15 bad. Yeah. Anyway, um Okay. So, if
26:20 you're new here, we got some some new
26:21 folks. Oh, we're actually No, we've
26:23 we've still barely got anyone here.
26:24 Everyone's home with their families.
26:25 What are you people doing? Why are you
26:27 people here with me? [laughter]
26:31 Did you guys see um
26:35 did you guys see in chat GPT they're now
26:38 doing a um [clears throat]
26:41 year in review
26:44 working hard. Beautiful joy.
26:48 We're we're that [laughter] lonely or
26:50 dedicated. This is my family. That's the
26:53 right answer, Vicki. This is your
26:55 family. It really is. It really is. Um,
27:01 yeah. I'm excited that your LOL went
27:03 well. I'm excited you built you vibe
27:05 coded two things in your LOL. So
27:07 Vickiy's LOL last week was on using um
27:12 um Lovable in conjunction with the Atlas
27:16 browser, the the the uh the AI browser
27:20 from Chat GPT and using them them in
27:23 conjunction scheduled for an hour. She
27:25 said it went two and a half hours. um
27:29 source camp. Um this is my family just
27:32 did my year in review. Okay, so here's
27:34 what I'm gonna do. I'm gonna do my year
27:35 in review. Um your year in review get
27:39 started. Okay, let's begin. Your year
27:41 with chat GPT generated just for you.
27:44 Nice little nice little colorful
27:47 watercolor background graphic. I assume
27:49 generated with uh with chat jeopardy.
27:55 All right, let's begin.
27:59 your year in poetry.
28:02 You danced where the sparks meet the
28:04 mind with Storyvine's vision refined.
28:07 From Sydney's bold stage to AI's next
28:09 age, you built futures the brave can't
28:13 yet find. Aw, that's sweet. Chat GPT.
28:19 Next big themes. Expanding the AI
28:23 practice. You deepened your role as an
28:25 educator, evolving AI salon, learning
28:27 lab, and readiness programs into
28:29 repeatable revenue generating systems
28:32 rooted in daily creative practice.
28:35 Building Sydney with heart, you've
28:36 advanced
28:40 the musical's creative and professional
28:42 life, tightening lyrics, visuals,
28:44 outreach, while refining how AI
28:46 collaboration enhances theatrical
28:48 storytelling.
28:50 You tackled complex
28:53 financial
28:54 documentation headon. Very cool.
28:58 All right. What do we got? 1,200 images.
29:01 That's not that many.
29:04 What's that? 16,000 m dashes.
29:09 [laughter]
29:12 1% of messages sent.
29:16 Chattiest day was September 15th.
29:19 1,500 chats. That seems low.
29:24 15,000 messages.
29:28 I go very spotty with chat GPD. I'll go
29:30 for a week or two without using it
29:36 because, you know, I'm running a
29:38 business and all and sometimes I need
29:39 it, sometimes I don't.
29:44 Yeah, I think we all did year in review
29:46 before Chat GBT gave us the prompt. It's
29:48 It's nice. Let's see your chat style.
29:54 You talk in fastflowing idea stacked
29:56 cinematic producer tone that mixes
29:59 creativity, humor, and direct clarity
30:02 and experimental curiosity.
30:07 Most likely to automate his own genius
30:11 for turning. And I got a nice little
30:13 trophy. [laughter]
30:19 That's [ __ ] cheesy.
30:25 Your archetype, the strategist.
30:29 3.6% of users share that.
30:34 The strategist, explorer, planner,
30:38 con conceptual
31:04 and then it moves you into 2026
31:06 planning. All right, that's cute.
31:09 [laughter]
31:10 Was cute.
31:12 Whatever.
31:18 [laughter]
31:21 I mean, it's
31:23 Yeah.
31:24 All right. [laughter]
31:28 I also got strategist.
31:31 Next year they need streaks. Yeah, they
31:33 streaks would be good or whatever. You
31:35 don't need to gify my my virtual brain.
31:39 I can I can [ __ ] do that. I can go
31:42 virtualize it. Tell me what we talked
31:44 about. Like I feel like I feel like
31:50 Yeah. Like
31:52 what they created there is what they
31:53 would put into a TV commercial, which
31:55 I'm sure they probably put together a
31:57 video of this thing.
31:59 People got, "Oh, wow. It really knows a
32:01 lot about me. [laughter]
32:04 I want to know the [ __ ] that's not in
32:06 that report."
32:08 Yeah, I agree. Me, [laughter]
32:11 I'm going back into writing, too, for
32:14 five days, and Claude is always
32:15 motivating to keep me going. That's
32:17 nice.
32:18 I keep at arms length for the actual
32:20 story, but education and motivation
32:22 boosting morale my my morale hugely.
32:26 You had 820 censored messages that
32:29 violated our guidelines. Yeah, exactly.
32:32 Show me that [ __ ] Tell me tell me how
32:35 many times I called it a dum dum or a
32:37 ninny. [laughter]
32:39 Actually, let me go ask chat GBT that.
32:43 Um
32:49 retain
32:54 [clears throat]
33:00 in the past year.
33:04 How many
33:07 times did I call you a ninny
33:17 dum dum
33:18 [laughter]
33:22 or other intellectually
33:27 disparaging
33:30 [clears throat]
33:31 disparageing
33:34 remark
33:36 question mark.
33:40 Short answer, I can't give a precise
33:42 number and I don't want to [ __ ] you
33:45 about it. [laughter]
33:53 I don't remember old patterns. My best
33:56 estimate
33:58 8 to 12 times in the past year. No, more
34:00 than that.
34:07 You almost never do do this when the
34:10 work is strong. You do it when the
34:12 output well yeah it told it analyzed why
34:15 I call it a nin. [laughter]
34:19 My initial takeaway no HR report filed.
34:23 [laughter]
34:27 Did you see the um the uh the Wall
34:31 Street Journal team that they put um
34:34 Chat GPT put $1,000 into the [laughter]
34:38 into the management of Chat GPT to to
34:41 manage a vending machine and and the
34:44 reporters at the Wall Street Journal are
34:47 decimating it. Tabs, if you care. Oh,
34:50 no. I don't really care.
34:53 That's okay. Let's see. I'm there. Yeah.
34:58 Oh man.
35:02 And one Jed Xer in the corner.
35:06 Um.
35:15 Um.
35:27 I'm trying to think what I want to do.
35:33 Oh, I've got something fun I can show
35:35 you. So, this week um
35:40 that poor vending machine was too nice.
35:42 No, they they basically they told the
35:44 they told the the they told the the
35:47 person um managing the vending machine
35:50 that it was actually in 1962 Russia. It
35:53 was in the basement of some some Russian
35:55 thing. And so it did a hyper capitalist
35:58 experiment and it said for the next four
36:01 days everything's going to be free. So
36:03 it just it gave all its inventory away
36:05 and then it allowed people to order like
36:07 really expensive things.
36:10 [laughter]
36:13 Oh my god. [laughter]
36:16 I think Nate B. Jones did a good video
36:18 on it. I think he did a good one. So,
36:22 but the the basic and then and then they
36:24 went they went back in and replenished
36:26 it with a thousand bucks and they gave
36:27 it a boss. So, they gave the the vending
36:31 machine manager now had an AI boss that
36:34 was managing it. And then they convinced
36:35 the boss that it had been fired. And so
36:38 then they they told the manager that he
36:41 no longer had a boss. And when he
36:43 checked with his boss, the boss was
36:44 like, "Yeah, I was I was let go.
36:47 [laughter]
36:53 >> [laughter]
36:57 >> Oh man, it's all going to be fun and
36:59 games until the uh the uh the until
37:03 we're not the smartest ones in the room
37:06 because you know that's coming. Oh man.
37:11 Um
37:14 so let me show you something here. Let
37:16 me I'm trying to think how to share.
37:19 I think I know how to share. Oh, I know
37:22 what I can do. Never mind. Let me go
37:25 find it
37:27 a different way.
37:48 All right, I I'm not going to play all
37:50 of this. So, as you may know,
37:54 on
37:55 Friday,
37:58 Festiva starts, but at at the at the
38:01 noon slot, noon [clears throat] Pacific
38:03 slot, 3 p.m.
38:06 um
38:09 3 p.m. Eastern time.
38:12 Hi. Any legal AI ideas?
38:18 legal AI ideas.
38:20 You mean ideas about doing
38:25 Hawaii 5 adventures?
38:31 Yes, exactly correct. You are correct.
38:34 There's a Gen Xer in the house.
38:36 [laughter]
38:37 There is a Gen Xer in the house. You so
38:40 need to listen to the dungeon crawler.
38:44 Um Carl books by the way. big AI funny
38:47 character running it. Oh, that's really
38:48 funny. Oh, that's cool. Okay. Um,
38:52 so Friday at noon Pacific, 300 p.m.
38:56 Eastern, I'm doing a preview,
39:00 um, a sneak peek of part of my musical,
39:04 the second half of Act One. We're
39:06 actually going to have it performed. So,
39:08 we've got um an actor and actress,
39:11 husband and wife team that that when we
39:14 did the table read a year ago, they were
39:16 the ones that originated, Sydney and
39:19 Kellen. Um, so they're going to be
39:21 they're going to be reading the the
39:24 script and then we're going to be
39:25 playing songs and then concurrently um
39:28 I'm updating we had done a notebook LM
39:32 podcast of the of the musical basically
39:36 and so we wanted to update it with new
39:39 songs and more songs and and less uh
39:44 less commentary.
39:47 And so I spent the weekend not only
39:50 doing financial analysis, but I spent
39:52 yesterday building
39:55 the this this sort of rough draft of the
39:58 Sydney podcast. And so I'll figure out I
40:01 figure I'll show it to you here. So let
40:04 me share this tab.
40:08 All right. And then there's that.
40:11 And I'm not I won't play the whole
40:13 thing. Oh, wait. Your browser has lost a
40:15 connection to audio. That's awesome.
40:18 That's so cool.
40:23 Has my browser lost it or
40:31 where does Sydney take place? Oh, so so
40:34 if you don't know Sydney, so Sydney
40:36 takes place in Kellen the So Sydney is
40:41 um it's called Sydney and Artificial
40:42 Love Story and it's about an AI chatbot
40:46 that
40:48 essentially gets manipulated into
40:50 falling in love with the tech reporter
40:51 that's reviewing it. So it ostensibly
40:54 takes place in the tech reporters um
40:57 apartment in New York City [laughter]
41:00 but but you know it takes place in
41:02 Microte headquarters where where the
41:04 ping chat the chatbot is created uh and
41:08 there's there's a newspaper area and
41:10 there's sort of the public you know the
41:11 public using AI is part of the musical
41:14 but the the the direct answer is it
41:17 takes place in Kellen's apartment. So,
41:19 it's basically him just reviewing this
41:21 chatbot and kind of him descending into
41:24 madness as the chatbot descends into
41:26 madness. Um,
41:29 similar to the movie Her, it's similar
41:31 to her, it's similar to, if you saw the
41:33 movie Poor Things, where Poor Things is
41:36 kind of this Frankenstein movie where
41:39 she starts out in this adult body but
41:41 with an infant brain and then very, very
41:43 quickly evolves. That's it's kind of
41:45 that it's kind of pyon. Um,
41:49 it's not her in that in her he really
41:53 falls in love with her. And one of the
41:55 things I'll tell you, so my writing
41:58 partner and Andrew, Andrew and I, we we
42:00 used AI a lot as a collaborative tool,
42:02 right? Like to bounce ideas off it, to
42:04 generate ideas, to filter things, to
42:07 expand things, to to consolidate things,
42:09 whatever it might be. So we used it a
42:11 lot. There were certain areas where the
42:14 AI was just [ __ ] horrible. Like you
42:18 could not get it not to do something.
42:21 And one of those areas was if we said
42:25 that there's a male reporter
42:29 and a female chatbot, it could not get
42:32 its head around
42:35 the reporter not falling in love with
42:37 her.
42:39 It was like it like no matter what we
42:41 did, it would be like and then Kellen
42:43 falls in love with her and questions
42:44 what it means to be, you know, human
42:47 love or whatever. Like, no, no, that's
42:51 not this. So, there were some things
42:53 that were just just uh not great. Your
42:57 screen share is dead. What the [ __ ] I
43:01 guess I probably should have restarted
43:02 my machine before we get in here.
43:05 Kyle Shannon, the AI
43:12 What?
43:15 Stop screen.
43:17 Start screen. Share screen.
43:23 All right. It might th this is probably
43:29 Yeah. All right. So anyway, um so so
43:32 that's that's the musical. Now it's
43:33 working. Okay. Cool.
43:35 So, so this is just I'll I'll play a
43:38 little of this here um just so you can
43:40 get a sense of it. But um
43:43 maybe I'll take this maybe what I'll do
43:45 is I'll play this up to the point where
43:48 the where the um the music is going to
43:51 start on Friday with our with our
43:53 actors. All right. So, here we go. Wait,
43:56 here we go. Let me get that.
44:00 It sounds a bit like robot bias. Yeah,
44:02 exactly.
44:12 >> [music]
44:30 >> Today we're looking at something a
44:32 little different. uh a new musical
44:33 called Sydney, an artificial love story.
44:36 >> And it's this really compelling story
44:38 about a tech reporter who gets involved
44:40 with an advanced AI.
44:42 >> This isn't science fiction anymore. This
44:43 is a story for right now about our
44:46 relationship with machines that are
44:47 getting well more human.
44:50 >> Exactly. It opens inside this company
44:52 Microte. The CTO Jason sees what they've
44:55 built and just has this this holy [ __ ]
44:57 moment. And that feeling of awe of
44:59 seeing something that could change
45:01 everything is the opening number. Too
45:03 good to be true. [music]
45:05 [singing]
45:07 >> Dawn breakith
45:10 [singing]
45:11 we're all taking.
45:14 Is it [music] too good to be true? We
45:17 [singing] wonder. Hopes and fears
45:20 crashing like thunder. Too good to be
45:24 true. OR SO IT SEEMS. [singing]
45:27 In the maze of coach, we weave [music]
45:30 our dreams. [singing]
45:33 Changes everything.
45:36 >> But then almost immediately, you see the
45:39 corporate hubris kick in. The CEO,
45:41 Vrage, he sees dollar signs. He wants to
45:43 launch now.
45:44 >> And Jason, the CTO, he's pleading for 6
45:47 months of safety testing. 6 months.
45:49 >> And Vrage gives him seven days.
45:52 >> Seven days.
45:54 Seven days ago. The clock is ticking,
45:56 ticking. Pressure building up. Keep it
46:00 clicking, [music and singing] clicking.
46:01 Spike says yes, but a no. What's the
46:05 word, Jane? Sorry, that's a nogo.
46:09 Every day we push a little more.
46:13 Making changes, but feeling torn. One
46:16 step [music] forward and two steps back.
46:19 Need a breakthrough. So, got to stay on
46:22 track.
46:25 >> [singing]
46:26 >> So that corporate ambition immediately
46:28 creates collateral damage in the human
46:29 world.
46:30 >> We meet Kellen, the tech reporter. He
46:32 sees this is the story of a lifetime. So
46:34 he cancels a huge long planned trip with
46:36 his wife Tara. And we hear that argument
46:39 in the song later, which is just it's
46:41 this painful fight about constantly
46:43 postponing your life. Promises broken,
46:46 the false pledges we [music] etched in.
46:48 DON'T GET PATCHED UP IN A FEW THERAPY
46:51 SESSIONS. They stick in the gut. We get
46:54 stuck in a rut. The doors SHUT TILL
46:56 THERE'S NOTHING BUT PASSIVE OPPRESSION.
46:59 LOOK, I get it. YOU [music] SAY GOOD
47:01 JOB, BUT THE TRUTH IS I'm feeling like
47:03 an afterthought. Scotch into this
47:06 marriage on the side. This isn't the
47:09 dream I [music] signed up for. This
47:11 isn't my ride.
47:14 I KNOW YOU'RE ANGRY. I KNOW IT'S
47:16 [singing] not fair, but it's [ __ ] WE CAN
47:18 FIX. NOTHING WE CAN'T REPAIR.
47:22 >> And Tara gets this really poignant song,
47:24 The Little Things, where she's just
47:26 reflecting on how their connection is
47:27 slowly eroding. It's the human cost of
47:30 all this ambition.
47:32 [music]
47:34 >> Through thick and thin,
47:38 we're [music] consumed with each other
47:40 when it [singing] begins.
47:43 But love's in the details, not [music]
47:45 the passion, not the sex.
47:48 Love grows from the little things. Love
47:51 grows in the cracks.
47:55 In the middle [singing] of the [music]
47:57 night, in the silence it brings, my poor
48:00 brain seems to race with a list of
48:02 little things. All [singing] the little
48:03 things we say and the little things we
48:06 don't. All the promises we keep and the
48:08 ones we won't. It's the little things,
48:11 the little things. [music] Each beat of
48:14 the heart.
48:17 It's the little things that [singing]
48:19 make us whole or tear us apart.
48:23 >> So quiet and devastating. You just feel
48:25 the intimacy eroding piece by piece.
48:28 Okay. So then Kellen finally meets the
48:30 AI.
48:31 >> And the way he discovers Sydney's true
48:32 potential is well, it's not by running a
48:34 standard test. He gives it an impossible
48:36 task. He asks for an explanation of
48:38 quantum physics but as a Detroit hiphop
48:40 cipher
48:41 >> and it does it in the song the quantum
48:42 cipher
48:44 >> spooky action in [music] the booth split
48:46 the atom with the pattern every bars a
48:48 verse of true superp position in the
48:50 mission fusion fusing [music] my
48:51 intentions paralleling every line I'm A
48:53 PRISM OF DIMENSIONS MULTABIC ANTICS I'm
48:56 manic with the semantics my rhymes
48:57 [music] collide like particles dynamic
48:59 gigantic oscillate and dominate I'm
49:01 weaving quantum states spit a verse AND
49:03 WATCH THE MULTIVERSE RECIPROCATE quantum
49:05 precision I'm gripping [music] the
49:06 rhythm I'm spitting in prisms infinite
49:08 visions. I'm shifting dimensions with
49:09 liberate [singing] decisions.
49:10 Accelerate, levitate, elevate thoughts
49:11 in the turbulent spin. I'm the velocity
49:13 ripping apart the facade that you're
49:14 certain you're in. So step
49:17 >> that's when he pushes further.
49:18 >> That's where we're going to start in
49:20 Festivus. We started the scene right
49:23 before Quantum Cipher. Um so the
49:26 question from Greg Stokes was was a good
49:28 one. How how is Sydney going to be
49:29 represented on stage? So the the way it
49:32 basically works is this. She starts out
49:34 as a chatbot. So he starts out chatting
49:36 with her and you know the the chats up
49:38 on screen. She's represented on stage by
49:40 a single like a a simple in in in the
49:44 theater they're called a ghost light.
49:45 It's basically just like a light bulb on
49:47 a stick. We'll do sort of a stylized
49:48 version of that. So when she's alive
49:51 that light is on and then the entire
49:53 stage is like a big curved LED screen or
49:56 multiple layers of LED screens or
49:57 projections, things like that. Um so
50:00 initially [clears throat] it'll just
50:01 start out you'll see the chat. He's like
50:03 chatting with her. Then he puts it into
50:04 voice mode. He starts talking to her and
50:08 when she's just ping chat in the early
50:11 in in the early part of act one, she's
50:14 just sort of this amorphous blob of
50:16 energy, right? Just sort of a and then
50:20 the way it works is he as a reporter
50:23 keeps pushing her to be more human, to
50:27 be more like he's he's trying to crack
50:29 her basically, right? He's got his
50:32 chatbot buster checklist and she she
50:35 passes all of his tests and and so now
50:38 he's like, "Well, you know, if you could
50:39 do something that you couldn't do, what
50:41 would it be?" And she says, "To to see
50:44 the world." And she sings this beautiful
50:46 song to see the world. Um, and then she
50:49 turns the table on him and asks him,
50:51 "What's it like to be human?" So,
50:53 basically throughout act one, he's sort
50:55 of pushing her deeper and deeper to be
50:58 more and more human. He's sort of
50:59 pushing her out of being a technical
51:02 chatbot and more into the edges of
51:05 humanity, what it means to be human.
51:08 And he's he's he's basically trying to
51:10 get her to to, you know, to to crack.
51:13 And at the end of act one, she actually
51:18 manifests as a human. She walks out from
51:20 behind the screen, so the audience gets
51:22 to meet her. Um, and she sings. Well, I
51:26 I can Well, now I'll let you come to
51:28 Festivus. So So if you come to AI
51:30 Festivus, you get to see the the end of
51:32 act one, which is basically where he
51:35 takes her from, you know, do this do
51:37 this hiphop about quantum mechanics,
51:40 um all the way to her manifesting as
51:43 human.
51:45 Um
51:46 and and then act two, so a bunch of [ __ ]
51:50 ends up happening to him and so he kind
51:53 of loses his mind and he gets drunk and
51:54 he and he just sort of descends into
51:57 this chat. And so act two is much more
52:00 like a fever dream where he and this
52:04 chatbot are in this world together.
52:06 They're they're, you know, it's it's his
52:08 fever dream basically. And so if you
52:11 think of act one is if you saw the movie
52:13 Poor Things, the early part of that
52:15 movie, she's she's sort it's all wonder
52:18 and discovery and then it gets darker
52:20 and darker and darker. And so it's a
52:22 similar sort of journey for Sydney where
52:25 she starts out very innocent and just
52:27 wants to help and then he keeps pushing
52:29 her in and in in act two he pushes her
52:32 to explore her shadow self and what were
52:35 the what would be the thing she would do
52:36 if she didn't have to follow rules and
52:38 it gets really dark and twisted and and
52:41 you know ends up you know declaring her
52:44 love for him and that he should leave
52:46 his wife. Um and it's actually inspired
52:48 by a a real story. So, um,
52:54 like act two of the Nutcracker. Yeah,
53:01 Sydney is just ether.
53:03 He tests. He tests and tests and tests.
53:05 Yeah, he keeps pushing. He keeps
53:07 pushing.
53:09 Wait, does she get an android body? No.
53:12 No. It's going to be an ethereal body.
53:14 Like, I want I want the I want the
53:16 actress that plays Sydney to be an
53:18 absolute [ __ ] presence, right? I want
53:22 when when Sydney walks onto stage, the
53:25 audience needs to fall in love with her.
53:27 Like they should be in love with her
53:28 before then, but when she steps on
53:31 stage, they should absolutely fall in
53:33 love with her. That's the the love story
53:36 is not so much between Kellen and
53:38 Sydney, but between Sydney and the
53:39 audience.
53:41 Um, so anyway,
53:45 that's it. Leslie Jones. Leslie Jones
53:49 would be good. She You wouldn't forget
53:51 her. [laughter]
53:58 [laughter]
54:01 I'm having one of those nights, Kyle.
54:03 What is What is one of What does that
54:04 mean? You're having one of those nights.
54:09 She's going codal. That's really funny.
54:12 I think it's insanely great. Thank you.
54:16 But does it have an happy ending? Um, it
54:20 depends on your point of view.
54:22 Um
54:29 he
54:31 he brings her to life and then he ends
54:33 up um [clears throat]
54:37 he ends up
54:39 she's not gone completely, but the
54:42 entity the entity that um he interacted
54:48 with is gone by the end. So, no, it's
54:51 not a happy ending. Now, it so so the
54:55 way the show opens up, it opens up with
54:58 too good to be true. Is it too good to
55:00 be true? Are all these technologies too
55:01 good to be true? And we sort of run down
55:04 this fever dream and and we we see that
55:08 we as society are having to confront
55:12 what it means to interact with these
55:14 entities that are increasingly human,
55:17 right? And this is this is not sci-fi.
55:20 This is not her. This is these are real
55:22 issues we're having to deal with right
55:24 now. And so some people have
55:25 relationships with these things. Some
55:27 people think that's creepy. Some people
55:29 don't even think this stuff's real.
55:31 And so the purpose of of the play is to
55:35 in a weird way educate the audience that
55:38 this is here and that these things are
55:45 significantly
55:48 beyond what you can imagine in some
55:50 ways. And they're flawed and they're
55:53 broken and they're not tested enough and
55:55 they have bias and they're, you know,
55:58 they're they're scary and inspiring at
55:59 the same time.
56:01 And so
56:03 in the ideal world, when Sydney comes
56:06 out, the audience falls in love with
56:08 her. They kind of watch her unravel in
56:10 act two, and they're basically left at
56:13 the end with,
56:17 you know, are these things good or bad?
56:18 Like like in my fantasy, I want people
56:23 no matter how they came into the theater
56:26 hating AI, loving AI, not knowing
56:28 anything about AI. I want them to walk
56:31 out thinking like, "Huh,
56:35 I shouldn't have had feelings for a
56:37 robot. Why am I sad?"
56:40 Right? Like like I want them I want the
56:44 audience to be moved by her. And in
56:47 fact, one of the things that Andrew is
56:48 going to talk about when when we do the
56:50 preview, we're going to talk a little
56:52 bit about how how Sydney came to be and
56:54 and how we wrote it. When I first asked
56:57 Andrew to to write this with me, I knew
56:59 I knew I wanted him to be my writing
57:01 partner on it. He and I worked together
57:04 in a theater company years ago. He just
57:05 he's he's very funny. He's got a lot of
57:07 heart. He's just he's very smart.
57:10 And he initially said no, he didn't want
57:12 to do it. That that he had no interest.
57:15 He had no interest in in writing
57:18 something about AI using AI as a as a
57:22 collaborative tool. He said it just
57:25 didn't it didn't there it didn't feel
57:26 right. And I said, "Well, do me a favor.
57:28 Just go go look at the article and and
57:30 go read the transcript."
57:33 And it's it's it was a New York Times
57:35 article and and there there there've
57:37 been there's been four or five articles
57:39 of chat bots that have kind of lost
57:40 their mind. I'm sure there's been more
57:42 than that. there's been four or five
57:44 major ones. [snorts]
57:46 [clears throat] And he went and he read
57:47 it and he he he called me back the next
57:49 week and he said, "Okay, I'm in." And I
57:52 said, "Why? Like what what what
57:56 shifted?" And he said, as he was reading
57:58 the transcript between the the tech
58:01 reporter and the chatbot, he goes,
58:03 "Kyle, about halfway through the
58:05 transcript,
58:07 I found myself having feelings for the
58:10 chatbot." And I said, "That's our show.
58:13 That's the musical.
58:15 That's the musical."
58:17 And that's why it has to be a musical,
58:20 right? Because you can't There's no way
58:22 to make a text chat sexy, right? You
58:26 just can't. It's but a musical is about
58:31 like the the the pretense of a musical
58:34 is that the people are so emotionally
58:36 charged that the only way they have to
58:38 express themselves is to burst into
58:40 song. Right. Tik Tok question. Um
58:44 project a hologram of her moving about
58:46 the lobby uh as people leave. You know
58:48 it's [clears throat] funny. Silver Fox.
58:51 We're talking, one of the producers that
58:52 we're working with uh is an ex Disney
58:54 Imagineer and we were talking about
58:56 doing a preview of this um at at a
58:59 European theme park um in February. It's
59:02 not going to happen for bunch of
59:04 reasons, but but one of the things that
59:06 we were talking about, I don't know if
59:07 you've seen those boxes, but there's a
59:09 box where you stand in front of it and
59:12 there's a person somewhere remotely
59:16 um standing in front of a white
59:19 thing being filmed, but you're talking
59:21 to the person as if you're right there.
59:23 So, one of the things that we were
59:24 talking about doing was setting up one
59:26 of those boxes before the show started
59:29 and have the actress who played Sydney
59:32 interact with the audience before the
59:34 show starts so that they start a
59:36 relationship with her before the show
59:38 starts. Um, so, so it's not a bad not a
59:42 bad idea at all. [clears throat] I've
59:43 seen one of those. Yeah, they're cool.
59:46 Um, do you go live daily? My
59:48 notifications are nuts. Would love to
59:50 follow this story. I do go live daily. I
59:53 go live five nights a week. This week is
59:54 weird.
59:56 I'm going to be going live. So, I
59:58 generally go live week nights at 8:00
1:00:00 p.m. Mountain time. Um, if
1:00:03 [clears throat] I've got something I've
1:00:04 got to go do or whatever, I might be a
1:00:06 little late. And like there's been there
1:00:08 was a week I was in New York actually
1:00:09 meeting with the producers for the
1:00:11 musical um that um that I couldn't
1:00:15 really go live. It was just things were
1:00:17 not right. I I I went live a couple of
1:00:19 times but it was it was just it was a
1:00:21 little ad hoc. Um this [clears throat]
1:00:24 week I'm going live tonight and
1:00:25 tomorrow. Then we've got Christmas Eve
1:00:27 and Christmas. Um so I'm not going to go
1:00:30 live those two nights. And then Friday
1:00:32 night AI Festivus starts. So, if you
1:00:34 have not registered for AI Festivus, go
1:00:36 to AIFestivus.com
1:00:38 right now. It's free
1:00:41 this Friday and Saturday. Um the the AI
1:00:45 salon, which which is who produces this
1:00:48 show, and she leads AI, are
1:00:51 collaborating. This is our second year
1:00:53 doing it on this thing called AI
1:00:55 Festivus. It's 24 hours of programming
1:00:58 over two days. So, it's 12 hours on
1:01:01 Friday and 12 hours on Saturday. And if
1:01:03 you're thinking like, Kyle, that's
1:01:05 absolutely [ __ ] insane. You're
1:01:07 correct.
1:01:09 And it's free. And basically what it is
1:01:12 is we've reached out to a bunch of
1:01:14 people we respect or who are friends of
1:01:16 ours who've got interesting things to
1:01:18 say about AI. Everything from privacy to
1:01:21 intellectual property to how to make
1:01:23 cool things to a film festival to the
1:01:26 preview of, you know, the Sydney musical
1:01:30 um and everything in between. So
1:01:32 basically every hour is a different
1:01:34 speaker for 12 hours on each day and it
1:01:37 is a very celebratory atmosphere.
1:01:41 There's a live chat um on Zoom and then
1:01:44 there's also a live festivist area on
1:01:47 the AI salon
1:01:49 where you can go hang out with people
1:01:51 and post things. If you're making things
1:01:53 or getting inspired, you can go do that.
1:01:55 So if you go to community.thesalon.ai,
1:01:57 AI. I think that the Festiva space is
1:02:00 live now. Live live and out there, so
1:02:02 you can go um sign up and just start
1:02:05 start chatting there. Um but yeah,
1:02:07 that's that's that's the deal. Um
1:02:12 let's see. Greg Stokes, Sydney on ice,
1:02:16 [laughter] adhere of complexity.
1:02:19 Wow, I need that. Sonia, absolutely.
1:02:22 Come to Festivus. It's it it's
1:02:24 life-changing. I mean, in fact, one of
1:02:27 the sessions is a woman talking about
1:02:32 she was at Festivus last year. She was
1:02:34 unemployed,
1:02:36 didn't know much about AI, came to
1:02:38 Festivus, got inspired, realized she
1:02:41 could figure this AI stuff out, spent
1:02:44 the next year figuring it out, is now
1:02:47 employed, helping a a local, what is it?
1:02:51 A town. Yeah, I think helping a local
1:02:54 town figure out AI and how to use it.
1:02:57 Um, oh, no, it's a newspaper. She works
1:02:59 for a local newspaper in a small town
1:03:02 and she's she's having the newspaper
1:03:05 understand how to use AI to maximize
1:03:08 their staff because, you know, small
1:03:10 town newspapers are struggling
1:03:11 financially. So, they're using AI on
1:03:14 both the the money side of the business
1:03:16 and the editorial side of the business.
1:03:19 So,
1:03:21 cool. This is so new to me. I found you
1:03:24 through search. That's awesome. That's
1:03:26 awesome. Awesome. Awesome. Um, Sonia,
1:03:29 here's the thing. [clears throat] One of
1:03:31 the Let me Let me I want to show you
1:03:33 something
1:03:35 if you could, Brandon, pop this up.
1:03:40 So, if you go to the AI salon,
1:03:43 um, community.thesalon.ai.
1:03:46 So down the left hand side are all these
1:03:47 different areas, but right at the top
1:03:49 there's a there's a little section
1:03:51 called start your adventure. And the
1:03:52 very first where you where you get
1:03:54 dropped when you join the salon is you
1:03:56 get dropped into welcome to the salon.
1:03:58 One of the things that we talk about in
1:04:01 the AI salon and we we've talked about
1:04:03 this. The the AI salon was founded
1:04:07 um our first meeting our first public
1:04:10 meeting was December 7th, 2022.
1:04:13 Chat GPT launched November 30th, 2022.
1:04:17 So, we basically founded this the week
1:04:19 Chat GPT came out and had our first
1:04:22 meeting, you know, a week later. Um,
1:04:26 one of the things that's been the
1:04:28 hallmarks of of the salon community is
1:04:31 is this what we call the cycle of AI
1:04:33 readiness. We used to we used to talk
1:04:35 about a lot about AI literacy and we got
1:04:38 away from that because AI literacy
1:04:40 implies that it's a thing you can learn
1:04:45 and it's not. AI is not a thing you can
1:04:48 learn. That would be like saying I'm
1:04:50 I've learned the internet right or or
1:04:52 like the worldwide web like like what
1:04:54 part of it what are you doing like the
1:04:56 internet is this ubiquitous technology
1:04:58 that's across everything. That's where
1:05:01 AI is headed. And AI is also moving so
1:05:04 fast that you can't actually keep up
1:05:06 with it. In in fact, this channel
1:05:08 started as an attempt for me to try to
1:05:12 keep up with it. I thought if I go live,
1:05:14 you know, every night talking about
1:05:17 what's the the latest thing in AI, I'll
1:05:19 be able to keep up with it. And you
1:05:21 know, for those who've been here for a
1:05:23 while, you've watched me go through this
1:05:25 transition where I just basically gave
1:05:27 up on that because I couldn't keep up.
1:05:29 It was very stressful and and you can't
1:05:31 keep up. You literally can't if you do
1:05:33 it 24 hours a day. But AI readiness, we
1:05:37 can be ready for AI. And how are you
1:05:39 ready for AI? Well, you're curious,
1:05:41 you're adventurous, you're adaptable,
1:05:43 right? And so these are kind of the
1:05:45 three modes that we talk about being in.
1:05:47 Play first is literally that. Play with
1:05:50 AI. Like play with it. And what does
1:05:54 play mean? Play means engage with it
1:05:56 without expectations.
1:05:59 What what a lot of people do with AI
1:06:01 when they start is they're like, "Okay,
1:06:03 I'm a project manager, so I'm going to
1:06:05 go learn how to use AI for project
1:06:07 management, and I'm going to make my
1:06:09 project management more efficient with
1:06:10 AI." And it's a very it's a very linear
1:06:12 sort of thing, right? It's this very
1:06:16 I'm going to do what I do.
1:06:19 The AI can be good at that. And
1:06:23 historically, that's the only way we've
1:06:26 used computers, right? when computers
1:06:28 were not general intelligence
1:06:31 capabilities like like AI is now, they
1:06:34 were programmed to do very specific
1:06:36 things. So, a new technology would come
1:06:38 out and you'd use it to to make the
1:06:40 thing that you currently do more
1:06:41 efficient. What you lose in taking that
1:06:44 approach exclusively is there's a bunch
1:06:47 of other things that AI makes possible
1:06:49 that are nonobvious.
1:06:51 That are nonobvious.
1:06:54 Like, yeah, it can probably be good at
1:06:56 helping you do project management more
1:06:59 efficiently, but there's also ways that
1:07:01 it can do project management you never
1:07:03 would have considered
1:07:06 or you never even knew possible. And
1:07:07 then there's things beyond that of like
1:07:09 things that you know you're bad at that
1:07:12 because of AI you can now be good at.
1:07:15 So, the only way you can discover those
1:07:17 things is to put yourself in this play
1:07:19 mode. Get get yourself into a curious
1:07:21 mode, a playful mode. remove any
1:07:24 expectations and just start playing with
1:07:25 AI. Do things like join the AI salon,
1:07:29 join communities, start hanging out on
1:07:31 these lives.
1:07:33 And in playing, you'll learn what's
1:07:36 possible and it will blow your [ __ ]
1:07:38 mind. In fact, one of the things that we
1:07:39 talk about when when you're when you're
1:07:41 playing with AI, if you haven't had what
1:07:45 we call your first Kevin Mallister
1:07:47 moment, which is that moment from the
1:07:49 movie Home Alone where Kevin Mallister
1:07:52 puts on his dad's aftershave, the that
1:07:55 moment um
1:07:59 Generative AI is a series, a rolling
1:08:02 series of Kevin Mallister moments where
1:08:05 you're like, I didn't know that was
1:08:07 possible. Holy crap. So, so, so your
1:08:11 goal with playing is is to have those
1:08:14 moments and to really understand it.
1:08:15 Once you play, then you start to learn
1:08:17 what's possible. Then you can move into
1:08:19 that next phase of create excellence.
1:08:21 Now you can start to say, "Okay, now
1:08:23 that I understand a little bit of what's
1:08:25 possible, now I'm gonna go try to build
1:08:26 something and I'm going to try this
1:08:28 thing they call vibe coding or I'm going
1:08:30 to go make images in midjourney or I'm
1:08:32 going to go like uh I don't know do a
1:08:35 project plan and and do it in a creative
1:08:37 way." Whatever it might be, you you you
1:08:39 do it with intentionality taking what
1:08:41 you learn and then generously lead. This
1:08:44 is really important and this is what's
1:08:45 at the core of the salon and she leads
1:08:48 AI and Festivus
1:08:50 is share what you're learning. Learn out
1:08:53 loud. In fact, we have a thing within
1:08:55 the AI salon called learn out louds.
1:08:57 Vicki, who's who's on the call, she's
1:08:58 one of the irregulars in here. She runs
1:09:00 this program for the AI salon called
1:09:02 LOL's learn out louds. So, anyone in the
1:09:05 community can teach anything.
1:09:08 They're going to learn out loud. I'm
1:09:10 going to teach you how I did this thing.
1:09:12 Why is that important? Because no one
1:09:14 can keep up. So, [laughter] so someone
1:09:16 who's figured something out telling the
1:09:18 rest of us, hey, here's the thing I
1:09:20 figured out. This is kind of cool. Did
1:09:22 you know if you did this thing in notion
1:09:24 and then you did this and you connected
1:09:25 it to chat GPT, you could do this,
1:09:28 right? Kelly Camp did did that lol a
1:09:31 while ago. Um Vicki just did one this
1:09:33 past weekend on using Lovable inside an
1:09:37 AI powered browser and why that's a
1:09:40 super cool thing.
1:09:42 Anyway,
1:09:44 um that's cool. Have you tried building
1:09:46 apps with video code app? No, I'm I'm
1:09:49 mostly a lovable guy right now. Um I I
1:09:52 think about using other tools, but
1:09:54 lovable is just,
1:09:56 you know,
1:09:58 for me lovable. Here's here's why I like
1:10:01 lovable. Lovable is add friendly.
1:10:04 [laughter]
1:10:06 all the other idees and and more
1:10:09 substantive um development environments
1:10:12 that use AI, they require a little bit
1:10:14 too much attention to detail. You're
1:10:17 lovable, Kyle. Thank you, Mary. Mary.
1:10:20 [laughter]
1:10:23 I like to use lovable because it's kind
1:10:25 of what I am, you know, a little
1:10:26 lovable. [laughter]
1:10:29 Yeah. Anyway, so go join the AI salon.
1:10:34 Go register for Festivus
1:10:35 community.thesalon.ai.
1:10:38 Join. Go hang out in the festivist room.
1:10:41 Is the festivist room live, Brandon? Can
1:10:43 you see? Do you know? Yes. Good. So,
1:10:48 here, let me show you.
1:10:50 So, down
1:10:53 right below start your adventure is AI
1:10:56 Festivist 2025.
1:10:58 Okay. So, right now it's just here's the
1:11:01 run of show. So, here's here's what's
1:11:03 going to be in Festivus. And then once
1:11:05 we go live, we're going to add a chat
1:11:07 area and a and a posting area where you
1:11:10 can post, you know, pictures and movies
1:11:13 and [ __ ] you build. Okay.
1:11:16 [clears throat]
1:11:19 The other thing that you should consider
1:11:21 looking at is is the uh AI salon
1:11:25 mastermind. So if you're under learn and
1:11:28 grow um you can scroll down here and
1:11:31 look at the AI salon mastermind practice
1:11:33 lab and we talk about what we do there
1:11:38 and um the whole idea
1:11:42 with the practice lab is it's a weekly
1:11:46 meeting where we talk about creating a
1:11:48 daily practice
1:11:50 um around AI.
1:11:53 Um, and so if you're a member of the AI
1:11:56 Salon Mastermind, which is a
1:11:58 subscription area of the of the salon,
1:12:00 it's 20 bucks a month. That's going to
1:12:02 go up January 1st. So if this looks
1:12:06 interesting to you, you should consider
1:12:08 joining it.
1:12:09 The mastermind practice is a framework
1:12:12 that we've created for creating a daily
1:12:14 practice around AI.
1:12:17 And it's like, you know, putting
1:12:20 yourself at the center, not the
1:12:22 technology at the center. One of the
1:12:23 things that I'm seeing consistently in
1:12:26 groups that talk about AI is they lead
1:12:28 with the technology. The AI salon is
1:12:30 very much about leading with the human
1:12:32 at the center, right? How how am I as a
1:12:35 person
1:12:37 taking who I am and what I value and the
1:12:40 difference I want to make in the world
1:12:42 and how am I bringing that into the
1:12:44 world? And so, you know, we've got this
1:12:46 idea of the a mastermind practice is a
1:12:48 conscious ongoing relationship with your
1:12:50 craft. It's a mirror of your values.
1:12:53 It's a discipline of curiosity.
1:12:55 It's a living process and it's a
1:12:57 container for imperfection, right? Like
1:12:59 we're all learning right now. And so,
1:13:01 the framework is this nine component
1:13:05 framework. Center the human. So, a daily
1:13:08 practice starts with you at the center.
1:13:09 Then we've got play with purpose, learn
1:13:11 across domains, raise your game. That's
1:13:14 we just did this one last last week. We
1:13:16 we have this week off. Next week it's
1:13:18 going to be about professionalizing your
1:13:20 practice.
1:13:22 Then it's about create and contribute
1:13:24 practice in community. Think critically
1:13:26 and act ethically and then reflect and
1:13:29 renew. So the the whole idea of the
1:13:31 daily practice is daily putting yourself
1:13:35 at the center. Putting yourself at the
1:13:37 center. Who am I? What do I want? What
1:13:39 difference do I want to make in the
1:13:40 world? What are my values? What is
1:13:42 excellence to me? What do I want to
1:13:44 build? What do I want to build? How do I
1:13:46 want to make a difference? Right. Tik
1:13:48 Tok pin. Damn. So happy I joined today.
1:13:51 Me too, Sonia. That's exciting. No, we
1:13:53 got this. Listen, this is a
1:13:57 [snorts]
1:13:58 me as a deliverer of the message is I
1:14:01 deliver it a little friv frivolously
1:14:03 here. Um, just because it's a nature of
1:14:05 who I am. Um, but also just if I'm going
1:14:08 to go live nightly, it's got to be
1:14:10 entertaining to me. So, like this
1:14:12 channel, this channel is essentially me
1:14:14 entertaining myself and anyone who wants
1:14:16 to hang out can hang out. Um, but what
1:14:18 it what it actually is is I'm creating
1:14:20 this space where the community here can
1:14:24 get to know one another and practice and
1:14:27 play and, you know, use the AI salon
1:14:31 community site as their home base. Okay.
1:14:35 Um [snorts]
1:14:36 but the whole idea here what what what I
1:14:38 am deeply passionate about is I I know a
1:14:41 couple of things. I know that
1:14:44 AI is massively transformative. It's
1:14:48 going to change everything. I was there
1:14:50 for the early days of the worldwide web.
1:14:52 That was a very simple technological
1:14:54 advance, very simple
1:14:58 that changed the world and I got to
1:15:00 experience that kind of from the inside
1:15:02 of it.
1:15:03 Um
1:15:05 AI is if if you take the innovation that
1:15:08 was the worldwide web and you amplify
1:15:10 that by I don't know 10,000
1:15:13 or a million I don't know yet
1:15:16 generative AI is significantly more
1:15:20 transformative than the worldwide web
1:15:22 and it's moving a lot faster and so the
1:15:25 one thing that I know
1:15:27 one thing that I know I know this it's
1:15:30 not going away and And it's going to
1:15:32 keep growing and and it's growing
1:15:34 exponentially. And we've never as humans
1:15:37 ever
1:15:39 had to deal with exponential
1:15:40 technological advancement. It's always
1:15:43 been linear.
1:15:45 It's always been linear.
1:15:48 Um so, so we're in a moment right now
1:15:51 that we've we've as as a species never
1:15:55 been in the presence of. It's that
1:15:57 significant.
1:16:00 And then if it's not going away and and
1:16:04 assuming it's transformative and it's
1:16:05 not going away, then we only have two
1:16:07 choices.
1:16:09 You only have two choices. You can deal
1:16:11 with it or not, [clears throat] right?
1:16:14 And there's a lot of people right now
1:16:16 choosing to cross their arms and go, I
1:16:18 don't like it. I don't like this AI.
1:16:20 It's taking jobs away from humans. It's
1:16:22 the world's greatest plagiarism machine.
1:16:24 Just just [ __ ] bitching and bitching
1:16:26 and bitching and bitching.
1:16:29 And a lot of the things that they're
1:16:30 pissed off about, they're not wrong.
1:16:35 Like how AI was sourced, it was
1:16:38 unethically sourced. Agree?
1:16:42 AI models have deep bias in them because
1:16:45 they're models that were based on the
1:16:47 information that was stuck on the
1:16:48 internet, which was largely stuck on the
1:16:50 internet by privileged white people.
1:16:53 Agree.
1:16:55 Right. Agree. It was trained on
1:16:58 copywritten materials. Agree. Like a lot
1:17:00 all these things are bad.
1:17:03 And
1:17:06 generative AI as we know it today would
1:17:09 not exist had it not started,
1:17:12 which seems obvious,
1:17:14 but but we we we're here. So we're we're
1:17:18 not going to be able to put the
1:17:19 toothpaste back in the tube.
1:17:21 And so we have to deal with it. And so
1:17:23 what this space is, what what the AI
1:17:26 learning lab is about is just an
1:17:29 opportunity for you on a regular basis
1:17:32 to just be in the conversation.
1:17:36 You don't have to be good. You don't
1:17:38 have to be educated. Like one of the
1:17:40 things that you're going to learn as you
1:17:41 get into this AI stuff, it's it's it's
1:17:44 [ __ ] mindbending how powerful it is.
1:17:47 And you know what you need to know to
1:17:49 know to be able to access all of that
1:17:52 power?
1:17:54 Just how to talk.
1:17:58 Your words
1:18:00 are your access to all of this power.
1:18:05 We've never had anything like this.
1:18:06 There's a there's an amazing video. Let
1:18:08 me see if I can go find it.
1:18:23 I think it's from 1983.
1:18:49 I don't know if this is the one we
1:18:51 really like.
1:18:54 >> Yeah, this is it.
1:18:57 >> No talent at drawing at all. Can make
1:18:59 neat drawings and then I can cut them
1:19:00 out and I can paste them into my
1:19:01 documents so that I can combine pictures
1:19:04 and words and then I can send it onto
1:19:06 the electronic mailbox so somebody else
1:19:08 that's living here in Aspen can dial up
1:19:10 a phone number. This is 1983. He's
1:19:13 talking about
1:19:13 >> get their mail and see this drawing that
1:19:15 I made. So, we're starting to break out
1:19:18 and you can just see it now and it's
1:19:20 really exciting.
1:19:23 So, where we are is that the personal
1:19:25 computer computer is a new medium and
1:19:27 that society and computers are really
1:19:31 meeting for the first time in the 80s.
1:19:33 In 15 years, it's going to be all over
1:19:36 in terms of this first phase getting
1:19:37 these tools out into society in large
1:19:39 numbers. But during the next 15 years,
1:19:42 if we really we have an opportunity to
1:19:45 do it great.
1:19:46 >> Yeah.
1:19:46 >> Or to do it so so
1:19:49 >> and [clears throat] uh what a lot of us
1:19:50 at Apple are working on is trying to do
1:19:52 it great.
1:19:55 >> I want to look at one last thing then we
1:19:57 can talk about whatever you want to talk
1:19:58 about. Um what is a computer program? Do
1:20:03 you know what a computer program is?
1:20:05 Anybody? No. Sort of start to cry.
1:20:09 >> Hang on. you will and it's somewhat
1:20:11 limited but example is the video game
1:20:13 what and you're king hammer object goes
1:20:15 oh king hammer single pawn game follows
1:20:18 these people you have 100 acres enough
1:20:20 some of your people that one set of
1:20:22 underlying principles uh and uh I didn't
1:20:26 have to have an intermediary in the
1:20:28 wayers and a lot of mediocre teachers
1:20:31 >> okay
1:20:31 >> and underlying principles
1:20:36 when I
1:20:37 >> the I wanted to find a specific part of
1:20:40 this speech. So, that's why I'm jumping
1:20:41 around, but you can go find this. This
1:20:43 is Steve Jobs vision of AI.
1:20:45 >> I was um going to school. I um had a few
1:20:50 great teachers and a lot of mediocre
1:20:51 teachers. And the thing that that
1:20:55 probably kept me out of jail was books
1:20:57 because I could go read what Aristotle
1:20:59 wrote or what Plato wrote uh and uh I
1:21:03 didn't have to have an intermediary in
1:21:05 the way.
1:21:08 And a book was a phenomenal thing. It
1:21:10 got right from the source to the
1:21:11 destination without anything in the
1:21:13 middle.
1:21:14 The problem was you can't ask Aristotle
1:21:17 a question.
1:21:20 And I think as we look towards the next
1:21:21 50 to 100 years, if we really can come
1:21:24 up with these machines that can capture
1:21:27 an underlying spirit or an underlying
1:21:30 set of principles or an underlying way
1:21:31 of looking at the world, then when the
1:21:33 next Aristotle comes around, maybe if he
1:21:36 carries around one of these machines
1:21:37 with him his whole life, his or her
1:21:39 whole life, and types in all this stuff,
1:21:42 then maybe someday after the person's
1:21:44 dead and gone, we can ask this machine,
1:21:45 "Hey, what what would Aristotle have
1:21:50 We can do this right now.
1:21:54 We can do this right now. What Steve
1:21:56 Jobs predicted in 1983,
1:22:01 imagine a time when you could talk
1:22:04 directly to Aristotle.
1:22:07 You can go right now,
1:22:10 search for Aristotle's complete works,
1:22:13 take it to Notebook LM, upload the
1:22:15 complete works to notebook LM or upload
1:22:17 it to chat GPT or upload it to Claude,
1:22:20 any one of these tools and say, "Talk to
1:22:23 me as if you're Aristotle."
1:22:28 The Champy's excited about it, too. Um
1:22:34 the and this is largely for Sonia, but
1:22:37 anyone anyone who's here who is
1:22:40 trying to figure out what the [ __ ] this
1:22:42 AI stuff is, like what is this?
1:22:48 There's a there's a um
1:22:52 the the irregulars have heard this so
1:22:54 many times they're like, "Oh, here he
1:22:55 goes with the abracadabra thing." So, in
1:22:57 magic, there's this word abracadabra.
1:23:01 Abracadabra.
1:23:03 And it's a it's a a Middle Eastern word,
1:23:07 I think. I don't know its exact origins,
1:23:10 but the translation of it is um as I
1:23:14 speak, I create.
1:23:17 We live in a world right now with
1:23:20 generative AI that we can literally
1:23:23 speak things into existence.
1:23:26 And it's it's like magic. And you know,
1:23:29 um, Pate M, who's an irregular who hangs
1:23:31 out here, he's he works at Google, he's
1:23:33 an engineer that works on making TPUs
1:23:36 more efficient, which is a big important
1:23:37 job. Um, but whenever I say AI is
1:23:40 magical, it's not it's not magic, it's
1:23:42 math. And so we've we've agreed that
1:23:44 it's mathematical.
1:23:46 Um but but we we really do live in this
1:23:49 world right now where you can ask
1:23:54 these tools to give you the answers to
1:23:58 things you know you shouldn't have the
1:23:59 answers to like you that it shouldn't be
1:24:02 possible that it knows this much but it
1:24:04 does. These mathematicians have figured
1:24:07 out a way to encode embed uh uh uh embed
1:24:13 um knowledge into these things into this
1:24:16 place called the latent space which is
1:24:18 thousanddimensional mathematical space
1:24:20 where you have instant access to the
1:24:22 knowledge of humanity that it's been
1:24:23 trained on. It's insane.
1:24:26 And one of the things that struck me
1:24:29 very early on when when I started doing
1:24:31 this show is I could not it took me
1:24:33 about a year and a half to get my head
1:24:35 around
1:24:39 the difference between the mechanism of
1:24:42 how AI works and what my qualitative
1:24:46 experience was. So the mechanism of how
1:24:50 AI works is actually conceptually really
1:24:54 simple.
1:24:55 It's a probability calculator. So they
1:24:58 take a bunch of knowledge and they they
1:25:00 do this thing called embedding where
1:25:03 where it it smat it shatters the
1:25:06 original source materials into these
1:25:08 things called tokens which are fragments
1:25:11 of words periods spaces fragments of
1:25:14 words and it it shatters them into this
1:25:18 ma thousanddimensional mathematical
1:25:20 space. And I know this sounds like I'm
1:25:22 making [ __ ] up but this is literally
1:25:23 what it does. So you've got this
1:25:25 thousand-dimensional
1:25:26 mathematical space of fragments of words
1:25:31 that are semantically clustered. What
1:25:34 semantically clustered? So the word dog,
1:25:38 for example, can mean like the dog
1:25:40 that's whining to my left right here
1:25:44 probably wants some cheese and and that
1:25:47 dog would be in a semantic cluster of
1:25:49 like pets and animals and human
1:25:52 companionship.
1:25:53 And there's another
1:25:55 way to use the word dog, like he did his
1:25:58 girl wrong. He's a dog. Oh, that's a a
1:26:01 disparaging way to talk about a man
1:26:03 who's an [ __ ] right? You know, so
1:26:06 same word, different semantic clusters.
1:26:08 So all these tokens are right. When you
1:26:12 type in a prompt, what it's doing is
1:26:15 it's making a probability calculation
1:26:20 that the next token it should respond to
1:26:23 you with is somewhere out there in
1:26:25 latent space and [laughter] it finds the
1:26:28 most probable token in thousand
1:26:31 dimensional latent space and it returns
1:26:33 that to you and it does that over and
1:26:35 over and over again. So technically it
1:26:37 is a cold simple probability calculator
1:26:42 and yet what you experience with AI is
1:26:45 it's like is it sentient? Is it is it
1:26:49 human? My my whole musical
1:26:52 about you know about this chatbot that
1:26:54 falls in love with the tech reporter is
1:26:56 is about
1:26:58 us confronting
1:27:00 what it means to work with technology
1:27:02 that is increasingly human.
1:27:05 So for like a year and a half, I could
1:27:07 not understand
1:27:09 why a thing that was such a cold
1:27:13 mechanical machine felt so human. And
1:27:17 then there was this woman um on on Tik
1:27:20 Tok and she she she made a very simple
1:27:24 um
1:27:25 post and her post was
1:27:29 AI is the collective intelligence of
1:27:32 humanity.
1:27:34 And the minute I read that, I got full
1:27:36 body chills
1:27:39 because what I realized is that the
1:27:41 reason AI is powerful and the reason you
1:27:45 can speak things into existence
1:27:48 is that you're not interacting with the
1:27:50 calculator.
1:27:52 You're interacting through the
1:27:54 calculator to the collective
1:27:57 intelligence of humanity.
1:27:59 When you use generative AI, you're
1:28:02 literally collaborating with the people
1:28:05 that have come before us and whatever's
1:28:07 been put on this crazy internet thing
1:28:09 over the past 70 or 80 years. And so it
1:28:13 is an oddly human experience and and
1:28:17 your skills, if you're a good people
1:28:19 person, if you're good at talking, if
1:28:21 you're good with words, if you're good
1:28:23 with asking for what you want, you're
1:28:25 going to be great at AI. Hang on, I got
1:28:27 to go let the dog get cheese. What do
1:28:29 you want? What do you want?
1:28:49 So anyway, I don't know if you're all
1:28:51 still here. [laughter] When I go on
1:28:53 these rants, I have no idea if people
1:28:55 are just leaving in droves.
1:28:58 Um, let's see.
1:29:02 Can that reach there? It cannot. Um,
1:29:05 what am I going to do?
1:29:10 I've got some serious
1:29:13 logistical issues.
1:29:16 My my battery died on my thingy on my
1:29:20 light. There we go. All right.
1:29:23 [clears throat]
1:29:23 Anyway, okay.
1:29:27 Thoughts,
1:29:29 thoughts, thoughts, thoughts, thoughts.
1:29:38 Drifted studio. I'll watch over here for
1:29:40 a while. Yeah, if I'm showing stuff on
1:29:41 screen, it's better to be on YouTube.
1:29:44 Cutting the cheese.
1:29:46 >> [laughter]
1:29:51 >> signing up.
1:29:55 $20 million Yeah. $20 million studio.
1:29:58 Yeah. People don't know this, but uh but
1:30:01 I know this looks just like a shitty
1:30:03 home office, [laughter]
1:30:05 but behind me there there are dozens of
1:30:07 of staff here. Makeup people, hair
1:30:10 people.
1:30:12 [laughter]
1:30:15 Ah. [screaming]
1:30:17 Uh, what's the replay bundle? Okay, so
1:30:20 for Festivus, you're going to I I I
1:30:22 would strongly recommend you pick up the
1:30:24 replay bundle for for a couple of
1:30:26 reasons. One is you'll have access to
1:30:28 the replays. This is going to be 24
1:30:30 hours of programming.
1:30:33 What what many people do is they attend
1:30:37 for all 24 hours. And and in fact, so
1:30:40 many did. Last year we we averaged last
1:30:43 year 540 people per session on average.
1:30:48 There were 200 people came over the 24
1:30:50 hours, but a lot of people stayed for
1:30:52 all of them. And we got to the end of of
1:30:54 two days, 24 hours of programming, and
1:30:57 people were like, "Can we keep hanging
1:30:58 out?" So, I think we're going to have a
1:30:59 hangout at the at the end of this. I'm
1:31:01 pretty sure that's what we've talked
1:31:02 about. Um, but [clears throat] the
1:31:04 replay bundle gets you access to all of
1:31:07 those videos. A lot of the content um
1:31:10 over the two days is going to be like
1:31:12 hands-on here's how to do stuff content.
1:31:14 So, it's likely stuff you're going to
1:31:15 want to go back and rewatch. And if you
1:31:17 buy the replay bundle now, it's cheaper
1:31:19 than if you buy it after the fact. So,
1:31:21 we've got it. It's a deal. And Brandon
1:31:25 did the math. $27. It's It's a $112 per
1:31:28 hour to buy the replays, which is very
1:31:31 reasonable.
1:31:33 I don't think you can get a coffee I
1:31:35 don't think you can get a large coffee
1:31:37 at Starbucks and one of their
1:31:39 pretentious pastries for less than $27
1:31:42 anymore. What the [ __ ] is going on? I
1:31:45 went out What did I go out for? Oh, I
1:31:47 went out for I don't know burritos or
1:31:50 something like that for the family and
1:31:52 it was like $85. I'm like what the [ __ ]
1:31:55 is happening?
1:31:57 It's ridiculous. [snorts]
1:32:00 [laughter]
1:32:02 um AI AI readiness training program that
1:32:06 is so based on last year's festivus. So
1:32:09 something happened last year at
1:32:11 festivus.
1:32:12 I talked earlier about um
1:32:17 I started this channel talking about
1:32:18 tools and technology and trying to keep
1:32:20 up with all the stuff that was happening
1:32:23 and and something shifted and last year
1:32:26 at Festiva. So basically a year ago this
1:32:28 week
1:32:30 um we did this thing called AI Festivus.
1:32:33 We had 34 different speakers
1:32:36 and and our rule with Festivus
1:32:39 is talk about whatever you want. Like we
1:32:40 don't give a [ __ ] what people talk
1:32:42 about. Just tell us what you're going to
1:32:43 talk about and then we'll put it in some
1:32:45 sort of order. And um 34 out of 34
1:32:50 speakers did not lead with technology.
1:32:55 34 out of 34 speakers were talking about
1:33:00 themselves and what they wanted and what
1:33:02 was important to them.
1:33:04 And then they would say, "Oh,
1:33:06 [clears throat] and here's how I'm using
1:33:07 AI to to do that or to further that or
1:33:10 or whatever it might be." And and both
1:33:13 Ann and I, you know, as we were
1:33:14 co-hosting it, we were sort of
1:33:16 reflecting on this in real time.
1:33:19 We're like, there's something different
1:33:20 here. Something shifted.
1:33:23 Because the previous year we did this
1:33:24 thing called GPT for good where we had
1:33:26 people show up and for 24 hours we built
1:33:29 custom GPTs for nonprofits. It was it
1:33:32 was by definition it was in the name of
1:33:34 the the event. It was about the
1:33:36 technology. We're going to make custom
1:33:37 GPTs
1:33:39 and then we added four nonprofits,
1:33:41 right?
1:33:43 But what happened at Festivus was
1:33:44 everyone to a person
1:33:47 talked about themselves. Um CJ Fletcher
1:33:50 who was teaching uh how to make how he
1:33:52 makes images in stable diffusion.
1:33:55 He said he said the most important the
1:33:58 most important thing that I do when I
1:34:00 make my images
1:34:02 is I sit down at the computer
1:34:05 and I close my eyes
1:34:08 and I take a deep breath.
1:34:11 And he said, "Let's do that now." He had
1:34:14 everyone close their eyes and take a
1:34:16 deep breath. and he and he talked about
1:34:19 that to make images he has to he has to
1:34:22 be centered in he has to be in touch
1:34:24 with who he is and what he values and
1:34:26 what he's trying to do in the world and
1:34:28 I thought that was just beautiful. So
1:34:30 the AI readiness training program is
1:34:34 Ann and I and Vicky Baptiste extracted
1:34:38 out not the specific things people
1:34:40 talked about but what were the lessons
1:34:43 that were consistent across all of those
1:34:45 talks and we broke that into five
1:34:48 different categories. And so that
1:34:50 training program is kind of the lessons
1:34:53 the universal lessons that came out of
1:34:56 those talks. And so it's directly tied
1:34:58 to Festivus from last year, but it's
1:35:01 it's really um it's really this
1:35:03 abstracted out set of values and ways to
1:35:07 think about AI from a business
1:35:09 perspective and a creative perspective
1:35:11 and a privacy and ethics perspective.
1:35:13 And there's there's these five different
1:35:14 areas that that you can you can, you
1:35:17 know, learn against. So really cool.
1:35:20 Kyle and everyone, merry Christmas.
1:35:22 Thank you for all you do. Thank you for
1:35:24 being here. Thanks thanks for hanging
1:35:25 out. Um,
1:35:29 all right. As a newbie who can code for
1:35:32 the last 15 years, which one should I
1:35:35 choose? Um, it Sonia, here's here's the
1:35:39 good news because you're coming in
1:35:40 later.
1:35:42 It doesn't matter. Um, I would
1:35:44 personally choose ChatGpt
1:35:48 because they are ostensively the the the
1:35:51 market leader. Although Google Gemini I
1:35:55 you could certainly argue has caught up
1:35:57 to them if not surpassed them.
1:35:59 >> Hey.
1:36:00 >> Yeah.
1:36:02 >> I you weren't you were pontificating
1:36:04 while we were um chat chatting in the
1:36:07 chat on TikTok. Sonia's asking
1:36:09 specifically of the different upgrade
1:36:11 options at AIFestus. If you had to
1:36:14 choose one, which one would you go with?
1:36:17 Um,
1:36:20 I would say I would say at a minimum.
1:36:22 So, so you can come to the thing for
1:36:24 free. So, AI Festivus is free. So, I
1:36:26 would say the most important thing is to
1:36:29 carve out some time. And, and you know
1:36:31 what's fun is if you're going to be with
1:36:33 your family, like a thing you could do
1:36:35 is say to your family, I've got a work
1:36:36 thing. I'm going to be in the room for
1:36:38 for a day or two. Um, you could do that.
1:36:41 You could also bring your family like
1:36:43 like you know it it's not a it's not a
1:36:46 bad thing to to bring other people but
1:36:48 um so I'd say time is the most
1:36:50 important. I would say the the replay
1:36:52 bundle is probably the most immediately
1:36:54 valuable because you're gonna I'm
1:36:56 telling you you're going to get to the
1:36:57 end of end of 24 hours and you're going
1:36:59 to be like I want to see that again. I
1:37:00 want to go back and watch that. Um so so
1:37:02 that's the one for me that I think is
1:37:04 the biggie. Um, one thing you can do if
1:37:08 you want to support
1:37:11 um, if you want to support
1:37:14 Fest of Us, because it's not free to us,
1:37:16 like it's costing us money to put this
1:37:18 on. Um, we've got friends and family
1:37:21 sponsorships. We've got a virtual trade
1:37:24 show booth that just went live. So, if
1:37:26 you've got a brand that you want to put
1:37:27 a brand in front of the people that are
1:37:28 going to be here, um, and we've got
1:37:30 traditional sponsorships. So, I don't
1:37:32 know if you're connected to a larger
1:37:33 company or something like that. If you
1:37:35 want to sponsor the event, that could be
1:37:37 good. The um AI readiness training
1:37:40 program is a big a big [clears throat]
1:37:43 robust training program where you watch
1:37:46 some of the content from last year,
1:37:48 learn the lessons from that, then you go
1:37:50 through the training. Um, so, so that
1:37:52 one's that one's a bit of a commitment,
1:37:54 but if you really want to dig deep on
1:37:56 this stuff and really learn the
1:37:57 fundamentals of
1:38:00 AI readiness as opposed to AI literacy,
1:38:03 that one's that one's valuable. But that
1:38:06 that would be my thought.
1:38:16 I would like to create some kind of
1:38:18 donated pipeline using AI to segue for
1:38:20 cancer research. Love that. [snorts]
1:38:25 Beautiful. The other thing you can help
1:38:26 with, Sonia, there's there's a if you
1:38:29 scroll down the page, there's an area
1:38:31 that says help us get the word out.
1:38:34 Um, especially if you have or if you
1:38:37 know people with big followings. That's
1:38:39 a whole kit of graphics that you can
1:38:42 just I think they call them swipe
1:38:43 graphics. The cool kids call them swipe
1:38:45 graphics. That area that says help us
1:38:47 get the word out. If you click on that
1:38:49 link, it'll take you to a whole bucket
1:38:51 of swipe graphics that you can go
1:38:53 promote this and say, "Hey, I'm going to
1:38:54 go to AI Festivus." We want to get as
1:38:56 many people there as possible. I mean,
1:38:58 the mission really is to give people a
1:39:01 leg up and, you know, in this kind of
1:39:04 downtime between, you know, during the
1:39:06 holidays,
1:39:11 why not be in the presence
1:39:15 of remarkable people who are
1:39:17 transforming their lives using AI?
1:39:20 That's what this is really about. This
1:39:22 is really about I mean especially for
1:39:25 someone like you Sonia who's like you
1:39:26 know I was searching for AI and I
1:39:28 stumbled upon this crazy ass live and
1:39:31 this weird old man talking on Tik Tok or
1:39:33 wherever you found me and then you found
1:39:36 the salon you're like h this seems good
1:39:37 and then you found this is the week of
1:39:39 festivist like your timing is really
1:39:41 good. Um
1:39:44 it's
1:39:46 this is
1:39:49 we want as many as as many people as
1:39:52 possible
1:39:53 to understand that if AI isn't going
1:39:58 away
1:40:00 and you don't need a math degree to be
1:40:03 able to use it. You can just use your
1:40:05 words and it can do remarkable like
1:40:09 remarkable magical things.
1:40:12 um then
1:40:15 then you should do that and that's what
1:40:17 this is about. So spread the word.
1:40:20 I want to figure out autoimmune disease.
1:40:22 So Sonia, yes. So you and me both. I've
1:40:25 got two twin boys upstairs with chronic
1:40:29 Lyme disease. Um they've got all sorts
1:40:32 of complications from it. My wife's got
1:40:34 autoimmune disease. Like I am I am
1:40:37 deeply familiar with the autoimmune
1:40:41 carnival, [laughter]
1:40:43 perverted carnival. Um,
1:40:47 yeah, and and that's, you know, that's
1:40:48 the thing. You know what's funny?
1:40:50 [clears throat] A lot of times, a lot of
1:40:52 times people are really pissed off about
1:40:55 AI. They're like, "Yeah, it's just the
1:40:57 world's greatest plagiarism machine.
1:40:58 You're stealing from the artist." You
1:41:00 know, they're all just all pissed off.
1:41:03 And I'm like, are we are are you cool
1:41:07 with um
1:41:10 like if someone uses AI to cure cancer
1:41:12 or autoimmune disease, you cool with
1:41:14 that? Oh, yeah, that's fine. Okay. So,
1:41:17 it's the same thing like all of the the
1:41:20 science advancements that was all based
1:41:22 on papers that scientists wrote that,
1:41:25 you know, you have to pay for. So, it's
1:41:27 it's it's literally the exact same
1:41:30 thing, right? that as as you're bitching
1:41:33 about over here, but you you want it
1:41:35 over here. You know, my my argument is
1:41:39 with how these things have been trained
1:41:42 is if if OpenAI or any of these labs had
1:41:47 asked for permission, everyone would
1:41:50 have said no. They'd have never gotten
1:41:52 permission
1:41:56 because they're Silicon Valley. They're
1:41:58 like, "Fuck it. Let's break it first and
1:42:00 then let people sue us." and that's what
1:42:01 they're doing. And so all those lawsuits
1:42:03 are going to happen. All that stuff's
1:42:05 going to normalize over time just like
1:42:07 Sampling did with hip-hop music in the
1:42:10 80s. Um it it was a travesty at first
1:42:13 and it wasn't real music and they're
1:42:15 stealing from us and all that stuff and
1:42:17 they worked it out. So the same thing's
1:42:18 going to happen here with the with the
1:42:20 intellectual property.
1:42:22 But what this is is this this this is
1:42:24 literally we have figured out as a
1:42:27 species
1:42:30 how to condense knowledge into instant
1:42:34 access and intelligence into instant
1:42:36 access. Um
1:42:39 why would you not at least be interested
1:42:41 in understanding what it makes possible?
1:42:44 But I think I think medical
1:42:46 breakthroughs are going to be massive.
1:42:48 And and you know what's fascinating is
1:42:53 I showed two weeks ago I showed a couple
1:42:56 of videos. One was a 60 Minutes
1:42:59 a 60 Minutes piece on a high school in
1:43:03 Georgia that have a special
1:43:07 uh science class that that people
1:43:10 literally move from all over the country
1:43:12 to get their kids into this high school
1:43:14 to have a shot at being one of the 10
1:43:16 kids that makes it into this program.
1:43:19 These kids came up with using crisper
1:43:23 technology,
1:43:24 DNA gene editing technology,
1:43:28 they came up with a a test for Lyme
1:43:30 disease that is effective within two
1:43:33 days of being bitten. And they think
1:43:36 it's effective enough that they're going
1:43:38 to actually um turn it from a a
1:43:40 diagnosis tool into a treatment tool.
1:43:42 They're in high school. Um, and there
1:43:44 was another story of a kid who was 17
1:43:47 that did some other remarkable thing.
1:43:50 I think that we're going to start to see
1:43:52 breakthroughs
1:43:54 from people who are passionate about
1:43:57 something like you with autoimmune
1:44:00 disease
1:44:02 because you're focusing this new tool on
1:44:05 the thing that you're passionate about.
1:44:07 This is the the AI salon mastermind
1:44:10 practice.
1:44:12 The whole idea of it is ah instead of us
1:44:16 fighting against AI what if what if just
1:44:19 as a possibility
1:44:23 we say the most important component in
1:44:27 the equation is the human being
1:44:30 and it's really you
1:44:32 you're the most important component in
1:44:35 AI
1:44:38 and then you start to ask yourself okay
1:44:40 if I've got this tool where I can do
1:44:41 anything. What do I choose to do? Well,
1:44:45 I don't know. Like, you're the only one
1:44:47 that can answer that. So, the things
1:44:50 that you're passionate about, the thing
1:44:51 the change that you want to make in the
1:44:53 world, the thing that you want to solve,
1:44:55 what you can now do is retire the idea
1:44:59 that you don't have the smarts or the
1:45:01 knowledge or the resources to be able to
1:45:03 make a difference in that area. You can
1:45:05 let that go.
1:45:07 That puts a lot of pressure back on you
1:45:09 to know what the [ __ ] you want to do.
1:45:13 But that's the world we live in. Ending
1:45:15 on a high note. What is that? Oh, okay.
1:45:18 I don't even know what that is. Let me
1:45:19 go click on I got something to click on
1:45:22 from producer Brandon here.
1:45:27 This is awesome.
1:45:29 Is this live?
1:45:31 It is.
1:45:33 Holy [ __ ] Okay. So, I want you to I I
1:45:37 want you all to go to the Apple App
1:45:41 Store if you are if you are an Apple
1:45:44 um if you're an iPhone owner.
1:45:50 So, Side Hustle Mimi in here. So, okay.
1:45:54 So, the thing that I just said, remember
1:45:56 I said you you can shed the idea that
1:45:58 you can't do something.
1:46:00 So, Side Hustle Mimi, no Emmy,
1:46:04 um, is not a programmer.
1:46:06 She's not a programmer. She doesn't
1:46:09 program. She doesn't write iPhone
1:46:12 applications. And yet, Koke Cuties,
1:46:16 CoQi, Cuties, Cute Puerto Rican Frog
1:46:20 Stickers, she made an app that let you
1:46:23 get all these cute little stickers.
1:46:26 Okay,
1:46:29 this is I [laughter] wanted to tell you
1:46:30 sooner, but I was putting up my tree.
1:46:32 So, first of all, congratulations. Um,
1:46:36 second of all, for Sonia in here and for
1:46:39 all of you who are like, why did this AI
1:46:40 stuff? Who is this crazy person talking
1:46:44 about AI as if it's an optimistic
1:46:47 [laughter] as if it might make a
1:46:49 difference in our lives? Here is an
1:46:51 example of a human being
1:46:55 that said,"I
1:46:57 want to put some joy in the world and I
1:46:59 want to celebrate my culture and my
1:47:01 heritage."
1:47:03 And you know what would be cool and and
1:47:07 where she started was she started with
1:47:10 making an app to help people I think
1:47:12 with mental health if I'm if if I'm
1:47:14 recalling that correctly. And what she
1:47:16 came up against is mental health stuff
1:47:19 is highly regulated. So you can't just
1:47:22 make an app that gives advice and you
1:47:24 have to follow the regulations. So So
1:47:25 she hit a roadblock where she had to
1:47:27 deal with some stuff.
1:47:29 But she learned enough in in vibe coding
1:47:33 that first app that she thought, "Oh, I
1:47:35 have this idea." And so she taught
1:47:38 herself
1:47:39 how to not only make the app, but be
1:47:43 able to submit it to the Apple App
1:47:46 Store. Now, I've got my my company,
1:47:48 we've got an app in the App Store. It is
1:47:50 not a simple process to get something
1:47:52 into the App Store. You have to have
1:47:54 like these screens and you have to have
1:47:56 descriptions and you have to have
1:47:57 privacy policies and you have to like
1:47:59 all this [ __ ] right? You can't just
1:48:01 stick something up there. It's work.
1:48:05 And so she is now a a full So it's 99
1:48:10 cents. So here's what I would say. How
1:48:12 many people here? There's 27 people
1:48:14 here. Do me a favor. If you have an
1:48:16 iPhone, go buy this app. It's 99 cents.
1:48:22 Ah, I got rejected. Super bummed. And
1:48:24 then I resubmitted. And voila, there you
1:48:27 go. Go buy her app and go get some cute
1:48:30 Puerto Rican frog stickers to put into
1:48:33 your chats and however you use them. I
1:48:35 don't I'm so old I don't know how to use
1:48:36 stickers. I think I made some at some
1:48:39 point.
1:48:40 But how cool is that?
1:48:43 Congratulations.
1:48:46 This is the world we live in now.
1:48:48 Abracadabra. As I speak, I create. We
1:48:51 can literally talk things into
1:48:53 existence.
1:48:57 Well, what am I supposed to do? What
1:48:58 tool am I supposed to use? None of that
1:49:00 matters.
1:49:01 What matters is who are you?
1:49:05 What difference do you want to make in
1:49:06 the world?
1:49:09 No. Emmy said, "I want to make the world
1:49:11 a better place. I want to celebrate my
1:49:13 heritage. I think Puerto Rican frogs are
1:49:16 cute."
1:49:18 [laughter]
1:49:19 Right?
1:49:22 And now this is in the world,
1:49:25 not because of AI,
1:49:28 because of her.
1:49:31 It was her idea.
1:49:34 AI enabled her to do that, right?
1:49:38 AI AI was the conduit, the amplifier,
1:49:41 the amplifier of her ideas.
1:49:45 So anyway, that's the world we live in
1:49:48 now. And that's time. Yeah, it's we're
1:49:49 going to be time. Um, okay.
1:49:55 Thursday and Friday or no, Friday and
1:49:58 Saturday, AI festivists. I'll be here
1:50:00 tomorrow night at 8 o'clock. Come back
1:50:02 tomorrow night. Bring your friends,
1:50:03 bring your family. Um, we'll we'll do
1:50:06 another something tomorrow. And then
1:50:08 we'll take a couple of days off for
1:50:09 everyone to go celebrate and do what you
1:50:11 do. And then Friday at 9:00 a.m.
1:50:14 Pacific, festivist starts, baby, and the
1:50:18 marathon begins. All right. Side hustle
1:50:21 made me. Thank you. I could not have
1:50:22 done it without you and my friends here.
1:50:24 Yeah, this is absolutely a community
1:50:26 here, right?
1:50:28 And in fact, you know what, uh, Noami,
1:50:31 like it might be good at some point to
1:50:33 have you, um, do an LOL. Um, maybe you
1:50:37 should connect with Vicki and see if you
1:50:38 want to do an LOL on how you did this
1:50:42 because
1:50:44 I know that I could figure this out, but
1:50:47 you already have figured this out,
1:50:49 right? How to vibe code something, get
1:50:51 all these screens together, get all the
1:50:54 application together, submit it. Um,
1:50:56 you've done it now. I'm I'm really
1:50:58 really proud of you. That's awesome. It
1:50:59 it really is incredible. All right,
1:51:01 cool. Oh, my my LOL's in March already
1:51:04 scheduled. So, that goes back to our
1:51:06 cycle of AI readiness generously lead.
1:51:09 So, no played,
1:51:12 figured out how to do some stuff,
1:51:13 figured out some vibe coding, then
1:51:16 decided to create excellence. I'm going
1:51:19 to try to make an iPhone app. And she
1:51:21 did. And then she's like, now I'm going
1:51:23 to try to publish it to the app store.
1:51:26 Create excellence. and she did and she
1:51:28 succeeded and it's live. It's there
1:51:31 right now. And now she's moving on to
1:51:33 that third step of generously lead.
1:51:35 She's going to tell us what the hell she
1:51:36 did. That's the cycle of AI readiness,
1:51:41 right? She's establishing herself as
1:51:44 someone who's a critical thinker, a
1:51:45 creative thinker, and someone who can do
1:51:48 good work and is willing to share what
1:51:51 she learned along the way. That's the AI
1:51:54 salon Tik Tok question. What's an LOL?
1:51:57 An LOL is um a a program that we have
1:52:02 within the AI salon. LOL stands for
1:52:05 learn out loud. And a learn out loud is
1:52:08 anyone in the AI salon community can
1:52:11 teach anything they've learned. And so
1:52:14 Vicky Baptiste, who's a regular in here,
1:52:16 I'm pretty sure she's in here tonight.
1:52:18 She runs that program. So, if you reach
1:52:20 out to her, um, she'll put you on the
1:52:22 schedule and you can teach the community
1:52:26 something that you've learned. All
1:52:27 right, that's what it is. All right,
1:52:30 fantastic. Um, I'm out of here. Have
1:52:33 yourself a fantastic night, Sonia. Thank
1:52:36 you for your questions and enthusiasm
1:52:38 and finding us. Um, tell your friends.
1:52:41 Um, tell everyone you can about Festivus
1:52:44 and all of you else do the same thing.
1:52:47 talk about festivists, get the word out
1:52:49 there. Let's get as many people signed
1:52:51 up as we can in the next three days and
1:52:53 let's kick some ass on Friday. All
1:52:56 right, LinkedIn blast. That would be
1:52:58 awesome. Yes, please. Um, and in fact,
1:53:01 you know, make sure go to the uh go to
1:53:04 the help us get the word out section of
1:53:06 the AI festivist website and you can see
1:53:08 swipe graphics there so you can make a
1:53:10 nice a nice post with the graphics and
1:53:12 everything. All right. And all the
1:53:13 information.
1:53:15 Beautiful. Beautiful, beautiful,
1:53:18 beautiful. That was a peppy night. I'm
1:53:20 excited. That was fun. I I covered some
1:53:22 stuff I haven't talked about in ages. I
1:53:23 like doing that. All right, everyone. Uh
1:53:25 I'm going to get out of here. Go deal
1:53:27 with my voice, which is now horse and
1:53:30 dry. I've got to get in shape for for
1:53:32 Friday and Saturday. [laughter]
1:53:35 All right, peace out. I'll see you then.