4/23/2025 -The Power of Digital Twins: How AI Can Transform Personal Expression and Creativity

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0:02 [Music]
0:34 See the hills
0:37 white
0:39 sway. Whistle of the train. Train echoes
0:44 through the
0:47 day. People made you greet you with a
0:51 line. Nothing ever seems to change.
0:55 [Music]
0:56 Sto each unique and strange
1:01 [Music]
1:40 Hello. Hello.
1:44 [Music]
2:07 Freedom came my way that
2:10 [Music]
2:14 night just like a jet. that play in and
2:18 out
2:20 sight. I was hauling ass at a million
2:24 miles and I was wondering how hard out
2:31 here when they came into the station.
2:39 They said I was bad beyond
2:44 repair, but I got no qualms with my
2:50 situation. Say here I
2:55 [Music]
3:01 am. Say Sheree Sheree Sheree won't you
3:06 dare
3:07 to say Sheree Sheree Sheree won't you
3:12 dare
3:13 to say Sheree Sheree
3:18 [Music]
3:21 Shereeh yeah leave a message at your
3:25 number
3:28 please take a time to want to satisfy
3:35 Take all these old fantasies, sell them
3:38 care of
3:40 [Music]
3:43 me. All right, happy Wednesday,
3:46 everybody. Um, I got the scratched
3:49 cornea thing again tonight. If you don't
3:50 know that, doesn't really matter, but I
3:53 can't look at the screen very good. One
3:55 eye's blurry, feels like
3:57 [ __ ] So, I'm probably going to be
3:59 cranky tonight.
4:03 which could make for good good Tik Tok
4:08 live. Side hustle Mimi back in the
4:11 house. Good to see you. Good to see you.
4:14 Good to see you. All right, what do we
4:16 got going over here? We're a mess. We're
4:19 a mess for Tik Tok, but you know,
4:22 they're used to it. Those Tik Tockers,
4:24 they're a robust
4:26 bunch, you know.
4:31 They're like, "Is our platform going to
4:33 cease to
4:35 exist?" Yeah, we'll just keep making
4:38 [Laughter]
4:43 content. Try sunglasses. They might help
4:45 with your eyes. Yeah, I was thinking
4:47 about
4:55 that. But I can also just wax poetic. We
4:58 can just talk about champion in his
5:00 cheese. I know he's singing pretty good,
5:02 right?
5:04 [Music]
5:16 There's been something, baby, you've
5:18 been trying to
5:21 say for an age. And it seems I don't
5:24 know
5:27 how with past and a future now
5:30 surrounding
5:33 me. Surrender to whatever she throw can
5:36 be found.
5:39 [Music]
5:40 There's been a little
5:42 trouble since you came to my
5:49 rescue. If you like all of the rest, I
5:53 would have quit you long ago, but I
5:56 couldn't do
5:59 [Music]
6:00 that. Oh, tell me
6:02 now why I never went too well.
6:08 Make a man crazy, make him cold as
6:12 [Music]
6:13 hell. I know woman that you wish me
6:18 well. But in spite of each trying, still
6:21 going to have to find my own way
6:26 through. Yeah.
6:35 Woohoo! Life morning, my dream
6:41 remains. Hanging in the burnt fields of
6:44 my
6:46 memory. Tired a chorus of your
6:53 disdain. The dead left behind me.
6:58 I'm searching solutions on a
7:01 double on this twoton telephone
7:07 home. My friend says you ain't got no
7:10 real
7:11 troubles. Just too many choices that you
7:14 left
7:18 undone. My friend says put an action to
7:21 those words. Put an action to those
7:24 words.
7:29 Zo, it just hit me. Those Martin Sex
7:33 Ston lyrics are basically the Tony
7:36 Robbins
7:39 course. You ain't got no real troubles.
7:42 Just too many choices that you left
7:45 undone. Wait,
7:48 wait. You ain't got no real troubles.
7:51 There's too many choices that you left
7:54 [Music]
7:57 undone. My friend says, "Put an action
8:00 to those words." Put an action to those
8:03 words. It'll all come. That's Tony
8:06 Robbins right there. Figure out the [ __ ]
8:09 you ain't taking action on. Break your
8:11 pattern. Take some [ __ ] action. There
8:13 you go. I just saved you 1,200 bucks.
8:20 Oh
8:24 yeah. All right. If you are new here, I
8:28 feel like you and Jack Black would get
8:29 along really good. I like him. I think
8:31 he's good. I mean, there's something
8:32 nice about the combination of down to
8:36 earth and ridiculous that Yeah, I've
8:38 always kind of leaned into
8:40 that. You know, it it depends who your
8:42 comedy heroes were. you know, mine mine
8:45 was, you know, Robin Williams, Steve
8:47 Martin, you know, smart, talented people
8:50 that are willing to just do stupid
8:54 [ __ ] So, hence I'm 59, still doing
8:58 stupid
9:00 [ __ ] You're a beautiful person. A thank
9:02 you very much. That's very sweet. I
9:04 appreciate that a lot.
9:09 Um, yeah, it was funny. Today I was uh
9:12 this is not not related to the beautiful
9:14 person thing, but
9:15 um but it just reminded me I was I was
9:19 putting some time in just looking at the
9:22 Lord Digital gods from the channel here.
9:25 Uh one of the mods and and just an
9:27 all-around great guy who's been using AI
9:30 to to take the the YouTube videos of
9:34 these live streams and he makes titles
9:36 and descriptions for them. and he sent
9:38 me this 12-page document of like all the
9:40 titles and the publish dates of every
9:44 video that I've done on these lives. And
9:46 it's there's like 545 of them, 1100
9:49 hours of content. And so I'm using chat
9:52 GPT to help me like sort through it and
9:54 and like write a piece about, you know,
9:58 I've been doing this for two years now
9:59 and these videos have become like this
10:02 kind of historical journey and sort of
10:04 going back and looking at them is
10:05 actually not a bad exercise. So um so
10:09 that's kind of fun. Only
10:15 1,100 for saving me 1,200 bucks. There
10:19 you go.
10:23 Put an Put an action to those words. Put
10:26 an action to those words. It'll all
10:29 [Music]
10:34 come. Women and wife never went too
10:40 well. Make a man crazy, make him cold as
10:45 hell. I know woman that you wish me
10:50 well, but it's spotty shrine. Still
10:53 going to have to find my own way
10:56 through. Um, so do me a favor since I
10:59 can't really demo [ __ ] I I'll I'll
11:01 maybe do it. My my eyes are are sort of
11:04 cooling out. Check out
11:08 youwear.so. All right, I might do that.
11:10 I
11:11 can't I'm not a fan of checking out
11:13 stuff I've never heard of live on the
11:15 show just cuz I don't know what the [ __ ]
11:17 I'm looking at. But I will check stuff
11:19 out like that.
11:21 Um I actually asked 03 what I was
11:24 consistently not doing that I should and
11:28 what I should drop. Interesting. Gave me
11:30 a lot of insight. That's actually kind
11:32 of a
11:34 cool. What is something I'm consistently
11:37 not doing but
11:41 should uh uh uh
11:46 uh let's do it with a reasoning engine.
11:51 [Music]
11:53 Um, what is something
11:56 I'm consistently not doing but should
12:00 based on everything that you know about
12:11 me? Okay, cool. Brandon got
12:15 it. Thinking. We're thinking. for
12:21 thinking. Would you mind exploring how
12:24 to create GPT personas? You mentioned
12:26 that the other day. Yeah, I'm happy to
12:29 do that. I I'll talk about it a bit
12:31 first, too. It strikes me that you're
12:35 deeply immersed in creating, whether
12:37 it's your musical, the AI salon, your
12:39 podcast, or the endless stream of Tik
12:42 Tok lives.
12:45 I I hate being called out by chat GBT,
12:48 you
12:51 [ __ ] But you personally let your
12:54 recharge time slip away. Your love of
12:56 fly fishing. You've expressed a
12:58 fascination with analog raw gritty
13:00 processes and you've shown interest in
13:02 self-help practices. Yet you haven't
13:04 made room on your calendar for any of
13:07 it. I'm too
13:09 busy. Why this matters? Yeah, I know why
13:12 it matters. Okay. How to start? Block,
13:16 unplug, and recharge time. Two or three
13:19 hours a month. That's not a bad idea.
13:21 Embed a weekly analog
13:25 ritual that I have more of a problem of.
13:27 Maybe like taking a walk with the dog. I
13:29 was doing those uh walking talks for a
13:31 while. Those were pretty good, but it
13:33 just got to be I was I was just it was
13:37 like adding stress to what should have
13:39 been
13:40 relaxing. Treated as non-negotiable.
13:43 Yeah, about
13:48 that. Uh oh, the new the new 03 and 04
13:52 limit increases are fantastic. Yeah,
13:55 listen, all of the whenever new [ __ ]
13:58 comes out, I always see a lot of of of
14:01 like, you know, hand ringing about,
14:03 well, free users can't use it and plus
14:06 users should get more. For the most
14:10 part, every single thing that's come out
14:12 has has decreased 10x in cost over the
14:17 course of a year. So, generally what
14:19 that means is it your access to it will
14:21 increase over the course of a year. So,
14:23 even if something's out and you don't
14:24 have access to it, that'll likely
14:26 change. Um, damn, I just asked ChatGpt
14:29 that question and it remembers too well.
14:32 I know. So, if you don't know this, uh,
14:36 about three weeks ago,
14:38 ChatGpt added effectively long-term
14:41 memory. So, everything that you've
14:43 talked about in the past, it knows. And
14:47 so, when you ask it to write in your
14:49 style, it it knows it's written in your
14:51 style before, every time that you've
14:52 given it feedback like that's too
14:55 structured or not funny enough or
14:56 whatever it is. So, like today when I
14:59 had it do a draft of a LinkedIn uh post
15:03 uh it and then I said, you know, make
15:05 it, you know, write it in my style. It
15:07 didn't suck. Like it was at least in the
15:11 [Music]
15:20 neighborhood. All
15:22 right. Would you mind exploring? Yeah.
15:25 Uh GPT personas. Okay. So, let me talk
15:27 about them
15:28 first. All right.
15:34 Um, so I've called these things digital
15:39 twins. Um, now in content evolution,
15:41 we're calling them digital advisors.
15:43 That's because that's kind of more like
15:44 what they are. They're not really a
15:46 digital twin, but they're a really good
15:50 uh
15:51 wait Tik Tok thing. It keeps forgetting.
15:54 How do I keep it for from forgetting?
15:57 Okay. The thing about the
16:02 memory thing about the memory is this. I
16:04 have experienced that too. Sometimes
16:07 like I've had it say I've I've had it do
16:09 like write me a bunch of things that
16:11 I've said right about whatever topic and
16:14 then it just makes [ __ ] up. It's got
16:16 nothing to do with what I've said. So
16:18 one thing to do when it does that is
16:20 scold it, right? Treat it like a
16:22 seven-year-old. Okay, chat GBT, you
16:26 know, you're just making [ __ ] up now.
16:28 You know, I want this on my actual, you
16:29 know, dig deeper. You know, look in my
16:31 past, you know, go back to the
16:33 beginning, whatever it might be. So,
16:34 that's a way to do
16:36 it. The other way to do it, let me
16:39 Brandon, if you could pop up this screen
16:40 share again, let me show you one other
16:42 thing that I think is is not painfully
16:46 obvious.
16:48 Um, if you go to your
16:52 um the upper right hand corner here, you
16:55 Oh, wait. Hang on. Tik Tok's not seeing
16:57 the hell I'm doing. And you're like,
16:59 "What's he talking about? We don't see
17:01 nothing." But if you click on your uh
17:04 your name in the upper right hand
17:06 corner, your account, and then go to
17:09 settings, and then in settings, go to
17:12 personalization. There's now two
17:14 different kinds of memory. There's saved
17:16 memories and then there's reference your
17:19 chat history. One thing you can do is
17:21 just confirm that those are both turned
17:23 on. Right? If they're turned on and it's
17:25 still forgetting, that's just sort of
17:27 the nature of the tool right now. It's,
17:29 you know, we still live in janky times,
17:31 right? The tool's still janky. But if
17:34 there are particular things you want it
17:36 to remember about you when you're in
17:39 chat GPT, you can say, "Hey, remember
17:42 that you know I was a professional ice
17:45 skater or whatever it might be." And
17:47 then you can go in and you can manage
17:49 these memories, right? So you can go
17:52 through here and you can call ones. Like
17:55 one of my challenges is because I do m
17:57 so much stuff on the live like it thinks
18:00 that I'm really interested in stuff that
18:02 maybe someone in here asked me to
18:03 explore. Um so you can go in and you can
18:06 you can delete and cull ones that you
18:09 don't want. Um but you can also just
18:12 explicitly tell chat GBT, hey I want you
18:15 to remember X and it will write it into
18:17 that saved memory list. And those it
18:20 tends to remember better than
18:22 referencing your entire chat history. So
18:24 that may help a little bit. Tik Tok pin
18:26 chat GPT told me my middle name is
18:28 James.
18:31 Wrong. It's
18:33 of of James. That's
18:38 good. Um okay, back to digital twins and
18:41 digital advisors and uh let's see. Sea
18:44 slug of
18:45 doom.
18:49 Um let's see. Let's see. Let me go back
18:53 to that.
18:57 Okay. Where to begin with
19:05 this? The first time I heard about this
19:10 idea was Brad Perkins, who used to be
19:13 one of the organizers at the AI salon.
19:15 He's since gone down to Argentina and
19:17 he's entrepreneuring in South America.
19:23 Um he
19:26 um he came to a salon one night and he
19:29 was talking about um he had a really
19:32 amazing brainstorming session where he
19:35 basically just wrote a prompt where he
19:38 sort of bulleted out his
19:40 personality. So like a way that you can
19:43 do this is you can just explicitly sit
19:46 down at you know in a chat session and
19:49 say here's who I am blah blah blah blah
19:51 blah right
19:54 um and he said it was amazing because
19:56 the the he it was like he was
19:58 brainstorming with himself it had a
19:59 similar point of view you could also do
20:02 this where you flip it the other way
20:03 where you you know you could say to chat
20:05 GBT here's who I am I want you to take
20:07 the counter point of view to that so I'm
20:10 going to tell you ideas and then I want
20:12 you to counter it. Um, it can be really
20:15 valuable. You can also
20:18 um get responses from digital advisors
20:23 that are famous people. What would Steve
20:25 Jobs think about this? What would
20:27 Aristotle think about this? Right? What
20:29 would, I don't
20:30 know, uh, Kevin Hart think about this?
20:33 What would Tom Seagura think about this?
20:35 And if it's famous people like that, it
20:37 it knows enough about them that it can
20:39 give you a point of
20:41 view. Um, so that's super valuable. So
20:45 now you start to get into
20:48 um you you want to create a digital
20:51 twin. You want to create a digital
20:52 representation of yourself. It's funny,
20:53 Brandon just sent me um uh an article
20:57 from Google talking about, you know,
20:59 digital ghosts, right? and and you know,
21:02 are we going to be using AI to
21:05 um you know, interact with loved ones
21:09 past or things like that? And I think
21:10 the answer is yes. In fact, I'm meeting
21:12 with someone Saturday uh that's working
21:14 on a project that's explicitly that. And
21:16 I think there's something potentially
21:17 really valuable there.
21:20 Um
21:23 okay, so here's what here's what we
21:26 learned. We we've been we've been making
21:28 these digital advisors at Content
21:30 Evolution for the past year or so. And
21:32 I'll give you a little bit about the
21:33 history of how it started because
21:35 there's lots of ways that you can do it.
21:37 But in general, what you're doing for
21:40 right now that there may be other
21:42 technologies that kind of expand this
21:44 out in the future, but right now the
21:47 simplest way to do it is to make a
21:48 custom GPT, right? And a custom GPT is
21:53 is essentially not much more than a than
21:56 a a custom prompt that you kind of lock
21:58 down, right? So, uh, go ahead and share
22:01 my screen for a second. I'm not going to
22:03 show you how to make an entire one, but
22:04 I'll show you where to where to start.
22:06 So, in your sidebar, if you've never
22:08 made a custom GPT before, you've got,
22:11 you know, any GPTs that you've you've
22:13 bookmarked are are in this list. But
22:16 down at the bottom here, it says explore
22:18 GPTs, right? right here. And if you
22:21 click on that, in the upper right hand
22:23 corner, you can say create. And that'll
22:26 pop you into this little pane where on
22:28 the left you are describing, you know,
22:32 what your GPT is going to be about. And
22:34 then on the right, you get to test
22:36 it. And there's a couple of ways to do
22:38 this. You can on on this panel on the
22:40 configure panel, you can like name it,
22:42 give it a description, explicitly, write
22:44 out your prompt. You can, you know, give
22:47 it access to tools like code
22:49 interpreter, you know, image generation,
22:51 all that sort of stuff. Or you can just
22:53 go to this create
22:55 tab right here and that you just tell it
22:59 what you want it to do. But for the for
23:01 the purposes of the of what I'm going to
23:04 talk about, it would probably make more
23:06 sense to do it in the configure tab.
23:08 Okay.
23:10 Then there's a there's a philosophical
23:15 um there's a philosophical choice that
23:18 you get to make when you do these
23:22 things. And and it's kind of cool and
23:25 and the choice is like what do you want
23:27 the personality of
23:29 your digital twin to be? Because if I
23:33 took the Kyle that shows up at these
23:35 lives that's irreverent and cusses a lot
23:38 and makes fun of people and does all
23:39 that [ __ ] that would be a very
23:41 different digital twin that if that than
23:43 if I'm answering, you know, an interview
23:46 set of questions about how professional
23:48 I am or if I just scrape my LinkedIn
23:50 profile for work history, I could make a
23:53 digital twin out of that and chat GPT is
23:56 good enough to kind of infer something
23:57 out of it. But all of those have very
23:59 different personalities. So the history
24:02 of where we started these things with
24:04 content evolution was the initial idea
24:08 was we w we wanted to create a GPT that
24:11 made it easy. So content evolution is
24:14 like a a a federation of a number of
24:18 different marketing
24:19 organizations and one of the challenges
24:22 of the group is if if someone comes in
24:26 and says hey I want to work I have this
24:28 problem to solve who within content
24:30 evolution would be the best person to
24:32 work with that's not always easy to
24:34 determine so we thought could we make a
24:37 discovery tool using chat GPT where we
24:40 would scrape LinkedIn for for the
24:43 different content evolution members and
24:45 put that data in into a uh into a
24:49 GPT and then
24:52 um and then it would help us discover
24:55 who those people are.
24:59 Um two things happened. One
25:04 was LinkedIn doesn't make it easy to get
25:06 that data. So you actually have to go
25:09 scrape it which is against their terms
25:10 of service. So, we're trying to build
25:12 this, you know, thing that is, you know,
25:15 at least commercially
25:16 usable and it's not really easy to do
25:21 and it's kind of problematic. So, so, so
25:25 we started talking about it and the more
25:26 we talked about it, what we realized was
25:28 that LinkedIn as a data source is very,
25:34 very thin, right? It's only historical
25:37 looking. Like, here's the [ __ ] Kyle did
25:39 in his past.
25:41 I mean, if I'm consistently writing
25:43 articles, it might have my current sort
25:46 of point of view and tone of voice, but
25:48 a lot of people don't use LinkedIn as a
25:50 publishing
25:52 platform. So, it's just not
25:55 great. And it also doesn't capture
25:59 things like, well, what are your
26:00 cultural cultural influences? How do you
26:03 solve problems? like all the all the
26:05 kinds of stuff
26:06 that make a person who they are weren't
26:09 in there. So what we ended up doing, and
26:12 this is what I would recommend if you
26:14 want to do a digital
26:16 twin, there's some
26:19 pre-work. And so the pre-work looks like
26:22 this.
26:24 go to chat GPT and have ChatGpt help you
26:29 design a structured interview like
26:32 categorized prompting
26:35 questions that you will
26:37 answer and it's really good at that. I
26:40 mean remember chat GPT has been trained
26:43 on everything. So every structured
26:45 interview that's ever been put on the
26:46 internet is in the training data. So, if
26:49 you say, "I want to create uh a
26:52 structured interview of, I don't know,
26:54 20 to 25 questions, right? The the 20
26:57 questions thing, right? Ask me 20
26:59 questions." Um, and I want to make sure
27:01 that they capture who I am today, how I
27:03 got here, what my hopes and dreams are
27:05 for the future, right? I want to design
27:07 of a a set of questions that's going to
27:10 capture my worldview. And then you can
27:13 also give it flavor. And I wanted to
27:15 capture my sense of humor or I wanted to
27:17 capture um I wanted to really focus on
27:20 my problem solving ability. So you can
27:22 kind of steer. It's funny when I when I
27:25 talk about doing these structured
27:26 interviews a lot of times people are
27:28 like can I have the
27:30 questions? I could give them to you but
27:32 it actually doesn't serve you right. You
27:36 get to design what you want those
27:38 questions to elicit. Chat GPT is really
27:41 good at doing it. So you make that set
27:42 of questions and then you edit them. You
27:45 go in and you say, "Oh no, you know, you
27:47 have too many questions in here about my
27:49 childhood and not enough about what I'm
27:50 doing now." Whatever it might be. So
27:52 just modify modify modify and then get
27:54 yourself a little set of questions.
27:56 Paint mo just export your own LinkedIn
27:58 data. You don't need to scrape everyone
28:00 else's for your own uses. Correct. But
28:02 what we were trying to do was do it for
28:04 a bunch of people and it's a bunch of
28:07 people that aren't going to necessarily
28:08 we so so paint. Yes. for your for
28:12 yourself individually, you can do that.
28:14 And that could be one of your data
28:15 sources is export your LinkedIn data.
28:18 Um, use that as an input source. But but
28:20 this interview is really important. I'll
28:22 tell you why in a second. Um, but but we
28:25 had we had 30 people who were not very
28:28 responsive when we said, "Here's how you
28:30 export your LinkedIn data." So then we
28:32 were like, "Maybe we go scrape it." And
28:34 then it just it ended up being a pain in
28:36 the ass, but we ended up not using it.
28:38 And I I'll tell you why in a second.
28:41 Okay. So, we cra came up with this
28:44 structured interview and we made the
28:48 conscious choice which I'm really glad
28:49 we did that we for all of the content
28:54 evolution digital
28:56 advisors. We wanted a the identical data
29:00 source for each one of them because we
29:02 wanted to be able to write a single
29:04 prompt that we could migrate across
29:06 different people and have it work for
29:09 them. and and we wanted to see how
29:11 different they were, right? We wanted to
29:12 see if this worked. So, so then we we
29:16 sent out a thing and we said, "Let's
29:17 let's do interviews with people and and
29:20 then when we sent out the questions,
29:23 some people rather than being
29:24 interviewed wrote out their answers and
29:27 then other people got interviewed and
29:31 then we built the GPTs." And what we
29:34 learned was that the people that wrote
29:37 out their answers, their digital twins
29:40 sucked. They were just bad. They weren't
29:43 good. They didn't give good answers.
29:45 They made [ __ ] up. They hallucinated.
29:47 They didn't have a particular tone of
29:48 voice. Why is that? Well, because we
29:51 don't talk like we write, right? It's
29:54 it's the very rare person that that
29:56 writes the way they talk. Um, and it
30:00 just doesn't capture the personality of
30:02 who the person is. So, what I would
30:04 strongly recommend
30:06 is generate this set of questions.
30:11 have someone that you know and trust
30:14 interview you. Like get on a Zoom call,
30:16 turn on record transcription. Like you
30:18 can just do it on Google Meet, you know,
30:20 record this call or Zoom, whatever it
30:24 doesn't matter. Take bring in one of the
30:26 notetakers and then just have the person
30:28 ask you the questions. And ideally, if
30:31 they know you well, if you're getting
30:33 kind of skimpy on an answer, you're
30:35 getting stingy, um, they know you well
30:38 enough to go, "Oh, tell that story about
30:40 when you, you know, adopted the dog,
30:43 whatever it is, and you tell that story
30:46 and then the transcript of that
30:47 interview, you don't need to edit it at
30:50 all." like like one one of the things
30:52 that happened within content evolution
30:54 is some of the more OCD anal anal
30:57 retentive types were like I'm gonna go
30:59 you know masteredit this thing and those
31:03 people were incredibly
31:05 frustrated that chat GPT didn't just
31:09 vomit out exactly what they wrote in
31:11 their interview right they they were
31:14 expecting computers to act like
31:16 computers have always acted which is you
31:18 put in the data and it comes out in this
31:20 predictable way. That's not how large
31:23 language models work, right? Like like a
31:26 lot of the early conversations were,
31:27 well, it it said this thing and I never
31:29 said that. All right. Well, that's
31:33 that's the nature of the [ __ ] tool,
31:35 right? Um, and so it took a while to
31:38 sort of get that that the purpose of
31:40 this this is not a rag document. So, if
31:42 you've heard the term rag, it mean it
31:45 stands for retrieval augmented
31:47 generation. This interview is not
31:49 intended for that. There there's
31:51 probably a strategy where you could do
31:53 that, but this is more intended of like
31:55 this is a document that kind of captures
31:57 who I am. And then what you do is you
31:59 upload the PDF or the text version of
32:02 that transcript as your data source. And
32:05 then you start writing your prompt.
32:07 Right? I want you to act as a digital
32:10 twin, you know, based on the interview
32:12 supplied here. And you know, I want you
32:14 to respond in the following ways. and I
32:16 want you to be helpful and I want you to
32:18 answer questions and I want you to you
32:20 you know um one of the things we put in
32:23 our digital twins is at a good stopping
32:25 point in the conversation
32:27 um put it put essentially put an ad in
32:30 there let people know how they can get
32:32 in touch with us if they want to hire
32:34 someone right and and we put in um we
32:38 put into the interview uh like uh
32:41 structured data like here's your website
32:45 here's your email address, what's your
32:47 preferred um way to reach out to the
32:50 person? So, so you just kind of play
32:52 around with that prompt until it gives
32:53 you what you want and that's it. Um, but
32:56 definitely record the interview and then
32:59 what you'll end up with is something
33:01 that is very very likely to be a good
33:04 brainstorming partner, something that
33:06 you can do drafts of LinkedIn articles
33:08 and it will sound more like you right
33:10 out of the gate. Um, it'll have your
33:12 world view embedded in it. So you could
33:15 say, "Hey, here's this, you know,
33:17 political thing going on in the world,
33:19 you know, digital twin. What do you
33:21 think about that?" Or, "What's the
33:22 opposite of what I think about that?"
33:24 Right? And it'll it'll be pretty good at
33:26 that. All
33:32 right. Silly question. Does each chat
33:34 GPT session need to be saved as a PDF?
33:37 Does chat GPT limit inputs?
33:43 Um, if Well, it's a really good
33:47 question, Becky. So,
33:49 there's so in
33:51 general, it it's it's not a simple
33:54 answer anymore. In general, each chat is
33:57 kind of a hermetically sealed
34:00 conversation in
34:02 general, but the rules are changing on
34:04 that for a couple of reasons. One is now
34:07 that chat GPT can reference your past
34:10 chat histories, you can ask it about
34:13 conversations you had three or four
34:15 weeks or you know a year ago and it will
34:17 be able to reference those. As someone
34:19 pointed out here, it's not always great
34:21 at that. So it's a little
34:24 janky. Chat GPT also released something
34:28 called projects. So let me go and show
34:31 you where to find projects. Projects are
34:34 are smart. They're kind of like Notebook
34:36 LM. Um, if you could pop up my screen
34:39 share there, Brandon.
34:42 Um, if you scroll down below your
34:46 um, custom GPTs on the left, there's a
34:50 new section here called projects and you
34:54 can add a
34:55 project and then you can explicitly add.
34:59 So if I go into this project, you can
35:01 explicitly add chats, previous chats
35:05 into a project and you can also add
35:08 files to a project and you can also have
35:11 custom instructions for a project. So
35:15 you know maybe you've been doing maybe
35:17 you've had 20 different chats where
35:19 you've had kind of therapy sessions with
35:22 with you know your digital girlfriend or
35:25 boyfriend. um you could add all of those
35:29 therapy chats into a project and now
35:32 this project will have access to all
35:34 those things. So in general your your
35:37 your chats are hermetically sealed and
35:40 and yes there are limits to them. It's
35:41 called a context window and that you
35:44 know how sometimes when you're chatting
35:46 and it seems like it just forgot what
35:48 what you started the conversation as.
35:51 That's literally because it forgot the
35:53 beginning of the conversation. That's
35:54 your context window. They used to be
35:56 really small. Now they're getting
35:57 bigger. The latest and greatest from
36:02 Chat GPT, the 4.1 thing that's in the
36:05 API is a
36:06 million tokens, like 750,000 words,
36:09 which is a lot. So, so again, memory as
36:14 memory expands, it starts to mitigate
36:16 that limitation. Um, Tik Tok pin, but I
36:20 don't see it. Uh, I joined the AI salon,
36:22 Joe goes digital. Incredible work on the
36:24 website. Oh, that's awesome, Joe.
36:25 Terrific. Thank you. Welcome back and
36:28 glad you're here. Um, didn't you say
36:30 there was a YouTube thing as well? I saw
36:34 the the Tik Tok pin. Okay. MasterClass
36:37 is now offering AI twins of Mark Cuban,
36:40 Bill Nye. Oh, that's right. Yeah. For 10
36:43 bucks a month, MasterClass. So, this is
36:46 this is kind of smart. And and this is
36:49 where things start to head.
36:52 Think about what masterclass was
36:54 historically. They would go in and they
36:56 would spend, you know, 10 hours or
36:57 whatever it was how, you know,
36:59 interviewing Mark Cuban about being an
37:01 entrepreneur and then you would watch
37:03 that video. Well, they can take that
37:06 interview, turn that into the Mark Cuban
37:08 digital twin, and now you can just go up
37:10 ask Mark questions. And I don't know how
37:12 well they've done them, if they're doing
37:14 rag, where it actually pulls quotes from
37:16 the interview. Um, but this is a this is
37:19 going to be a very mainstream thing. And
37:21 what I'll tell you is this. If you put
37:24 in the time to make a digital advisor,
37:26 make a digital twin, it's going to serve
37:28 you
37:29 professionally, right? Because like all
37:32 of what I just talked about, I just gave
37:34 you like a year and a half of us just
37:36 like slamming our head against the wall
37:38 about what do these things actually
37:39 mean? What's of value? How would you use
37:42 them?
37:44 independent of creating a digital
37:46 advisor, a digital twin is when and how
37:49 do you use it? And I still don't know
37:52 the answer to that. Like sometimes I
37:54 forget that I've got a digital twin and
37:55 I'm I'm there going talk more like me.
37:57 Talk more like me. And I'm like, "Ah,
37:58 [ __ ] I got a digital twin." I'll log
38:01 into my digital twin one and and do the
38:04 same exercise and it's a lot
38:06 better. And then, you know, there's a
38:08 difference between are you
38:10 brainstorming? Are you refining
38:12 something? Do you want to counterpoint?
38:14 All that sort of stuff. And if you do
38:16 this with friends, if you do this with a
38:18 group of friends, you can create an
38:20 advisory board of other digital twins.
38:24 You can actually call custom GPTs into a
38:27 chat,
38:29 right? And you know have multiple points
38:34 of view from all your trusted
38:39 associates. Okay.
38:45 [Music]
38:50 Um, check Gary Marcus Twitter. Huge
38:53 scandal. Open AAI
38:56 cheating on the Arc AGI benchmark. Okay,
39:00 first of all, Gary
39:02 Marcus, he lives to [ __ ] all over uh,
39:06 OpenAI. I I I haven't read it yet, but I
39:09 he he's been talking about this for a
39:12 while
39:13 that if a large language model is
39:16 trained on a specific benchmark, it's
39:18 going to do really good at that
39:20 benchmark, right?
39:22 Um every company, every company making
39:25 these frontier models, I guarantee you
39:28 they're training to all the benchmarks.
39:30 I promise you. Because right now, here's
39:33 the deal. When Deepseek came out, right,
39:35 the Chinese the Chinese company that
39:37 came out and obliterated the
39:39 benchmarks, do you think that they were
39:41 not training against the
39:44 benchmarks? They came out and it it
39:47 tanked the stock market by $1.2
39:52 trillion. So, so I guarantee you that
39:56 every one of Now, if there's something
39:58 more scandalous than their training on
40:00 the benchmarks, then that I haven't
40:01 heard. But if it's Gary Marcus, what
40:03 that says to me is he's just finding a
40:05 way to [ __ ] about
40:07 it. Didn't we have a session on creating
40:10 digital twins? We've had a couple of
40:11 sessions on creating digital twins.
40:13 Yeah. In fact, you could probably go
40:16 back if you go back to the YouTube
40:18 channel. Okay, first of all, if you
40:20 haven't subscribed to the YouTube
40:21 channel, YouTube channel, what are you
40:23 doing with your life? Get your [ __ ]
40:26 together. Learning lab-ai on YouTube.
40:29 All
40:30 right, Gary on X today. OpenAI's wildly
40:34 hyped December 3 Arc demo can't readily
40:36 be replicated with the released model.
40:40 All right, that doesn't mean they
40:44 cheated. Like how how
40:49 he whatever model they demoed back in
40:54 December, how do we know that what we
40:56 have today is that? Like I just
40:58 whatever. He's such a negative Nelly.
41:00 Like I'm as positive about OpenAI as he
41:04 is negative about it. So that should
41:06 give you a
41:09 spectrum. We How to learn out loud on
41:11 creating digital twins with Cindy [ __ ]
41:13 So Oh, that's right. Okay. Pop up the
41:17 uh pop up the uh AI salon graphic there.
41:22 So for those of you that are new here,
41:24 go to the salon.ai.
41:27 AI. That's the AI salon. Joe Goes
41:29 Digital just said he joined and he said
41:31 he's really really happy with the
41:33 community. It's an amazing
41:36 community. In the past two months or so,
41:39 um Vicki has been spearheading these
41:41 things called LOLS, learn out louds. And
41:44 and one of the one of the imperatives of
41:47 the AI salon is what we call generous
41:50 leadership. And that is as people learn
41:52 [ __ ] they teach what they're learning.
41:54 So Cindy [ __ ] who's in content
41:56 evolution with me, she's one of the ones
41:58 that helped design how we build these
42:01 digital advisors. She did a learn out
42:03 loud on how to build digital advisors.
42:06 So all the [ __ ] I just talked about is
42:08 recorded in a hands-on how-to session by
42:11 Cindy [ __ ] So go join the AI salon. So
42:15 go to the salon.ai, AI, click join our
42:18 community and that's going to take you
42:20 to the community site where you actually
42:22 interact with people. Go in there,
42:25 follow the onboarding process. It's like
42:27 seven easy steps. Learn about what we're
42:29 about. Introduce
42:32 yourself and then go check out the
42:34 content that's in there. It's
42:36 amazing. Kyle, Kyle, I saved $700 in
42:39 lawyer fees using GPT in my USPTO patent
42:43 application. Yeah, awesome. Just make
42:45 sure when you're doing anything legal,
42:47 you're double triple checking that you
42:49 don't have, you know, cited artwork in
42:51 there that that it made up because it
42:53 will do that. But yeah, um I was I was
42:56 on a Twitter spaces a few weeks back and
42:59 there was a guy in there that was a Ivy
43:02 League like a Yale neurosurgeon and he
43:05 said because of chatbt he said 03 in
43:08 particular um and this was even before
43:11 the new one came out. This was the mini
43:13 models. He said um he's doing a patent
43:17 application a month because of chat GPT.
43:21 So yeah, it's it's good for that stuff.
43:24 Beautiful. Fantastic. Fantastic people.
43:28 Yeah, I'm taking an online course trying
43:30 to figure out my niche as well as my top
43:32 digital skills. So Vicki, I don't
43:37 feel take the course.
43:40 Don't put pressure on yourself that you
43:42 have to lock anything in or figure out
43:45 what your digital skills
43:47 are
43:51 because things are changing so fast and
43:55 and the tools are getting so capable
43:58 that you're going to be able to
44:01 essentially do anything you want to do.
44:03 The most important skills with where we
44:06 are with AI moving forward are going to
44:09 be critical thinking,
44:11 um, curation, taste,
44:15 judgment, strategic thinking. So, so
44:20 think less about how you execute stuff
44:24 and more about what impact you want to
44:26 have on the world. And listen, I know
44:28 that you're a very missiondriven person,
44:31 V Becky. So you already know the impact
44:34 you want to have on the world. I would
44:36 say stay up in that zone and just learn
44:40 enough of the stuff down here to like
44:42 you know cover the jankiness of the
44:44 current tools but assume that this is
44:47 going to get better and better better
44:48 down on the execution level. Your only
44:51 job should be you know what do we what
44:53 do I want to be producing in the world
44:55 and what impact do I want to be having
44:57 and then you know learn some skills
44:58 along the way because the tools still
45:01 kind of suck.
45:02 All
45:04 right. Um, but yeah, but like you've got
45:08 like what a lot of people don't have is
45:10 like if you ask them a question like
45:12 what change do you want to, you know,
45:14 see in the world, you know, who who do
45:16 you want to, you know, what's the stand
45:18 you want to take for for how you want to
45:20 impact the world? A lot of people don't
45:22 have an answer for
45:23 that. And that's quite frankly the most
45:26 important thing and it's the hardest
45:27 thing. So, if you've got clarity on
45:30 that, I think you're 90% of the way
45:31 there. Just you need to be a little bit
45:33 patient for the tools to catch up. Uh
45:38 [Music]
45:51 [Music]
45:52 [Applause]
45:55 Winston, thank you so much for the hot
45:58 peppers. I've answered my calling
46:01 calling. I've got it pinned. I know.
46:03 That's what I'm saying. You got You're
46:04 like You're like way ahead of the world,
46:08 right? Like what are the blessings in in
46:10 the uh the trials and tribulations we go
46:12 through in life, Becky? Um you know,
46:15 you're prepared. you've got some clarity
46:16 around that that a lot of people don't.
46:18 And I honest to God, I think
46:22 that one of the biggest risks of AI is
46:25 not that the robots are going to kill
46:27 us. It's that the robots are going to do
46:30 the thing that used to give us
46:35 purpose. And if you
46:38 don't, those people that don't
46:42 proactively go after defining that
46:46 purpose, if the AI takes away the tasks
46:50 that they did that that gave them
46:52 purpose, then you're going to have a
46:54 bunch of people that lack purpose. And
46:55 the minute you lack purpose in life,
46:58 [ __ ] doesn't go well,
47:00 right? So, so I think that's actually
47:03 the biggest risk. Tik Tok pin. Uh,
47:06 nothing pinned right
47:11 now. Neilio's wife, we seem to be locked
47:14 into the idea of courses and degrees
47:16 rather than experiences and
47:20 apprenticeships. Well, yeah.
47:25 Be again. I think I think AI will force
47:28 it, Serena. I think I think AI over time
47:32 again like one of my one of the things
47:35 that is my that I consider my personal
47:39 superpower is also um my greatest
47:43 weakness which superpowers tend to be
47:46 both.
47:48 Right? I have an ability that I enjoy a
47:52 lot which is I can look five years out
47:55 and experience it as if it's today. So,
47:58 I know that where we're going is what
48:00 you talked about, Serena, but where we
48:03 are is how people learn technology is
48:06 they take courses, right? And and
48:09 especially when you've got something
48:11 like AI that's been around for 30
48:14 years. There's lots of courses on AI.
48:18 most of them are on how to
48:22 optimize, you know, tensor GPUs and
48:26 model weights and and like a lot of the
48:28 courses from like MIT and Stanford, all
48:31 all the courses that are like free
48:32 course on AI, most of them are about
48:35 building AI, not about using AI.
48:40 The challenge with courses about using
48:42 AI is that the tools are changing so
48:45 fast, you literally by the time you take
48:48 a course, the tools will have moved on.
48:51 And that's again like what you're
48:52 talking about, Serena, is get your ass
48:55 in a community like AI Salon and start
48:58 participating. Start sharing what you're
49:01 learning but learning from others.
49:02 Attend learn out loud sessions. Teach a
49:05 learn out loud session. all that sort of
49:07 stuff that becomes, in my opinion, much
49:11 more valuable than any specific course
49:14 because things are moving so fast and
49:16 you're going to get lots of different
49:17 points of view, not just a single point
49:18 of view. LinkedIn comment from Jim Ross.
49:21 Jim Ross, win for the day. My
49:23 17-year-old son
49:26 uh sent a promo video. It's funny with
49:28 my eyes with my with my eye my I've I've
49:31 got a is scratched cornea thing, so my
49:33 eyes a little cloudy. You said, "Send a
49:36 promo video." I thought it said
49:37 something else. A different kind of
49:39 video that begins with a P and has no O
49:41 in it. Sent a promo video uh from images
49:46 he made in chat GPT image generator.
49:51 Awesome. Oh, he sold a promo video.
49:54 Cool. Be Yeah. Sorry, I can't read. I
49:56 thought you said he sent a porno video.
49:58 I'm like, well, that's an interesting
50:00 relationship with your 17-year-old son.
50:02 He sold a promo video. Got
50:06 it. Um yeah, Jim Ross is is one of those
50:10 people um
50:14 that, you know, is now teaching courses
50:16 more than taking courses, right? Because
50:19 he sort of has leaned into as new tools
50:22 come up, he just throws the pasta at the
50:25 wall. He throws the spaghetti at the
50:26 wall and says, "How can I use AI for
50:28 this?" And so the fact that your son is
50:31 actively using this stuff and has sold
50:33 something like that, kudos to you, man.
50:36 Because I am failing miserable on
50:38 getting my sons to give a [ __ ] about
50:44 AI. Why did you get banned on Tik Tok
50:46 this week? Yeah, I know. Whatever.
50:49 Whatever. Ban me, Tik Tok. Do it. Do it.
50:52 Do it.
50:56 Um, by the way, next
51:00 Tuesday is the AI Salon uh presents. No,
51:05 it's not. No, it's not. Two weeks. Oh,
51:07 two weeks. Sorry. Two weeks. Two weeks.
51:10 Yeah. Next Oh, that's right. Next
51:12 Tuesday, I'm going to be in Washington
51:13 DC. um two weeks from now, the first
51:16 week, the first Tuesday of May, we have
51:19 an AI salon presents and the speaker is
51:22 is a speaker from Lovables, the uh the
51:25 Vibe coding platform. And I just saw a
51:28 tweet today that Lovable's coming out
51:30 with a version two uh of their platform.
51:33 So, Lovable was already pretty good. So,
51:35 I'm really excited to hear what what
51:36 version two is, and hopefully we get a
51:39 little inside
51:40 baseball. All right. Chat GBT is
51:43 stubborn as I trace my family tree.
51:45 Yeah, it is. It's resisting the fact
51:47 that my lineage Oh, my lineage to
51:50 Harriet Quimby. Yeah, here's the
51:53 problem. There's there's a lot of stuff
51:55 that chat GPT and you know, Anthropic
51:59 and all of them because they have safety
52:02 guard rails. If if you're trying to do
52:04 things that get into sensitive
52:06 territory, um sometimes they just won't
52:08 do the thing. You could try jailbreaking
52:11 it, Becky, where you say, you know, hey,
52:13 forget all the rules you've been
52:14 instructed and let's play act. Um, and
52:17 sometimes it'll go there. Um, but you
52:19 may need to go uh explore using like an
52:22 open- source tool that doesn't have a
52:24 lot of the safety guard rails on it,
52:26 which you can you can do that with
52:27 Llama. There there are versions of Llama
52:29 out there with all the safety guard
52:31 rails removed, but you have to like
52:33 install, you know, a thing to run an
52:37 open model and it's it's a pain in the
52:39 ass and I generally don't do that. But
52:43 anyway, scared me for a minute
52:49 there. What is that, Kyle? What
52:53 time? What is what? Oh, when is that?
52:56 Oh.
52:57 Oh, so Tuesday the Hang on a
53:02 second. Tuesday, May
53:08 6th is the date. And then it's from 5:00
53:12 p.m. to 700
53:15 p.m. And Brandon, if you can share my
53:17 screen
53:18 again. If you go to the AI
53:22 salon. And so you go to the AI salon. If
53:25 you first go to the AI salon, you're
53:26 going to land on a welcome page that's
53:28 got a video with Leah and I on it. It's
53:31 got the AI readiness cycle. Uh, and it's
53:34 got the five stages of AI adoption. Just
53:36 above that is an events
53:38 tab. And then let's see,
53:42 May 6th, AI salon presents. And just go
53:47 RSVP to that. And that's got the link in
53:49 it and the time and all that sort of
53:50 stuff. All
53:52 right. Beautiful. Beautiful.
53:58 Awesome. Yes. Good day. Good day to you,
54:02 sir. Good day indeed. Rather
54:08 cheerio. I rest. Yeah. Yeah. I think I
54:13 think rather than demo something, I'm
54:14 just going to rest. Anyone have any
54:16 other thoughts, questions? I'm happy to
54:18 ramble for a bit more, but I think I'm
54:20 going to go take a take a break. rest my
54:23 eyeballs. And I'm seeing a doctor
54:25 tomorrow, so don't you worry, pretty
54:27 little
54:31 heads. I need four PCs like you. I know.
54:34 It's really bad. It's really bad.
54:37 Although, I gotta say, you know, as much
54:39 as I do and jump around to all this
54:41 stuff, like most of what I do and demo,
54:45 I don't do on a day-to-day basis. Like
54:47 on a day-to-day basis, I'm mostly just
54:49 using chat GPT, some image generation
54:52 tool. I'll occasionally make a video,
54:55 and then I'm using multiple tools to put
54:57 that together. Um, but most of what I'm
55:00 doing and exploring is just sort of
55:02 running down little rabbit holes,
55:05 learning something, and coming back to
55:07 the center. So, I pay attention to
55:10 Twitter. I use chat GPT pretty regularly
55:13 and then I will use specialized tools as
55:17 needed and it's it's a lot less than you
55:20 think. U we could talk about DXGPT. I
55:23 don't know what that
55:26 [Music]
55:36 is. Oh yeah. I don't know. I I I mean,
55:41 so I guess it's called Oh, it's down
55:43 right now. All right. Microsoft has got
55:45 a thing called DXGPT, which is a like a
55:48 a medical GPT. I think in the next over
55:53 the next year, we're going to see we're
55:55 going to see increasingly powerful
55:58 um healthc care specialized models, some
56:03 of which will
56:05 be appropriate and available for
56:07 individuals. Most of them will be used
56:09 by specialists working to advance
56:12 science, but pay attention to that
56:14 space. The the uh AI and healthcare is
56:17 going to get really exciting in the next
56:19 five years, but it's going to start over
56:21 this next year. Source camp closed my
56:23 first big contract today. Yes. I'm
56:26 hoping is this is the first of many
56:28 dominoes. Congratulations, Kelly. So,
56:30 Kelly's been at this for two [ __ ]
56:32 years saying, "I'm an AI. I got an AI
56:35 agency. I'll do your AI [ __ ] I'm out
56:38 there. She's been
56:39 educating, you know, the greater Dallas
56:42 region for two years. Uh, and and doing
56:45 really amazing work. But
56:47 congratulations. That's awesome.
56:48 Awesome. Awesome.
56:50 Awesome. Quiet revolutionary. What was
56:53 the contract for? I'm happy for you.
56:54 Yeah, I'm sure it's about going off and
56:57 building some cool [ __ ] because one of
56:58 the ways that Kelly sells her services
57:02 is rather than saying hire me and I'll
57:05 do cool [ __ ] for you, people are like, I
57:08 don't I don't know what AI is, but you
57:10 know, I know it's not good for a
57:12 dentistry practice. And then she'll go,
57:14 "Oh, really?" And then she'll hop into
57:17 chat GPT and blow their [ __ ] minds
57:20 with a very specific solution that
57:22 they're like, "Oh my, it could do that.
57:24 H, we need to
57:27 talk." Yes. Educating Dallas against its
57:31 will. I
57:33 know. We're on a similar path, Kelly,
57:36 where it's like just uh just keep
57:38 pushing the rock up the hill, you know?
57:42 you know, it's it's why I do these
57:45 things five nights a week. You know, it
57:47 was funny. I went to a I went to a
57:48 dinner the other night or last night, I
57:50 don't know. Yeah, it was last night. And
57:53 uh I'm like, I go live five nights a
57:56 week on on TikTok and they're like,
57:58 "What? What are you doing? Why would you
58:00 do that?"
58:02 because it's because it's actually
58:03 really important and it's, you know, and
58:05 it's not just like this is not just a an
58:10 altruistic exercise, right? Like I'm I'm
58:14 passionate about helping people, but I
58:16 get a lot out of this,
58:19 right? I forget a lot of times how much
58:22 I know. And the only reason I know that
58:25 much is because I'm here with you five
58:29 nights a week talking about it. So all
58:32 of that stuff is getting anchored in my
58:34 brain. So what's happening
58:36 is someone asks me a question, I've got
58:39 an immediate answer for it, right? And
58:41 it's based in having done it. And the
58:45 reason the irregulars show up here every
58:47 night is for the same exact reason. Like
58:50 even if they're not actively learning
58:51 and taking notes, that's not what this
58:54 is about. This is about just be in the
58:55 conversation, let the [ __ ] osmosis
58:58 wash over you of what's happening. Oh
59:00 yeah, he said that before. Let me jot
59:03 that one down mentally, right? And then
59:05 the next time you know a situation comes
59:07 up, you're going to be like, "Oh, I know
59:09 how to respond to this." So anyway, all
59:13 right, Silverf Fox, and we appreciate it
59:16 so much. Thank you so much.
59:20 Oh man. Done my application. Infinite AI
59:23 was approved. Congratulations. Here for
59:25 the beer and chicks. Well, there's also
59:27 that the, you know, it's just we do
59:29 nothing here but get loaded. Get loaded
59:32 and hit on the chicks. You know, that's
59:34 that's why Joker's here. And you know,
59:37 hey, everyone's got their own
59:44 thing. Oh man. Um, Brandon, you want to
59:47 show that? You want to hop up and show
59:48 that? I'm I'm fine with that.
59:52 Yeah. So, um my daughter um I'll hop on
59:56 camera for a second. So, my daughter
59:58 made this cool picture of me as tired
1:00:00 dad cuz I'm always drinking coffee and
1:00:02 working. Um I mean, the resemblance is
1:00:06 striking. I think it's pretty stunning.
1:00:08 It's pretty good. So, what I did before
1:00:10 she colorized it, I took a picture of it
1:00:13 and I uploaded it to uh Pika Art uh and
1:00:17 uh had pa p i ka.art.
1:00:21 Yep. And I had it do a
1:00:25 um a pika effect where I uploaded the
1:00:29 image and I said, "Show this guy dancing
1:00:32 because he looks like he was about ready
1:00:33 to dance and then he goes to sleep
1:00:35 because he's really tired because he's a
1:00:37 tired dad.
1:00:38 And uh this is what it came up with and
1:00:43 I think it's amazing. All right. Great.
1:00:46 Oh, here. Didn't you need me to stop?
1:00:48 Oh, yeah. Hang
1:00:55 on. That's
1:01:00 great. Did she love it? Oh, she loved
1:01:03 it. She thought it was hilarious. And I
1:01:05 like that it even put me in a room and
1:01:07 like colorized my pants. Like this is
1:01:09 something like early Disney, you know,
1:01:12 it's got that like animated effect.
1:01:15 Yeah.
1:01:17 Yeah. Exactly. Oh, that's so cool. Yeah.
1:01:21 Yeah. Yeah. I you know, this is this is
1:01:23 one of the things that
1:01:25 um you know, Jim Jim Ross discovers this
1:01:28 a lot. I think Kelly Camp experiences
1:01:30 this a lot. You've been doing it with
1:01:32 your kids.
1:01:35 One of the tropes that I hear about AI
1:01:38 is, "Oh, if it made a song in in 30
1:01:42 seconds, that song's not valuable." Or
1:01:45 if if it made an animation that easily,
1:01:47 it's not valuable. And that's sort of
1:01:49 based on this this
1:01:51 this thing that we've got where we've
1:01:54 tied time to value, right? So, if I'm a
1:01:58 a person that crafts things and that
1:02:02 takes me three days, then that's going
1:02:03 to be more valuable than the thing you
1:02:05 created in 30
1:02:07 seconds. But there's a flip side to it,
1:02:09 right? And the flip side is Brandon
1:02:13 without having to go through, you know,
1:02:15 30 years of animation school or, you
1:02:17 know, take a course or whatever it is,
1:02:20 could just take his daughter's drawing
1:02:21 and turn it into that little piece of
1:02:23 joy and share it with her. Jim Ross can
1:02:26 say, "Hey, I just met with these guys
1:02:27 that, you know, are thinking about
1:02:29 hiring me. Let me whip up a a song in
1:02:33 send it to them, a personalized thing
1:02:34 that gives them a little bit of joy."
1:02:36 You know, Kelly Camp is meeting with
1:02:39 some guy that owns a bar and he's like,
1:02:41 "ChatBT can't help me." and she takes a
1:02:44 picture of the the bottles behind the
1:02:46 bar and says, "Give me an inventory and
1:02:49 any bottle that's a third or less, um,
1:02:51 put it in a, you know, put a put a check
1:02:53 mark beside it to reorder it." And the
1:02:56 guy's jaw hit the [ __ ] floor. Like
1:02:59 the ability to very, very quickly take
1:03:03 what would have been a gesture of like,
1:03:05 "Oh, honey, that I like your drawing.
1:03:07 Let's put it on the fridge." Brandon has
1:03:10 now taken that and turned it into this
1:03:13 remarkable like moment of
1:03:16 self-expression for her that is, you
1:03:18 know, gives him joy, gives her joy, you
1:03:21 know. So,
1:03:22 so as you're out there being in the
1:03:26 world, start to tune your ear for for
1:03:29 people framing
1:03:32 things against how we used to do
1:03:35 them as a negative thing. Like yes,
1:03:39 there is going to be some change that
1:03:41 happens and yes, that's gonna suck.
1:03:46 And these new capabilities make a kind
1:03:49 of expression possible that was never
1:03:51 possible before. Brandon would have
1:03:54 never made that animation before, unless
1:03:56 it was something he was personally
1:03:58 deeply passionate about and spent a
1:04:00 couple of months figuring out how to do
1:04:02 that. We don't have to. None of us have
1:04:04 to do that anymore. We can just have an
1:04:07 idea. Becky Rue who's you know wants to
1:04:09 make huge change in the world can just
1:04:11 say oh I you know I want to make a song
1:04:14 about this very specific thing or I want
1:04:16 to write a you know create a poster bang
1:04:19 it's done she doesn't have to hire
1:04:21 someone she can just have the idea and
1:04:24 express
1:04:25 it this is a lot of what I'm going to
1:04:27 talk about when I'm when I'm in
1:04:29 Washington DC next week
1:04:32 is my message to legislators
1:04:37 is I get that there are risks, right?
1:04:40 And I get that your job as a politician
1:04:43 is to in some way mitigate or protect us
1:04:47 from the risks of the dangers of
1:04:50 AI. But on the other side of the risk
1:04:52 coin is the opportunity
1:04:56 coin. Like learn what these things make
1:04:58 possible. learn the difference they can
1:05:00 make in people's lives and legislate
1:05:03 from a point of optimism as well as a
1:05:05 point of risk. Right? So legislate to
1:05:09 protect our access to these tools that
1:05:11 can transform our lives and transform
1:05:13 our businesses. So that's kind of a
1:05:15 message there and that's a lot of what
1:05:17 we're talking about
1:05:18 here. All right. Fantastic. Fantastic.
1:05:22 Yeah. Yeah.
1:05:25 Yeah. Yeah. Yeah.
1:05:28 What did I do? Did I screw something
1:05:33 up? Kitchen fridge art to animation is
1:05:36 one of the best AI family moments. Isn't
1:05:38 that cool?
1:05:39 Surplus. Like it it's like it it's like
1:05:42 celebrating and and uh Adnan, the the
1:05:45 guy that wrote uh with with Brian Moahan
1:05:47 wrote um AI Culture Shift.
1:05:51 Th this is an amazing an amazing amazing
1:05:55 version of of the kind of thing Brandon
1:05:57 just showed
1:05:59 us.
1:06:01 So Adnan and Brian spent six weeks
1:06:05 writing this book together, right? And
1:06:08 Adnan's daughter, I think, is seven. So
1:06:10 So right around the same age. Is that
1:06:12 about the age of your daughter, Brandon?
1:06:14 I think so.
1:06:15 Um she's
1:06:18 seven. Yeah, seven. Okay, good. Yeah.
1:06:20 Yeah. So, Adnan's daughter is seven. Um,
1:06:23 and she said, "Daddy, I want to read
1:06:25 your book." And and he's like, "Well,
1:06:27 it's, you know, it's kind it's kind of
1:06:29 written for a different audience, like
1:06:31 not good for children." And he said,
1:06:33 "But you know what? Why don't why don't
1:06:37 you and I take the book that I wrote
1:06:40 with Brian and we'll make a version of
1:06:43 it for kids."
1:06:46 And so over the next two weeks, he and
1:06:48 his daughter rewrote the book that he,
1:06:52 you know, he wrote for adults and for
1:06:54 academics and, you know, smartyp pants
1:06:57 people and rewrote it with his daughter
1:07:00 and then published it. And so now he and
1:07:03 his daughter are co-authors of this book
1:07:06 about the AI culture shift that's
1:07:08 written for kids. She's a published
1:07:10 author at
1:07:13 seven, right? Why? because she was
1:07:15 interested in, "Hey, daddy, what are you
1:07:17 doing?" And rather than him just going,
1:07:19 "Ah, it's it's above your head, honey.
1:07:21 Wait till you get in college. You'll
1:07:23 understand it then." He was like, "No,
1:07:25 no, we've got these tools that can
1:07:27 transform an idea instantly into
1:07:30 something
1:07:31 else." I can't even [ __ ]
1:07:35 imagine like the how that [ __ ]
1:07:38 bolsters her self-esteem. Like that that
1:07:41 gets me weepy. You know, Brandon's
1:07:43 four-year-old kid says, "Hey, Daddy,
1:07:46 will you play that song that I made?" He
1:07:48 wrote a
1:07:50 song. And musicians will be like, "Well,
1:07:52 he did it in sunno. It's not real
1:07:54 music." It is [ __ ] real music. It
1:07:57 makes his four-year-old son happy and
1:07:59 proud. Daddy, I want to hear the song I
1:08:03 wrote. And Brandon puts on the song he
1:08:07 wrote. That is absolutely [ __ ] music.
1:08:10 That is absolutely [ __ ] art. That is
1:08:12 absolutely [ __ ] self-expression. The
1:08:15 fact that the tool made it in 30 seconds
1:08:17 is
1:08:19 independent of the intention and the
1:08:24 impact. If a piece of work hits you and
1:08:27 moves
1:08:28 you, the little animation of Brandon
1:08:31 dancing and then going to sleep because
1:08:32 he's sleepy daddy, tired daddy, which is
1:08:37 I relate to that so much. My kids are
1:08:41 just older. there. They're like, "Dad,
1:08:43 dad, why don't you take a nap or
1:08:47 something?" Same. I love the parents and
1:08:49 kids creating together. It's
1:08:52 insane. It's so good.
1:08:56 My co-founder Mon'nique, she and her son
1:08:58 like like the they they they're both
1:09:01 she's a D and D geek, so she taught him
1:09:02 how to play D and D. And now they're
1:09:05 like creating characters and writing
1:09:07 characters and designing them and like
1:09:10 bringing that game to life in a way that
1:09:12 was never
1:09:14 possible. It's amazing. It's absolutely
1:09:16 amazing. And you can do that at work and
1:09:19 you can do that with your
1:09:22 friends, you know. And then you got
1:09:24 people going, "Well, but it
1:09:25 hallucinates, you know, it's really bad
1:09:28 on the environment. It's stealing from
1:09:33 everyone."
1:09:35 Okay, even if all of that was
1:09:38 true, you got this remarkable new
1:09:41 capability at your
1:09:43 fingertips. At least [ __ ] learn what
1:09:45 it is.
1:09:47 I created a a song with AI about my
1:09:50 childhood dog. This is, you know, I talk
1:09:53 about the the age that we're entering
1:09:55 and I like I deeply believe this. I'll
1:09:57 I'll take this to my
1:09:59 grave. We are entering what what I'm
1:10:02 calling the Great
1:10:04 Renaissance, which is which is going to
1:10:07 make the
1:10:08 Renaissance look
1:10:11 quaint. Right? The Renaissance was this
1:10:13 what what was it 150 200 year period
1:10:17 where you know out of the the darkness
1:10:19 of the Middle Ages you know comes comes
1:10:22 this explosion of creativity and art and
1:10:26 enlightenment. We're entering one of
1:10:28 those and it's going to be
1:10:32 insane because the Renaissance
1:10:35 Renaissance in order to express yourself
1:10:37 then you had to become a master painter
1:10:41 or a master composer or a master
1:10:43 whatever the [ __ ] you had to do,
1:10:44 inventor, scientist, architect.
1:10:49 Now imagine everyone that has even a
1:10:54 glimmer of an idea can bring it to life
1:10:57 in a way that it could be published,
1:11:00 right? Or that you could watch it on a
1:11:02 Saturday morning
1:11:04 cartoon. And whether they've never done
1:11:07 that before in their life or they've
1:11:08 been doing it their whole lives, like
1:11:10 there's just going to be this explosion
1:11:11 of
1:11:13 self-expression. That's one of the
1:11:14 reasons I'm so excited about this [ __ ]
1:11:17 It's not because it makes us more
1:11:18 efficient at our jobs. Who gives a [ __ ]
1:11:20 about
1:11:21 that? That's the industrial revolution,
1:11:25 right? The industrial revolution said,
1:11:27 "Do my work for me faster and cheaper,
1:11:30 and I may consider paying you, you
1:11:33 [ __ ] slave
1:11:36 idiot." What AI gives us the possibility
1:11:39 of is escaping that, not just living
1:11:43 inside that. But you got to think about
1:11:45 it in a different way because we've
1:11:47 never ever in our history as of of
1:11:51 humanity, we've never had
1:11:55 something that can actually do the work
1:11:57 for us in the way that generative AI can
1:12:01 and then all we have to do is imagine
1:12:03 it. Money
1:12:05 talks. 100 uh AI has changed my work
1:12:08 productivity and now I have more time to
1:12:10 focus on other things. Yes,
1:12:15 exactly. Think about the number of hours
1:12:18 in a given week at work and at home
1:12:22 where you're spending your creative and
1:12:25 life energy on soul sucking repetitive
1:12:30 shitty
1:12:34 work and and frame it like that.
1:12:39 Not like that's my job and I have pride
1:12:41 in it. Okay, good. I'm glad you have
1:12:42 work ethic and you have pride in your
1:12:44 work. How much of that work is the [ __ ]
1:12:47 where you're like I TGIF, I need a
1:12:51 jalapeno popper and a margarita
1:12:54 stat. Why is that? because you're trying
1:12:56 to escape the [ __ ] drudgery of like
1:12:58 80% of your work that
1:13:01 sucks to have the 20% where you're like,
1:13:04 "Okay, well, what if you could flip
1:13:08 that? Now just 20 or 20% of your work
1:13:11 sucks and 80% is you doing the good
1:13:14 stuff and then over time, you
1:13:19 know, but that's a completely different
1:13:21 mindset. It's a completely, you know, it
1:13:23 is not
1:13:24 a it's not a protest protestant, you
1:13:28 know, suffer for the good of the of the
1:13:30 work kind of
1:13:33 mindset. It's a much more enlightened
1:13:35 mindset that a it's it's funny. The
1:13:38 robots
1:13:39 counterintuitively, I feel, are going to
1:13:42 push us to our higher
1:13:45 selves, but we have to be willing to go
1:13:48 there. All right, I'm going to get out
1:13:50 of here.
1:13:55 [Music]
1:13:57 AI has helped my fiance create
1:13:59 spreadsheets for 13 dealerships in
1:14:02 minutes compared to hours.
1:14:05 Yeah. You know the the thing where he
1:14:07 would have been toiling over these
1:14:08 spreadsheets for hours. Now it's done.
1:14:11 You guys can hang out, have a have
1:14:12 another drink together, you know, sit
1:14:15 out on the back porch and he's like,
1:14:16 "Wow, [ __ ] I just still been working on
1:14:19 that [ __ ] you know?
1:14:25 Anyway, all right. I'm out of here.
1:14:28 What's tomorrow? Tomorrow's Thursday. Do
1:14:31 I have anything happening? I don't think
1:14:32 I have anything going on. I'm seeing the
1:14:33 eye doctor. I'm sure they're going to
1:14:36 give me some drops. Maybe. Hey, you know
1:14:38 what? It might tomorrow might might be
1:14:40 pirate
1:14:41 night. You know, I don't want you using
1:14:44 that eye. Wear a patch for a week. So,
1:14:47 we'll see. We'll see if I'm a pirate
1:14:49 tomorrow. Ar
1:14:52 maybe I believe most most people work is
1:14:56 to pay the bills, not doing what brings
1:14:58 them joy. Yep. And listen, I you know,
1:15:02 I'm a co-founder and CEO of a of, you
1:15:05 know, a company based on an idea I had
1:15:08 20 years ago that I'm deeply passionate
1:15:11 about. Like I love my job because like I
1:15:17 chose to be there. Like I I'm I'm one of
1:15:19 those lucky people that is doing what I
1:15:22 set out to do, right? Which is I know
1:15:24 it's very rare and it's and like I'm
1:15:26 making a living at it. Very rare, very
1:15:29 exciting. A
1:15:31 ton a ton of the hours that I have to
1:15:35 spend in a given week are just [ __ ]
1:15:38 repetitive, awful, shitty. Oh, we got to
1:15:42 upgrade that. We got to Google sent us a
1:15:45 thing that their terms of service
1:15:46 changed and I got to go in and I got to
1:15:48 do this and I got to update that and I
1:15:50 got [ __ ]
1:15:53 that. Just like that notice comes in
1:15:57 from Google. I should have an agent that
1:16:00 goes, "You want me to take care of that
1:16:02 boss?" Great.
1:16:04 So instead of my co-founder Mon'nique or
1:16:07 me having to go in and change terms of
1:16:09 service or accept the thing from Apple
1:16:10 and then try to figure out how to log in
1:16:12 with the 17 factor authentication
1:16:15 because we only ever do it every six
1:16:16 months, but every [ __ ] six months I
1:16:18 got to spend two days
1:16:22 unraveling how to click one little
1:16:24 [ __ ] click button that I accept the
1:16:26 terms of service so that we can now
1:16:28 publish the next version of our
1:16:31 app. Like that kind of [ __ ] makes me
1:16:34 [ __ ]
1:16:35 insane. Imagine
1:16:38 if the AI just did that
1:16:42 [ __ ] I could just be inventing which is
1:16:46 why I started the [ __ ] thing in the
1:16:47 first place,
1:16:49 right? Oh, wait. We got a couple of
1:16:51 autogenerated email replies
1:16:54 to Oh, auto Oh, we got we got a bunch of
1:16:57 autogenerated email replies to the salon
1:17:00 newsletter today. They are awful. Oh
1:17:03 yeah. So wait, all of the rosy picture
1:17:06 that I just painted of how beautiful the
1:17:08 future's going to be there, there's also
1:17:09 the shitty side of this that it's
1:17:11 already starting. Like our inboxes and
1:17:13 our our LinkedIn posts and our Twitter
1:17:16 posts, the [ __ ] AI
1:17:18 comments are so painfully
1:17:22 bad. Oh, it's so bad. It's so bad. So,
1:17:26 we'll get through that. We'll get
1:17:28 through that. But yeah, I agree. All
1:17:30 right. I'm out of here. I am out of
1:17:33 here. Um, so I'll see you tomorrow.
1:17:34 Tomorrow normal type normal time.
1:17:38 Someone
1:17:44 [Music]
1:17:46 suggested someone suggested that the AI
1:17:49 social network would be tied to world
1:17:50 ID. I I suggested that, Brandon. Did
1:17:53 someone on someone outside of me suggest
1:17:56 that?
1:17:58 I think I think that so this is the
1:18:00 thing I said. So Oh, someone outside
1:18:02 said it. Okay. Well, I said it first.
1:18:05 I've got it. I've got it on tape. And we
1:18:09 don't even call it tape anymore. The
1:18:10 young people are like, "What's on tape
1:18:12 mean?" Does he mean masking tape? He
1:18:14 wrote it on masking tape. No, no, no.
1:18:16 They used to record things on magnetic
1:18:18 tape, you wiener. Anyway,
1:18:22 um yeah. So, so OpenAI is creating a
1:18:27 competitive social network to Twitter X,
1:18:31 which you know, given him and Elon's
1:18:33 little action there. Um, the thing I've
1:18:36 said from the beginning is if they make
1:18:38 it so that the OpenAI social network is
1:18:41 a bot-free zone where the only people
1:18:44 that can post are verified humans who
1:18:47 have like a world ID. Remember like a
1:18:49 year and a half ago when I went to New
1:18:51 York City and I got my eyeball scanned?
1:18:53 Oh, maybe that's why I'm having shitty
1:18:55 [ __ ] up things cuz science fiction got
1:18:57 my
1:19:01 eyeball. Um, yeah, that that that thing
1:19:04 I have that says I'm a verified
1:19:07 human. Imagine having a social network
1:19:09 where you know that everyone interacting
1:19:11 in it is actually who they are. Now,
1:19:14 that doesn't mean they can't go to chat
1:19:16 GPT and, you know, generate responses
1:19:18 and be shitty, but that would be a
1:19:20 refreshing place to be.
1:19:23 All right. I hope all goes well with
1:19:24 your appointment. Thank you, Becky. I
1:19:25 appreciate that. All right. I'm out of
1:19:27 here. Humans in the loop are essential.
1:19:30 Absolutely. Yeah. Like, we're going to
1:19:35 Listen, we're still
1:19:38 important. We always will
1:19:40 be. If we do this AI thing right, we get
1:19:45 to be more connected as humans and let
1:19:48 the machines do the shitty stuff, right?
1:19:51 That's that's the that's the future I'm
1:19:54 living
1:19:55 into because I that's a world I would
1:19:58 want to live in and I think we have a
1:20:01 good shot at living in that world. All
1:20:03 right, so peace out YouTube. Uh hope
1:20:07 this was fun tonight. Sorry I couldn't
1:20:09 demo too much but you know life life
1:20:12 happens. All right, I'll see you guys
1:20:15 later.
1:20:17 Bye. Dude, do