6/29/2026 - Building Your Digital Brain: How to Reclaim and Curate Your Lifetime of Data

Transcript

1. 0:02[music] [music] [music]
2. 0:22[music] Good evening. Good evening. Good evening. Welcome to the AI learning lab
3. 0:38here in the AI salon. Welcome, welcome, welcome. It is Monday night, June 29th. Where did June go? Was it that like anthropic took away
4. 0:50fable and we're all we've all just been whining for three weeks and that makes time. It is whining the great time expender.
5. 1:01Is Is that what's happening? Welcome everyone. Uh welcome if you're new here. Um welcome. Welcome to the AI salon.
6. 1:10Welcome to the AI learning lab. This is Monday nights. Uh I am just going to sort of talk about stuff. If you have
7. 1:15thoughts and ideas, jump in. There's comments that you can comment here. So up in this h this corner right here is
8. 1:24um the uh the chat. So especially if you're on desktop, you you click that. It'll pop out over there. So if you're
9. 1:30if you're here and can chat, go ahead and throw something in chat. Say hello. Uh hello. Um and uh and you can also
10. 1:38check out the AI salon. So just check out everything going on in the AI salon. Um where to begin? Where to begin? Where to begin?
11. 2:11Okay, I'm going to begin with data hoarding. This
12. 2:25never seen this before if you've been on the live. This There's a whole bunch of hard drives.
13. 2:39I think in 35 or 40 years I've never thrown out a hard drive because
14. 2:55so if you're if you're neurospicy hey Frostbitten what's happening um if you're neurospicy and if you're a data hoarder one of the stories
15. 3:09that I tell myself is at some point in my evolution as a human, I'm going to take all the data on all
16. 3:21those hard drives and the ones under my desk here and the ones over there and all the old laptops I don't use anymore
17. 3:27that I didn't wipe the hard drives on, all of that. At some point, I'm going to take all that data and I'm going to look through it
18. 3:36and I'm gonna see what's there and I'm gonna find gems. I've got one of those myself. Yeah, you got the big box of hard drives and and
19. 3:47listen, it's not just that. I've got the same with fly tying materials. I've got the same with just all the stuff, right?
20. 3:55Books I'm not going to read, right? We've we've all got those things. And secretly in my head was like maybe there will be a day
21. 4:10where you can just take all your [ __ ] and something can figure out what's there for you. And that's that we're there. We're there.
22. 4:26I have taken files for programs that no longer exist, proprietary formatted files and given them to chatpt or claude and said, "What
23. 4:38is this?" And it says, "Oh, this is a file from this format and I I'll go ahead and dig through it for you and
24. 4:45extract all the data out of it for you." Right? And it's like, you used to have to pay people $10,000 to do data forensics.
25. 4:56So, why am I saying this? There's the data hoarding thing. So, somewhere on those hard drives probably
26. 5:09is an idea or two that if I saw it today would spark some new idea or rekindle an old project and could be something ma
27. 5:18amazing in the world. maybe nothing. For the past 20, 25 years, I don't know how old Google is, but once Google hit
28. 5:32the scene and Google cut us the deal with the devil. Hey, I got an idea. I'm going to give you this search engine for free
29. 5:44and all you have to do is just like give me your data. We're like, all right, cool. because how valuable is that data? Turns out
30. 5:55it's worth trillions, right? But you have to be Google, a company the size of Google to be able to do anything with it
31. 6:04because big data requires big data scientists and big iron to process that data. Except now you don't need to be a data scientist.
32. 6:20Got any Post-it notes in that suitcase? No, my Post-it notes went away. Hang on a sec. Oh, I know what I did. Hold on. Hold, please.
33. 6:31Restore tabs. There they are. Close notes. You're cute. Okay, I see them now. The linked item has been deleted
34. 6:41from this board. Frostbitten. I see the thing from frostbitten. Linda Sherman, aloha from Kawaii. I posted this on X
35. 6:48today. confused by the changes in Gemini lately and having notebook LM available in two places. They've been making lots
36. 6:54of changes and you aren't the only one. I made this chart that you can help. Oh, cool. All right. So, go go uh check out
37. 7:01Linda's post there. It looks like there. So, Notebook LM was what I was just going to talk about. So, Notebook LM at this point, I think you
38. 7:10can give it 200 files and they can be 500,000 tokens each. So that's about 350,000 words. So 200 files of 350,000
39. 7:22words each you can just upload to notebook LM and it'll just understand everything that's there. That is likely more data than you've
40. 7:32produced in your lifetime. Unless you're, you know, a really pr prolific data producer, it's a lot. And so we can now just take our bits
41. 7:46of things we've produced and transcripts of videos we've done and conversations we've had and books we've written and screenplays and
42. 7:56powerpoints and word documents and business analyses. Yeah, makes me sad because of the years of kid pics on some of those hard
43. 8:10drives. Bad mommy. Well, talk about bad daddy. So, I'll join you. I'll join you, Silver Fox. Because I was a photographer when
44. 8:20digital photography came out. I was like, well, I'm gonna keep doing film photography because it's good. It's
45. 8:26goodter. And digital photography was kind of crappy. So, so my guys were born in 99. Digital cameras back then were still kind of
46. 8:35shitty. And so I've got piles of slides and physical photos. I've got crappy digital camera photos. They're all over
47. 8:46the place. They're physically all over the place. They're digitally all over the place. So, yeah, there's there are
48. 8:53five, six year periods where I just have nothing because it's on some other form format. [clears throat] But we now live in a world where
49. 9:05what's striking me, this is like it's it's hitting me when I when I cut my personal deal with Google and Facebook and all those when
50. 9:18when I just said, "Yeah, they're going to give me free [ __ ] I'll give them my data." I don't care. I would never leverage that data anyway
51. 9:27in in no way. There was no place in my imagination that I would live long enough or technology would advance fast enough
52. 9:39for me to be able to think differently about that. And yet here we are. My husband keeps the slides in a temperature controlled
53. 9:50box. There you go. Got negatives? Yep. [laughter] Frostbitten 600. If you've got Google Ultra. All right. So, if you're paying
54. 10:00Google 200 bucks a month, your notebook LM you can upload 600 half a million parameter or uh token documents.
55. 10:11And that's [clears throat] just one tool, right? Then we have chat GPT. You've got your whole history of chat GPT, your whole
56. 10:18history of Claude, Perplexity, whatever tools you've used, Gemini. You have all these conversations and some of them because AI can do
57. 10:27remarkable stuff and you probably went down rabbit holes you've never gone down because you didn't have the expertise before.
58. 10:35You've now taken your ideas and run them down run them through these large language models. So you've got your digital hoarding data.
59. 10:45You've got your digital footprint. Hey Andy, you've got all of these conversations you've had in large language models.
60. 10:59You've got all of the active stuff that you're doing, right? So, here's my active stuff for work. Here's my active
61. 11:05personal projects. Here's my active community projects, right? Here's my little design thing. Here's the book I wrote. Here's my musical.
62. 11:19So, we now live in a world where you can take big piles of data and you can put it in a thing and you can go, "Tell me what's in the
63. 11:29thing." And then it'll list a bunch of stuff and you can like look through it. It's a lot of [ __ ] And if you've got, you know, if you're
64. 11:42one of the card carrying members of the ADD club, one of those things will excite you and you'll run into that rabbit hole.
65. 11:51But even with AI, if you're thinking of that data as a thing that you need to personally collect and then you need to personally
66. 12:00sift through, right? If I think about this box of hard drives, there's there's two pieces to it, right?
67. 12:10One is I need to buy some sort of box that I can just pull those hard drives out of the box and plug it into a
68. 12:16universal adapter to transfer the data from those hard drives to some other hard drive, right? And time was
69. 12:26that you would have to put stuff on that other hard drive and look through it and organize it and go, "Oh, this is
70. 12:31garbage." and this isn't and right you'd have to do all that. So, one of the reasons I've never gone through that is
71. 12:37that's completely overwhelming and I don't have a three-month period where I can just look through folders
72. 12:44and I don't have the attention span and I just don't care. But I've still held on to them. Well, now we live in this world where
73. 12:52you can just take this raw data and just dump it into a single directory and just point AI at it and say, "Go find what's in there.
74. 13:03Then you can say, "Oh, those those things are cool. Bring those out. Pull those out." Right? It'll find it. It'll pull it out.
75. 13:12But even with something like Notebook LM, you can say, "Make me a master list. Make me a map of all the [ __ ] that I've
76. 13:18just given you." It's kind of overwhelming, but
77. 13:36What if you could sift through it all? What if you didn't have to manually go through it?
78. 13:56You just buy another bigger computer with a giant hard drive. Right. [laughter] I haven't spent the time to find the
79. 14:05things I need AI to sort. This is one of the things we're going to talk about tonight. Let me correct that. My c husband keeps
80. 14:12his professional photography slides in humidity controlled cabinet, not temperature controlled. Color slides are somewhat fragile. Yeah.
81. 14:30So with aentic platforms like OpenAI's codeex and claude code and cloud co-work you can take your data and you can have
82. 14:43those things sift through your data and find the patterns and organize it and figure out what's in there and you can have it put it in a
83. 14:55tool like Obsidian where you can go look at all your stuff and see how it's all connected and you can do all that, but
84. 15:01I'm finding that overwhelming, too. Like I I see one of those Obsidian maps and it's like, do I got to click on all that
85. 15:06[ __ ] and then go look at the documents underneath it? Like that starts to get overwhelming. Well, I don't need to do
86. 15:13that now because I have an agent that I can just say, "Hey, did did I do any aing writing in the 80s?" that is related to anything I'm
87. 15:23doing today. Oh, sure. Here's three or four things you did. Oh, [ __ ] I forgot about those.
88. 15:40So, that's all there now. And and there's also just things like for however long you've been doing transcripts of your business meetings
89. 15:55and personal meetings and any videos you've done, any podcasts you've done, right? Any of that stuff that no not only captures your
90. 16:06knowledge, but it also captures how you talk. It kind of captures some version of who you are. So, let's park that. So, we've got all
91. 16:20of the digital crap we've ever made. We now have AI tools like Notebook LM, which can put it in a format that we can
92. 16:30interact with it in a pretty easy way. And now we have agents that sit on top of all that data and are able to do all
93. 16:37sorts of stuff with it without us having to personally sift through it. So, there's something there. Then out in the world,
94. 16:51we've got all this other stuff that we've made. Maybe we've made a workshop. Maybe we've made a book. Maybe we've made uh a business.
95. 17:01Maybe we're a consultant. Maybe we went to Stanford and Harvard and Yale and Colombia and we got PhDs from all of them. And for years
96. 17:18those letters equals money. Colombia PhD dollars. Harvard PhD dollars, right? 20 years at IBM dollars. There's all
97. 17:35these dollars connected to our expertise, to the things we put in the world. Nobody gives a [ __ ] anymore.
98. 17:46Nobody gives a [ __ ] about your degree. Nobody gives a [ __ ] about the paper that you wrote. Nobody g Why? Why? Why don't
99. 17:53they give a [ __ ] Isn't it just as valid as it always was? Like I still have that expertise. Yeah. There's just not a market for it.
100. 18:05Why? because I can just go to chat GPT and I can ask the same question and it will know all the stuff that you know and then some
101. 18:19and this part of the the great repurpose. So in in the AI salon in the mastermind, we've got the great repurpose. This whole idea that our
102. 18:27identities are tightly coupled to this stuff, these outputs that we've created, these degrees that we've gotten, these tasks
103. 18:36that we do at our jobs, and AI is systematically devaluing all of the external pieces of that, leaving us to say, wait a minute, what's
104. 18:49what's my value? And and to the to the extent that you can't decouple those, when the value of this stuff drops to zero,
105. 19:04[clears throat] you go with it. And that [ __ ] sucks. So like all that stuff, the workshop you created and the courses
106. 19:19and the books and the just all that stuff, there's not going to be a market for it. And if you're like Kyle, that's just [ __ ]
107. 19:31Tim Ferrris, you know Tim Ferrris, 4H hour work week dude, brilliant dude. Sales of his books, which are based on his expertise, on his
108. 19:44experiments, of how he's run his life, sales of his books have dropped 80%. Not eight, not 18, 80%.
109. 20:00And he's got a name. He's Tim Ferrris. you like watch interviews with him, you're like, "Shit, dude's dude's wicked smart."
110. 20:12So, even the best most expert of the experts are facing this same dilemma. Okay?
111. 20:27And I know this is getting bleak. I'm going to take you to the depths and then I'm gonna we're gonna we're gonna march
112. 20:32you back out. We're like walk up the mud bank. We're in the deep part of the lake now. Going to walk you back up.
113. 20:43There's a silver lining here. part of
114. 20:58my relationship with this channel certainly over the past year has has altered and I've been meandering.
115. 21:07I'll talk a little bit about this and I'll talk a little bit about that and talk about and then I meander.
116. 21:18We have to stay long enough to be walked out. So, don't leave yet, folks. Depths of despair. Yeah, we've got we've got all the we've
117. 21:26got all this digital [ __ ] we've made. A lot of it is now valueless. We've got the stuff we put in the world and the
118. 21:33stuff that used to have value that now is valueless or decreasing quickly in value. Anything new that we make. Oh, I have a
119. 21:45new way to teach chemistry. Oo, I have a new way to talk about how the world is flat or round or oval. It doesn't
120. 21:52[ __ ] matter. Whatever idea you have, anything you make now and put out in the world, no one is also going to give a [ __ ]
121. 22:04I created a new game. I I made a new No one's going to care. like
122. 22:20how do I make money [laughter] in this world you describe? I don't have a great answer for that, but I do I do now know what the [ __ ] to
123. 22:30focus on. Okay. So, a a big part of the DNA of the great
124. 22:44repurpose is about individuals reclaiming their agency, saying, "Here's all the tasks I had. Here's all the
125. 22:51degrees. Here's all the [ __ ] I had independent of that. Here's the kind of person I had to be to be able to do
126. 22:59that. Okay, I've got perseverance. I'm smart. I'm this. and that okay, those are values that persist. And those are values that if someone
127. 23:10knows me can trust me for those things. I'll make sure the job gets done. I'll make sure that I have a point of view.
128. 23:18I'll make sure that the thing is the prettiest thing you've ever seen. Whatever is that thing, right, of kind of how you show up when you
129. 23:27work. And then a layer deeper than that is who are you that you can show up like that. Oh, I'm a badass innovator. Ah, okay.
130. 23:39So, if you can start to get in touch with who you are as a human, you can start to say to the world, hey, you know
131. 23:47where I can help? Anywhere where you need a badass innovator, whatever that is. And what does that look like? Well,
132. 23:54that looks like me showing up, you know, with enthusiasm and with a point of view and with taste and with grit and stick
133. 24:01tuitiveness, and I'll make sure that, okay, that's someone I could get down with. Right? So, someone's not going to
134. 24:08hire you because of the degree or the job you had before. They're going to hire you because they get to know, oh, she's a badass.
135. 24:21I'll work with her for that. And bonus, she's got all that experience. Bonus, she's smart enough to have all those degrees, but it's like
136. 24:30the like the the what leads is shifting, right? We used to lead with the stuff. Here's the book, here's the degree, here's the resume.
137. 24:44Now we're having to lead with here's me. That's daunting, right? Okay. So, that's that's one half of this thing.
138. 24:55One half of the great repurpose. Reclaim your agency. Understand you've got [ __ ] value. Like real value.
139. 25:06You independent of the [ __ ] independent of the outputs. your point of view, your clarity, your brilliance,
140. 25:18your compassion, your empathy, whatever it is that's your thing, value. Now, we've got all this data. That is the [ __ ] you've created.
141. 25:31Yeah, Brandon's here. Am I missing something? Laughing out loud. Nobody gives a [ __ ] Me in a meeting today. I know. You
142. 25:39inspired me. You inspired me, Andy. >> [laughter] >> Okay.
143. 25:54One of the things that I've learned Oh, she wants me to hear the message. Preach. Yeah. Brandon's a badass.
144. 26:08Independent of his outputs, independent of what he does. Why? He cares. He's sweet. He's an incredible family man and father.
145. 26:24He'll show up. He'll give a damn, right? Where else would I be? He's funny. [laughter] He's funny in a very subtle kind of way.
146. 26:41Like he's someone you can hang out with, right? Independent. I don't know where he went to school. I don't care.
147. 26:53Okay, now we've got all this stuff. Chat GPT fairly early on recognized that
148. 27:09chat GPT remembering some of what you talked about was valuable. So, in the beginning, December 2022, you would talk to chat GPT,
149. 27:23and in your chat session, it would it would remember all this cool [ __ ] about what you talked about until
150. 27:32its context window got blown out because its context window was really short, had really short short-term memory, and then
151. 27:38even in the same conversation, it would sort of forget what you talked about before. It was really frustrating. And
152. 27:43if you went to a new chat, it completely didn't know anything about the previous chat, right? But then they added this
153. 27:50thing called memory where you could say, "Hey, chat GPT, remember that I'm the founder and CEO of StoryVine, and
154. 27:57Storyvine does this." And it would write it into its little memory. And I think it had, I don't know, 32,000 tokens of
155. 28:03memory that you could, it was, I don't know, probably five pages of little snippets of what you could do. And then they said, "Well, wait a
156. 28:14minute. We can also create these things called projects where you can take multiple chats and sort of string them together and then if
157. 28:23you're chatting in that project, it it can remember the other things that you talked about in there." And then there were custom GPTs where
158. 28:31you could you could upload data to a custom GPT and you could say, "Hey, I want a GPT that's all about every
159. 28:37screenplay I've ever written and I want it to be my screenplay writing style custom GPT." And that it had its own kind of little
160. 28:46memory thing. And then I don't know a year and a half ago they came up came out with actual memory, right? You could say based on the [ __ ]
161. 28:56we've talked about and I think it it initially would do like a year a year's worth of chats. We were sort of three years into chat GPT
162. 29:07and it could go back kind of a year and now I think it it can look at the whole thing. It can look at all of what you've chatted about.
163. 29:15But when I go to Claude, my three years of conversation are useless because now I'm in Claude and I have to
164. 29:25start a whole another memory there. And so all of a sudden I'm starting to recognize, [ __ ] those three and a half years of
165. 29:35conversation in chat GPT are incredibly valuable to me, but they're also incredibly valuable if I could take those out and put them into
166. 29:44some sort of format that I could just point Claude to it and say, "Hey, by the way, here's a lot of [ __ ] I've been
167. 29:50talking about for three and a half years." Claude would instantly get more valuable to me. Right? The foundations for what I'm describing,
168. 30:06the ability to pull out chunks of your digital life and start to assemble them in some central repository are here with us today.
169. 30:23these agentic tools like Codeex and Claude Co-work and Perplexity Computer and Grock Build and whatever the [ __ ]
170. 30:33else comes down the line. all of these things in the beginning. [laughter] Listen, in my day.
171. 30:53So, one of the things I talked a fair amount in this channel is when when I started creating digital twins for content
172. 31:08evolution, right? And if you were if you're here for those conversations, the way we did those was we were going to start with LinkedIn
173. 31:20profiles. We were going to take people's LinkedIn profiles and say, "Hey, let's make a digital twin based on what's in
174. 31:28their LinkedIn profile." There were two problems with that. One is LinkedIn are [ __ ] They don't have an API where you can
175. 31:37just go get people's data because I don't know, I guess privacy. But it sucks because even if you have
176. 31:44someone's permission, it's not easy to go get their [ __ ] It's not easy to get your own [ __ ] You can request a data dump and within
177. 31:5324 hours they'll give you a zip file with some amount of crap in it. It's awful. And then what we realized is that the
178. 32:02content of LinkedIn profiles is a very skewed reflection of who a human is. It's really just their work resume. Well,
179. 32:14what about what art they like? What about their family? What about what they're thinking about today? Right? If
180. 32:20I've got on there that I co-founded agency.com in the mid 90s, the [ __ ] does that have to do with me today?
181. 32:29Right? There's no way to infer. There's no way to project what that means. Did any of that carry forward or is it all just bloiating?
182. 32:43In my day, our computers had to call up another computer with the telephone. [laughter] It's true. So,
183. 33:00so you got all this stuff. You now have these systems like codecs and co-work agentic systems that can do work on your behalf. And how
184. 33:16you make those things actually valuable is that you feed them context. Well, what context do you feed them?
185. 33:25Well, what most people are talking about is you take your work files, you take your sales process, and you take your
186. 33:32spreadsheets, and you take your uh standard operating procedure documents, and you dump them into codecs. And then you say, "Hey, I've got
187. 33:42a standard operating procedure for how we do outbound emails." So, create an outbound email thing. And then at some
188. 33:49point in there, it's like it writes an email and you're like, "This is a shitty email." And it's like, well, you could
189. 33:55give me examples of emails that are not shitty and I'll start writing like that. Right? So, the way you make these tools good
190. 34:02is you you tell them what's good. You give them examples. You give them data.
191. 34:18A lot of that work data is going to be commoditized. A lot of that work data is about how this company
192. 34:35made [ __ ] the old-fashioned way. And with AI, we're going to make the same [ __ ] with robots and with new procedures
193. 34:42and this and that. So, a lot of that old data is irrelevant. We don't know which is irrelevant, but there's a chunk of that data that is
194. 34:56completely relevant and that is the chunk of the data that really represents who you are. [snorts] So you've got the great repurpose
195. 35:11humanity part. This the thing that Andy and I are collaborating on. She's working on the human piece of this.
196. 35:22Decouple your identity from your job. Figure out your value. Figure out what the [ __ ] you want to do and who you care about.
197. 35:28And then go do that. And over here on the AI side, the only thing that really matters in the in the future
198. 35:41is going to be the stuff that represents you that you the whole and and realized person can say to these agentic tools,
199. 35:54go do this stuff I want to do knowing everything you know about me. And that's that combination of the real
200. 36:05human being who understands what they want and their point of view seamlessly integrated with this this digital brain
201. 36:15that understands the you and what you want to do and what you consider good and what you consider valuable. Those
202. 36:26two things are going to be the only things in the world that AI can't replicate. So each of us becomes this kind of superpower
203. 36:39of humanity and wisdom. And then AI is the amplifier.
204. 36:56You're like, "Kyle, what the [ __ ] are you talking about?" [laughter] Okay, let's see. Mary Carol. Mary Carol.
205. 37:07Had a long chat with Sunny today. Given that, I'm going to create a bumper sticker that reads, "Don't hire me for
206. 37:12my PhD or fancy ass resume names. Hire me. Hire me for the brilliance I bring to your org in solving challenges you
207. 37:19didn't realize you have. Yes. Yes. Mary Carol. Exactly. And here's the thing. It's not that the PhDs and the [ __ ] you did are irrelevant.
208. 37:35It's that their value in the marketplace isn't apparent anymore. Right. But your value as a human, your value to go, hey,
209. 37:49one of my one of my superpowers is I can look at your org and I can show you problems you didn't even realize
210. 37:56were there. How do you do that? It's what I've done all my life. Really? Yeah. Well, where else have you done
211. 38:01that? Then you can bring out the bring out the resume, right? But it's like the initial conversation. How long is your
212. 38:08bumper MC? That's pretty funny. But but but that that's it. And I think this is this is where like like I actually think
213. 38:17this is where business marketing has to go. I think business marketing that relies on we're the experts, we're the
214. 38:25this, we're the that all that [ __ ] this is the the best methodology. This is [ __ ] that's worked for 30 years is going
215. 38:37to stop working. Tim Ferrris's books are not selling. All of that stuff is just going to go, well then what do people care about? I
216. 38:49don't know. Some guy at Deote who's like, hey, I'm this guy from Deote, but you know what? I really love growing
217. 39:00grapes and I grow grapes and here's how I think about them and here's how I had it and and when I work with companies I
218. 39:08think about them like I think about grapes and all of a sudden people like what's the who's the grape guy? What's
219. 39:16the he he works at Deote but he's a grape guy. Yeah, you should talk to the grape guy. He's good. Well, first of
220. 39:22all, he'll give you a good bottle of wine. But second of all, like how he thinks about grapes. You should see how
221. 39:28he thinks about your business. Like it's like it's like we're entering we're entering this and and the grape
222. 39:38guy the grape guy is a good one. So So there's there's a very small intersection of circles, right? about
223. 39:45someone who needs consulting, someone who can pay for consulting, someone who loves people that are interested in
224. 39:54obscure things like grape growing uh and then someone who is also uh into wine and someone right there's there's like
225. 40:03the little overlapping circles. There's there's probably only 300 people in the world that will resonate with the grape guy.
226. 40:15But if the grape guy's message gets to one of those 300 people, they're going to be doing business together.
227. 40:22Because the grape conversation is going to lead to some other conversation that's going to lead to some trust.
228. 40:28That's going to lead to, well, wait, what do you do in business? Oh, I need that in my business. or for you, Mary Carol,
229. 40:35you know, talking about some thing you're passionate about is going to lead to some other thing that makes them tell you about their
230. 40:43business that makes you go, "Oh, I worked with a business like that." And you know, I found out one of their big
231. 40:47problems, they thought their problems were this, this, and this. But what the real problem was was this. And the
232. 40:54minute you say that, the person you're talking to goes, "Holy crap, that's our problem." Well, I know how to fix that. [ __ ] Really?
233. 41:03Have you done this before? Uh, yeah. I have three degrees in it. And I did it for Apple and I did it for H and I did
234. 41:09it for H. Oh, well, we should talk. We should talk. Like, I think that's how this goes. Charles Adams. I never knew that I was on the planet
235. 41:19before the singularity. At least it'll be normal [laughter] not to have figured it out after. [laughter]
236. 41:31Oh my god, I somehow got a very very David Atenboroough voice. My life is complete. I have a life narrator. Oh, that's really good. Um,
237. 41:44I think it's what you do with those degrees that sets you apart. The insight, the critical thinking. Yeah.
238. 41:48But, but it's but but make no mistake, Chef Kelly, this is a like like it's it's a seismic it's a seismic inversion.
239. 41:57Certainly here in America. In America, you you lead with I went to this school. I worked for this company.
240. 42:07I've got this [ __ ] on my resume. Because we overidentify with the work. And then, oh, by the way, I'm an all
241. 42:18right person, right? Like that's how it's been. And that that work that has worked. But it's that's been declining. Like
242. 42:26this isn't like AI did this. This stuff's been declining. What AI is doing is putting the nail in the coffin and
243. 42:31flipping the the the value iceberg upside down. That now who you are is going to be the only thing that
244. 42:43separates you. Not what you know, not what you did, not where you went to school, who you are. So,
245. 42:58so one of the things that I'm building into the great repurpose and one of the things I'm teaching myself is how to
246. 43:08build this system, how to figure out, wait, what data do I want to go and collect? How do I gather my [ __ ] from um
247. 43:15chat GPT and Claude and Perplexity and my hard drives and all the [ __ ] I've ever done? And we're going to be teaching that. So, just like
248. 43:25we're teaching inside the great repurpose leadership things and and identity workshops and things like that,
249. 43:31the AI workshops are going to be all around this creating this digital self. This digital brain, I don't even want
250. 43:40digital self isn't even right. Right. It's it's creating a memory system that is who you are that you can point all of the AI tools toward
251. 43:53and that thing is going to become really valuable. Okay, let me do a quick break. So, if you you can pop that back up. If you're
252. 44:05a part of the the AI salon mastermind, you have access to the great repurpose workshops. You have access to the um AI
253. 44:13salon mastermind practice lab. You have access to all of the ondemand content that's been created. So if you want to
254. 44:19create a daily practice for yourself around how you use AI, but you haven't been to the practice lab meetings,
255. 44:26they're all recorded. They're all in there on demand and they're quite remarkable. They're like many of the com I I have multiple
256. 44:34conversations a week with members of the mastermind. I I am forever crying in those things because we get to witness
257. 44:44one another evolving and figuring out who we are and figuring out where the value is and figuring out how to put
258. 44:50that in practice. And it can be quite moving when you watch someone go from I don't know what the [ __ ] to do to holy
259. 44:57[ __ ] look what I just did. this whole big insight that I'm talking about about the value of a whole you and
260. 45:08a whole digital you and those two things interacting that has come directly from my conversations in the mastermind over
261. 45:18the past six months. So, um, so if you haven't joined it, consider joining it. Um, because it's about it's about leveling up your AI,
262. 45:28but it's really about leveling up your life. And it's about it's about figuring out what's got lasting value in this world. And I think
263. 45:39really owning who you are, really owning the data that represents who you are, that you give access to these AI tools.
264. 45:50Those two things are actually going to be all of our competitive advantage. Okay, cool. Um, so, so Brandon, do me a favor. Hop up on
265. 46:01stage and so I think Frostbitten's in here. Um, talk to me about what Frostbitten built and then maybe we can demo it. Wait, let's see.
266. 46:11>> Yeah, I was just gonna read this for you. [laughter] >> How I feed AI's lots of context. Wait, how I feed AIs
267. 46:20lots of context and DNA genome data. Then it helping connect things together. Then it visualizing it. Did you see the
268. 46:27link I sent a couple of hours ago? No, I didn't. But, um, Brandon, I I had a just a like a a what do you call it? I don't
269. 46:37know. I did a lot today, but none of it was related to any of this stuff, so I didn't see it. Um, but
270. 46:43>> most folks would call that a busy day at work. >> That's Yes, I remember [laughter] there was there was um It doesn't [ __ ]
271. 46:52matter. I I just remember this moment in high school where I was I was using a word that was bigger than needed to be
272. 46:58used. And this basketball jock was just like, "You mean you put your hand around the ball?" Um, okay. Let me look at this [clears throat]
273. 47:13pre genomic. So, let me share my screen. Is that Wait, where did I put it?
274. 47:33>> [clears throat] >> I just I just put your app in a tab. Frost bit enough. Here it is. I couldn't find the tab. [laughter]
275. 47:49I'm such an idiot. All right. Is it going to be obvious what I'm looking at here?
276. 48:03Kim Katkin, what are we talking about tonight? Recently, I saw a post on X about a six-piece memory system. Brent and I had
277. 48:12a long discussion one day about building an AI brain and how it needs to mimic the actual brain. Yeah, that's cool.
278. 48:19That's that's the kind of stuff that I'm going to be learning about and and putting together for us Ben. Okay, hang on.
279. 48:30Let me share my screen. I have a I have a suspicion about why my my screen was quitting all the time and I tried
280. 48:39something that hopefully will help. Okay. So, the frostbitten health atlas. Oh, this
281. 48:55is cool. This is a compass, not a GPS. A structured way to identify which genomic variants are worth investigating
282. 49:05based on the things you already know. your ancestry, medication response, physical traits, cognitive patterns,
283. 49:12tier one, zero cost observations, 5 to 10 minutes, blood work patterns. So basically upload your blood work. This is very cool.
284. 49:23Start screening. So it's got some Do you have this? Do you have this? Oh, this is cool.
285. 49:45So, this is already based on these questions already putting up potential genetic varants and things like that.
286. 49:53This is super cool. Frost Frosty Frosty McBitten
287. 50:31Super cool. And then you upload. So wait, let me go back. Then you upload. Oh, I can't go back. Can I go back? No, can't go back.
288. 50:40Educational, not diagnostic. This is super cool. So then you I assume you're putting in health data, watch data, things like that.
289. 50:49Is is Frostbitten here? I mean, I know he's here. Do you want to come up on stage and talk about this? This was a six-month ago app I built.
290. 51:00This is just a section taken out of the whole thing. 37 questions and you can use blood work to help narrow it down
291. 51:06with 20 conditions from this. The full app has 53 conditions matrix with 70 supplements, 256 medication interactions. That's amazing.
292. 51:18Well, what's what's popping into my mind is um at some point in the not too distant future if it doesn't already exist,
293. 51:31you're going to be able to take data like this and put it into a crisper Oh, Frost Bitten's in the studio. Great. Let's bring them up. Um
294. 51:40so, so, so this is super cool. Um, [laughter] so, so tell me the history of this thing and like like where is it and where,
295. 51:48where you want to take it. >> Uh, it was kind of when I did my 30 times genome sequencing like a year and
296. 51:54a half ago and then learning about all like a [ __ ] ton of things in like the first year and then before my grandma
297. 52:00passed away like a about a year ago at this point. I got hers done too and then I started matching up all that data and
298. 52:05then like once I started learning about everything I started like matching everything together like extended family
299. 52:10and even further family then then it started to apply to other people too and I was like okay this is interesting then
300. 52:16back in like January February I started putting this all together and this was like just a small section so like
301. 52:21there's where it's like escal well advanced to now is like oh there's 55 conditions with interactions again 70
302. 52:31different supplements nutrients vitamins like which ones you should that would help and which ones you should avoid and
303. 52:36it's also up to 260 medications or something now too with those 53 conditions. >> So do you think this thing just keeps
304. 52:44evolving at some point you'll just push a button and out out will squirt a a pill? Well, yeah, you could. It's kind of you
305. 52:52pretty much have like the exact precise type of very specific ones to take, but I mean, yeah, could you maybe
306. 53:02manufacture it into like, you know, the right combination of things? I'm sure >> maybe. >> Unbelievable.
307. 53:10>> But if somebody did have their genome sequencing done, they could match it to lots of these things in there. Like this
308. 53:14is just like a small excerpt that was taken out, right? >> Yeah. And is this what was the is this something you're passionate about or was
309. 53:22it that you were just dealing with like this just started as a curiosity like where how's this connected to you and what you care about?
310. 53:30>> Wow. Cuz my health wasn't doing good at all. So that's why like a year and a half ago I got this like you know 30
311. 53:38times. It's like about a,000 bucks or something. I mean it was there now I think it's about 7800 US.
312. 53:43>> Uhhuh. to get the really good one. But I was just trying to figure out because the doctors, you know, didn't have
313. 53:47enough time or spending, you know, they were more focused on, you know, how many patients they can get done through, right? Because,
314. 53:53>> right, >> they're not it's not really based on, you know, them spending an hour, it's how many they can get through, right?
315. 53:58So, just trying to like figure out what my health issues were and trying to stay alive because, you know, people want to
316. 54:05stay alive. So, then I was trying to figure out the things that I would like to like that I would need to do. So like
317. 54:09every time you get like a DNA result, it's like, hey, you would have these symptoms and these conditions, right?
318. 54:14>> But it doesn't tell you anywhere how you could actually make these symptoms or conditions less like which nutrients
319. 54:20specific ones you should take that maybe these wouldn't even happen to begin with. And so if you were taking those to
320. 54:26begin with, then you would have to take the medications. But if you did, then you would know in the newest version now
321. 54:31you can type in or match with one medication that it like links it all to the other ones with the same pathways in
322. 54:36the body and other different connections. is like medical conditions and then you can kind of see how they're all linked. It's
323. 54:43>> it's bonkers. It's crazy. >> Just we're just working on it here and there. >> And so this app, the the the Frost
324. 54:50Health Frost-alth-Las.netify.app, that's something anyone can use. >> Yeah. So I just threw it on there
325. 54:58because [laughter] most of the time I was running on my computer and I was just showing people, right? So then I
326. 55:03was like, "Oh yeah." So that I was at a family re or not family a school reunion on the weekend and then lots of these
327. 55:09thing conditions and stuff were starting to apply to people and I was like oh like then the next day I was like >> wow
328. 55:14>> I just turned the question part I just took that part of the whole project and got clawed to take it out and just turn
329. 55:19it into like a single file and then I just I was like okay I'll just throw it on I tried throw it somewhere else but
330. 55:24then I just end up throwing ati just to make it easy. Yeah, beautiful. All right, cool. Awesome, man. That's very,
331. 55:32very cool. Congratulations. That's awesome. >> But if you actually go through it and throw your blood work, it'll actually
332. 55:37tell you like, hey, if you have this, maybe, but here's some like here's a quick like, you know, maybe take more
333. 55:41magnesium or more vitamin C or something, whatever specific just had blood work done. I think I'm going to do that.
334. 55:48>> There's lots of And then if you I think it does it on there. if you say if you get your blood work done and say you if
335. 55:54you had the app open like you know two or three times right it'll it saves it locally right so like if say if there's
336. 56:01a like blood or something or whatever within the borderline it'll tell you after two three times hey this isn't
337. 56:06borderline maybe you should get this looked at maybe bring this attention if it's been sitting here this like
338. 56:10borderline the whole time most doctors only look at blood work to see what's wrong with you and not
339. 56:15>> you know once it gets past the certain edges right like the cut off so but not inside of it so these this helps with like edge cases and
340. 56:22It's beautiful. >> Yeah. Thanks. >> Cool. Thanks for sharing that, man. Um, so there there's a really good example.
341. 56:34So there's there's so much there to unpack, but what he's created there, the application is useful and valuable, right? So having
342. 56:45that application and what it is and what state it's in and how it's being used and how it's being marketed, if it's
343. 56:51being marketed, all that stuff can be part of the data set as can why he created the app in the first place. As
344. 56:58can what's going on now? Did that did that app actually help? at some point if the agentic tools get good enough and
345. 57:08he's got the ambition to do so he could say hey I think I want to commercialize this and somehow like how do I navigate
346. 57:16regulatory I know medical is crazy and then the agent can go off and do that right so every little piece of
347. 57:26what you've put time into and what you've created and who you are and why you did it and how that relates to your
348. 57:33values and who you care about and and who you are can all start to get amplified and tied together in ways that we as humans don't
349. 57:44need to make all those connections because they're really complicated. Like your world of data that you've created in your lifetime is a
350. 57:53complicated mess. And we as limited apes with language don't have the capacity to go through it, but the agents do,
351. 58:07right? And so that becomes incredibly valuable. Um I'm over here creating a life narrator for when I die, and he's over
352. 58:15there making it so I don't die. Yeah. Right? And both things can be true. You can you can have your life narrator, but
353. 58:25it's just going to be narrating it while you keep staying alive because of what he created. So now, okay, so this is good.
354. 58:36So we've got the great repurpose as this big umbrella. There's the human component to it. Who are you?
355. 58:45Why should we care? What do you bring to the party? the better you can get I can get at saying here's who I am and here's what I
356. 58:56bring and being able to articulate that and being able to tell stories about that and being able to get people to
357. 59:01resonate with that your value goes up all the [ __ ] that you used to lead with the value goes to zero you are the value
358. 59:13then we have this thing with all this data and all this stuff and all the things I've ever done and things that we
359. 59:19can't keep track of anymore, it can keep track of. So, what's our job with all that data? Our job is to go today,
360. 59:29the thing I care most about is taking Frostbitten Zap and turning that into a commercial enterprise and I'm going to
361. 59:35collaborate with him and we're going to and so I'm going to go to my agent and I'm going to say based on all this stuff you know about me,
362. 59:43we're going to go do this with that person over there. And by the way, here's all their information that
363. 59:48they've given us permission to tap into. So we can have those two entities collaborate together and go do a thing and then we as the
364. 59:58humans can go that's good, that's good, that's not good. Our job is taste and curation and having the idea in the first place and choosing
365. 1:00:08which one to go for. Okay. So those two elements of the great repurpose are about to become kind of [clears throat] shink
366. 1:00:23energized together and turned into like this Pokeball of energy and power that is going to be the thing that
367. 1:00:30distinguishes you in the world, the thing of value. It's going to be centered around you and who you are. Now, imagine a world.
368. 1:00:49And by the way, here's a here's a You want a business to build that potentially makes you billions of dollars? Go build this.
369. 1:01:05I've got this bucket of me that's got all my data in it. It's got the conversations I've had. It's got my health stuff in it. It's got
370. 1:01:15my sense of humor in it. It's got the visuals I like. It's got the writing style. It's got all It's This is the all of me that's got value.
371. 1:01:29All of the lessons I ever learned doing agency.com, all of the lessons I've learned doing StoryVine, doing the AI
372. 1:01:35salon, doing lives night after night after night for three and a half years, it's all got value. It's all in here, right? Imagine a system
373. 1:01:48where I can say companies or other individuals, if they want to tap into that, they pay me for it.
374. 1:02:03I like the way Kyle writes screenplays. I I wanna I want to tap into the official Kyle Shannon screenwriting tone
375. 1:02:11of voice and I want to write screenplays amplified by how he does it. All right, pay me a nickel every thousand tokens
376. 1:02:20you produce using my model. There's a something. I'm not chasing you down because you copied my screenplay.
377. 1:02:36I'm saying I will give you access to this who I am so you can go make your own [ __ ] screenplay based on [ __ ] I've written.
378. 1:02:50You're like, I'll pay Kyle a nickel every thousand tokens for that. Now, you might not pay Kyle for that, but what if the Kyle data
379. 1:03:05was one of 50 other writers that you really respect and you had access to a data set where you could go in and you could say, "Oh,
380. 1:03:17I want to write more like Kyle or more like this one or I want to I want to take sort of the best practices of all
381. 1:03:22those writers and I want to write like that or think financial analysis or think whatever the like screenwriting is just
382. 1:03:30a thing could be any of the things that data that we own is valuable. Okay. So, so there's that
383. 1:03:46then there's this other thing happening this bigger macro trend that's happening. Cindy [ __ ] told me about this last week.
384. 1:03:55She's doing all this research and what she's finding is that communities are purposefully making themselves smaller.
385. 1:04:15And they're making themselves smaller around a very specific number. People
386. 1:04:29are very excited about Frostbitten's thing. That's very cool. Um, and the very specific number is called
387. 1:04:37the Dunbar number. And actually, I want to go look it up. Tell me about the Dunar number.
388. 1:05:01The Dumbar number is the idea that humans can only maintain about 150 stable social relationships at one time. It comes from the British
389. 1:05:09anthropotoologist Robin Dunar who studied the relationship between primate brain size especially neoortex size and typical group size. He
390. 1:05:21extrapolated that humans that to humans and landed at around 148 which got rounded to 150. The core idea
391. 1:05:30is not you can only know 150 people. It's more like you can only maintain about 150 people as meaningful social
392. 1:05:39socially trackable relationships. People whose identity, context, relationship to you and relationship to others you can keep in your head.
393. 1:05:51Helpful way to think about the layers of intimacy. Inner Circle five, sympathy group 15, good friends 50, stable
394. 1:06:01network 150, loose acquaintances 500 plus. Um, but I those numbers are really cool, aren't they? So, so what do we have
395. 1:06:15here? Under 15 intimacy around 50 strong cohort around 150 village or tribe. Okay.
396. 1:06:44The epitome of mass media probably peaked. Let me let me let me see if this is um Did mass media peak right before
397. 1:07:00cable networks? Has it been declining since? Hang on.
398. 1:07:15Talking to my chat. GBT brain. because I have an instinct but I don't know if it's true. What's going on?
399. 1:07:29Chat GPT just [ __ ] to bed. Try again. And I know I'm not sharing my screen. So I'm just I'm just looking at research for a second.
400. 1:07:45Come on. H chat chippy TV slow. All right. Well, it doesn't matter. Um,
401. 1:08:02when you only had three TV networks, when you put out a message, that one message went to one of three large audiences,
402. 1:08:14right? We were watching ABC, NBC or CBS. And then and then the UHF channels with the snow, [laughter]
403. 1:08:24right? And then cable TV came along and fractured three into seven and then seven into 15 and then 15. And then the internet came along and
404. 1:08:35fractured it even further. Right? And now we're living in a world where we just within the past two weeks hit
405. 1:08:48the point where more content was generated by AI agents than by humans. So more content that we're taking in more than 50%
406. 1:09:00was not produced by humans. So, if you're a human making content, you you really don't have the chance at
407. 1:09:11at reaching 20 million people anymore. And in fact, Gary Vee is talking about this right now. He's got 50 million
408. 1:09:18followers or more. I don't know how many he's got. He's got a ton of [ __ ] followers, but they changed the algorithms in
409. 1:09:24social media. So, when he puts out a post, it's no longer shown to his 50 million followers. It's called attention media. Now what
410. 1:09:33what Tik Tok has done is they've said we're going to show a piece of content to a hundred random people and if that
411. 1:09:42goes well then we'll show it to 200 random people and if that goes well then we'll go to 500 then we'll go to a
412. 1:09:50thousand then we'll go right. So everything your audience size is based on each individual piece of content not based on your mass audience.
413. 1:10:00So, the fact that I have 45 or 46,000 followers on Tik Tok is irrelevant to how many people see my content. If my
414. 1:10:12content sucks, no one sees it. Okay. So, what does that mean? Well, I think that we used to have a fantasy
415. 1:10:29that if I have 50,000 followers and I put a piece of thing out there, that of those 50,000 eyeballs, that's how the
416. 1:10:37advertising agency talked about it. How many eyeballs do you have looking at your [ __ ] based on the number of eyeballs, some
417. 1:10:46percentage of them would buy or would engage or would do something, right? And I actually learned this from from
418. 1:11:02Andy that there's a huge difference between audience and community. audience is the 50,000 and the fantasy is I've
419. 1:11:15got some sort of relationship with them. I don't. The Dunar number says I can't. What I have is eyeballs looking at me,
420. 1:11:24but they don't give a [ __ ] about me. It's a it's that's not the relationship. The relationship is the 150 people who regularly or
421. 1:11:37semi-regularly come hang out at the live and interact with one another and interact with me that like all of us
422. 1:11:43interacting with one another. And if you think about those numbers of like five, 15, 50, and 150. Think about that. Of the irregulars,
423. 1:11:53there's probably five of them that you're really tight with. There's probably 15 that you're like, "Oh, I'd
424. 1:11:59love to see them at a party." There's probably 50 that like if you met them, you'd like, "I know you." So what if we're moving into a world
425. 1:12:16where the fantasy of having a million friends, a million audience, what if that fantasy is just shattered forever?
426. 1:12:31It certainly lowers the pressure of I've got to get a million people to like me. Remember project mockingb bird? One could argue
427. 1:12:42which is better controlled media through two outlets of fractured biased media with freedom to choose. I don't remember
428. 1:12:50project mockingb bird. I mean it sounds familiar. I just don't remember what it was. Valerie cox. This is why I make lists in
429. 1:12:58x to see those those I follow. Yeah, there you go. AI communities are shrinking because the field is moving too fast. The stakes are
430. 1:13:07higher. The largecale online discussion degrades into noise faster than trust confirm. Dunar's number is just a
431. 1:13:13convenient label for that human bottleneck. So, let me share an idea with you, Gareth.
432. 1:13:29What if you take that number and rather than
433. 1:13:45rather than think about like who are my 150 out there? What if you start building that network and like what if the prerequisites were
434. 1:14:01you kind of had to have your great repurpose [ __ ] together? You had to figure out who you are independent of
435. 1:14:07your work. You had to be a you have to be able to articulate who you are and what you can offer. What your value is,
436. 1:14:13who you care about, why, what your values are. You need to be able to articulate that. And then you've got a digital brain that is,
437. 1:14:24you know, a valuable asset that you've curated and and gardened and and weeded. And you've got those two things
438. 1:14:32together. And what if you started to create a network where you start to connect those people digitally and economically
439. 1:14:46and those people could live in a in a geography. They could live in a in a you know they could be part of a a physical
440. 1:14:54community. There's a guy named um oh what the [ __ ] his name? It's it's Emanuel. I forget his his last name.
441. 1:15:03He's I met I met him at the last DC flyin and he is he's a son of a pastor and he is doing deals with churches who have extra
442. 1:15:20space because people aren't going to church anymore. So they've got all this extra space that used to be community
443. 1:15:26center and all this sort of stuff. and he's leasing it out to to different organizations and pop-up stores and
444. 1:15:34things like that. But one of the areas he's getting a lot of traction is data centers, micro data centers, where big
445. 1:15:43data companies wanting to put data centers together rather than building the big 40,000 acre monstrosity are
446. 1:15:51saying, "Hey, there's all sorts of stuff out there that we could put, you know, machines in communities." So imagine if that community
447. 1:16:07said, "Well, wait a minute." Sounds like the beginning of a magic trick. So So you mean I really don't have
448. 1:16:1530,000 Chinese robots following me on socials? You do. [laughter] It's just they're never going to buy. Um,
449. 1:16:24so imagine that community being able to tap into some of that compute resource that's living in their local community
450. 1:16:33and that you could start to connect those people together. You could start to do things together. Or imagine, this is an experiment we
451. 1:16:44could potentially run in the AI salon. Imagine building a network of people who have their self and digital self [ __ ] together
452. 1:16:57and we start to pull pull compute [clears throat] resources, right? So if you enter the thing, you could
453. 1:17:05either pay money or you could pay with pedlops or flops, however many flops. So, I've got like a gaming PC and I've
454. 1:17:16got my M5 64 gig Mac and I've got my M1, this thing that I'm on right now with whatever it's got. I don't know, 32
455. 1:17:23gigs, 16, whatever it is. I've got some number of flops that I could put into the pool. And then you would obviously have to
456. 1:17:32have some technical infrastructure and technical people that could pull [ __ ] together. But imagine rather than me only being a able to run
457. 1:17:42a 32 billion parameter model, 50 of us collectively could run a 700 billion parameter model and we all get to use it.
458. 1:17:55And then because we've all got these digital selves, each one of which has value, well, two of them have more value and 10
459. 1:18:08of them have more value and and 50 of them and a hundred of them. And you limit that group, that network to 150 people,
460. 1:18:20and you don't get in it unless you're trusted. Right? So, so, so you've got all these overlapping circles of 15 trusted people.
461. 1:18:31And that's kind of how I'm starting to think about the salon right now. Not as 4,000 members of the AI salon. It's more
462. 1:18:40like Silverf Fox has, you know, five or 15 around her and Digital Gods does and Kelly Camp does and and then
463. 1:18:51and there's all these little overlapping circles. So imagine creating a system where you could purposefully overlap those circles and
464. 1:19:01create an economic engine [clears throat] that the members of that could tap into that larger resource and then if you're a member of it and
465. 1:19:17and you've got your health DNA thing rather than running your health DNA thing just on a crappy local model. You
466. 1:19:25could run it on this bigger batter ass model and you could take these agentic platforms and you could say, "Hey, go
467. 1:19:31turn that into a commercial entity and put that out in the world." And then some of what that generates goes to the group. Or maybe the data
468. 1:19:43that all of the people that are a member of is valuable enough that you can start leasing out that data and have companies
469. 1:19:49pay you for access to that data.
470. 1:20:10And the more flops you contribute or the more money you contribute, the more flops that are available. What are flops? Floating point
471. 1:20:20operations. Isn't that what they are? compute power AI learning sims kind of sounds like blockchain peer-to-peer community
472. 1:20:30problem solving. Yes. Yes. And and how would you track all this? Probably on the blockchain. Probably with NFTts that are not silly
473. 1:20:39graphics, but are tokens of access. If you've got this NFT, it means you can access this amount of data or you've got
474. 1:20:48a certain percentage of the thing. All of a sudden, I come into some, you know, a a windfall of GPUs fell off the back of a truck
475. 1:21:02and those GPUs can be contributed to the thing, I would get compensated for that somehow in in the thing. Now, what is all that? I
476. 1:21:13don't know. But like this is where my head is because if if the government is going to restrict access to to powerful models um and if
477. 1:21:28the economic engine as we've known it is about to go into full [ __ ] chaos rather than us being individuals trying
478. 1:21:37to solve this as individuals. What if you take trusted people you know and start to connect things and start to
479. 1:21:48connect resources and make little villages? Some are physically colllocated, some are digitally located. There's also um
480. 1:21:58a thing called meshtastic where you can communicate with one another even if the internet goes down in an encrypted way outside of the
481. 1:22:08internet. >> [snorts] >> Can I be in Brent's grid? Exactly. Mesttastic. Damn ken. Mesttastic baby.
482. 1:22:22That last part sounded very viable. So what does that look like? I don't know.
483. 1:22:36But it's like, you know, like we experimented on this channel with building GPTs and doing this and doing
484. 1:22:43that. I think part of it now is starting to understand how do we start to reclaim our data and put it into formats and
485. 1:22:51structures that we can own and maintain. This is my [ __ ] data. No, Google. you're going to have a copy of a piece
486. 1:23:01of it, but I'm going to start to claw back what I own and control because a lot of my digital data is garbage and I
487. 1:23:09don't give a [ __ ] about it. But there's some of it in there that I think's really valuable to what I'm up to right now. And that
488. 1:23:17I'm not going to have that live in Chat GBT. I'm not going to have that live in [ __ ] Claude or Gemini. I'm going to own that.
489. 1:23:26And then I'm going to dictate what AI tools have access to it and what are the parameters of that. And then I'm going to figure out how I
490. 1:23:37connect that to other people that are of value to me. And if I can get a diverse enough group of people
491. 1:23:45that are doing things like this one is trying to preserve how we tell our stories after we die and this one is
492. 1:23:52trying to make sure that we don't die and this one is trying to make sure that we all have strawberries and this one is
493. 1:23:57trying to make sure that we have the best art in the world and you put all them together and all their agents are
494. 1:24:04amplifying all that brilliance. You don't need to rely on all the other [ __ ] working. And listen, if all the other [ __ ] works
495. 1:24:18and you have that, cool. [laughter] Can I steal from the neighborhood grids? I'm sure there's going to be all sorts of that going on.
496. 1:24:32Wait, where did our data go exactly? Yeah, you got sleeper hackers that came in, sucked out all the data,
497. 1:24:42but you know, you're gonna have to have you're going to have to have technologists in there to make sure that all of that is being done well
498. 1:24:51and securely. Like I'm thinking about just my just creating my own personal data thingy. My guess is it's going to take me three
499. 1:25:08to six months to even understand what I want in it and what's possible to put in it and how to put it in it. And then
500. 1:25:15it's probably going to take me another year to get it good. And so I know what's in there and I know how to use it.
501. 1:25:27But that's where that's what I'm going to start working on. And I'm going to figure this this Dunbar number thing out. There's there's
502. 1:25:34something there's something here. I don't know what it is yet, but there's something here. It's going to be good.
503. 1:25:41It's going to be big. I'll be the forager and chef. Yeah. Yeah. Who's doing the good food? Who's doing the good music? We want concerts.
504. 1:25:53have our thing. So, imagine this. Let's say we're like five years in and we've got 120 people in the system and they've all
505. 1:26:07got their digital selves in there really well manifested. And then at someone at some point someone says, "Hey, um,
506. 1:26:18how about in August we bring in we bring together a bunch of bands?" And then they just say to the agents,
507. 1:26:26"Hey, could you put together a weekend festival? Pick a place. Pick the bands that that we know that people in here
508. 1:26:34will like. Book them. Pay them out of the treasury that this thing is generating money from. And we'll all
509. 1:26:42show up at the farm at Cindy's farm in in [ __ ] New Mexico. Show up there. It'll be a big concert. The robots will
510. 1:26:50have set up the stages. We hang out together. [laughter] Co-op, repurpose, reimagined. It is. But now we've got these amplification
511. 1:27:06machines. If we can figure out who we are and how we get represented in there that can take our ideas and make it all
512. 1:27:13real. All right, listen. Got three minutes left. This Wednesday at noon Eastern, we've got a new member mixer.
513. 1:27:20So, if you are new to this AI stuff, if you're new to the salon, if you're old to the salon, but you want to hang out
514. 1:27:27with new folks and go beat them, this Wednesday at noon Eastern, so 9 Pacific, 10 my time, 11 Chicago, noon Eastern, new member Mixer. Okay.
515. 1:27:41Um, this coming Friday is July 3rd, I think. That's right. Right. and the fourth is Saturday. I'm going to take
516. 1:27:51off Friday um so that we can all just go do go celebrate um and connect with our families. So July 3rd is Friday. Okay. So I'm going
517. 1:28:04to see you Wednesday night. Um if you can come to the new member mixer, please tell people about it. If you know
518. 1:28:13people who have thought about joining the salon or maybe join and haven't gone to anything, we're doing these new uh
519. 1:28:19new member mixers once a month. So, we'll talk about here's what's in the salon, here's how we got here, let
520. 1:28:27people introduce themselves. Um so, anyway, that's happening. Really excited about that. Um Thursday is uh the
521. 1:28:36practice lab and uh I think that's about it. So get your own [ __ ] together, get your digital [ __ ] together. Maybe we figure
522. 1:28:47out how to connect all that [ __ ] together and then all will be right with the world. And then maybe we just get
523. 1:28:53Fable back at some point and it was just a hiccup. [laughter] All right, Gareth got to go. If anyone needs a life narrator David Atenboro
524. 1:29:05voice and have 11 Labs, happy to share. That's awesome. That's super cool. All right, guys. Um, thanks. Have a great night. Bye.