Latest / Earn Your Leisure / EYL #309 Artificial Intelligence Explained: How to Make Money with AI & Use It to Improve Your Life ft X Eyeé

Transcript

EYL #309 Artificial Intelligence Explained: How to Make Money with AI & Use It to Improve Your Life ft X Eyeé · Earn Your Leisure

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  Speaker 1: Earners. What's up.
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• 1:53
  Speaker 3: All right, yeah, yes, welcome back, ladies and gentlemen.
• 1:58
  Speaker 1: Eyl, Happy Thursday, Happy Thursday, thursdow Man.
• 2:02
  Speaker 4: This is round two of our new series that we
• 2:07
  Speaker 4: are trying out is educational live streams, Live in the Flesh.
• 2:14
  Speaker 3: We last week we did real estate.
• 2:16
  Speaker 1: Yes we did.
• 2:17
  Speaker 2: We had a anazing conversation. Shout out at MG Shout
• 2:20
  Speaker 2: to everybody that was in the chat that got to
• 2:23
  Speaker 2: witness that live and other people that watched it the
• 2:26
  Speaker 2: day after or even leading up to this event. So
• 2:29
  Speaker 2: it was an incredible one packed with information. I think
• 2:33
  Speaker 2: tonight is gonna be one of those nights.
• 2:34
  Speaker 3: So, yeah, it's gonna be one of those nice so tonight.
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  Speaker 4: You know, it's one of these things that a lot
• 2:38
  Speaker 4: of people have been asking for for a long time
• 2:39
  Speaker 4: as far as artificial intelligence. And you know, we talked
• 2:47
  Speaker 4: about it a variety of different times on Market, Mondays,
• 2:50
  Speaker 4: even on EYL, but I think we had like a
• 2:52
  Speaker 4: thorough breakdown on what AI actually is from a very
• 2:59
  Speaker 4: easy to understand respective but more more importantly, how to
• 3:04
  Speaker 4: actually utilize AI for your own personal benefit as far
• 3:09
  Speaker 4: as your life, how to make money in your business,
• 3:13
  Speaker 4: how to you know, just be more efficient.
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  Speaker 3: That's important.
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  Speaker 4: A lot of time people talk about the negative size
• 3:19
  Speaker 4: of artificial intelligence, but obviously there's a lot of positive
• 3:23
  Speaker 4: things that you can do. So I think that this
• 3:28
  Speaker 4: is something that's obviously going to be very finally, considering
• 3:33
  Speaker 4: the times that we're in, this.
• 3:36
  Speaker 2: Is the talk of every room, every time we walk
• 3:40
  Speaker 2: into a room, and I think it's fitting, you know,
• 3:42
  Speaker 2: every time we meet somebody.
• 3:44
  Speaker 1: The awareness on AI it varies.
• 3:46
  Speaker 2: Some people have heard of it, don't really know, some
• 3:49
  Speaker 2: people kind of have heard of it, some people are
• 3:51
  Speaker 2: using it, some people don't even know what GBT stands for.
• 3:55
  Speaker 2: And so we've talked about it, like you said numerous
• 3:57
  Speaker 2: times about how we're using it, right, like you talk
• 3:59
  Speaker 2: about how you're using chat GBT nearly on a daily basis.
• 4:02
  Speaker 2: I know Ian sung about how it's made him an
• 4:05
  Speaker 2: even more efficient CEO for him. I've talked about how
• 4:08
  Speaker 2: I've been using it to help me when I'm investing,
• 4:11
  Speaker 2: but like people still haven't been saying, I've been using it,
• 4:14
  Speaker 2: Here's how I'm using it. So today hopefully we will
• 4:17
  Speaker 2: unpack some information so that the next time we run
• 4:19
  Speaker 2: into some people have conversations like I watched that and
• 4:22
  Speaker 2: this is how I'm using it.
• 4:24
  Speaker 1: That's the fact.
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  Speaker 4: And we got an expert in the field, X, who
• 4:31
  Speaker 4: we got connected with through Van Jones and spoke at
• 4:37
  Speaker 4: Investmentest and X got one of the best receptions from
• 4:41
  Speaker 4: anybody that spoke at invest Fest, which is speaks a
• 4:44
  Speaker 4: lot because obviously there's a lot of true, very highly
• 4:48
  Speaker 4: regarded people at invest Fest. So without further ado, let's
• 4:53
  Speaker 4: let's bring X up and let's let's get this going.
• 5:00
  Speaker 1: Hey, Hey, what's going on? Evening man?
• 5:03
  Speaker 5: Even it's a pleasure to be here pleasure to be
• 5:05
  Speaker 5: back on this stage.
• 5:08
  Speaker 3: Pleasure to have you.
• 5:10
  Speaker 2: It's an absolute honor to have you. And like you said,
• 5:12
  Speaker 2: it's very rare. I think this might have been the
• 5:14
  Speaker 2: first time. As somebody was speaking on stage, our phones
• 5:17
  Speaker 2: started blowing up, like, who is this person? Who is
• 5:20
  Speaker 2: this woman? She is killing it? I need to meet
• 5:23
  Speaker 2: her as soon as she gets off the stage. That
• 5:25
  Speaker 2: must have happened four or five times in my phone.
• 5:27
  Speaker 2: I'm sure it happened in his phone as well. I
• 5:29
  Speaker 2: was watching. I'm like, oh, oh, oh, this is incredible,
• 5:32
  Speaker 2: So congrat you. It's an honor to have you here tonight.
• 5:35
  Speaker 2: Everybody's in for a tree.
• 5:37
  Speaker 5: Yeah. Man, it's an honor to be here. I feel
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  Speaker 5: like as someone who's been in AI for you know,
• 5:41
  Speaker 5: almost twelve years now, this stuff comes like second nature
• 5:44
  Speaker 5: to me. But as it starts to go from AI
• 5:46
  Speaker 5: being behind the scenes to AI in our face, it's
• 5:49
  Speaker 5: critical that folks like me who understand this stuff come
• 5:52
  Speaker 5: back and give that game to our communities in a
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  Speaker 5: way that's accessible but also you know, accessible from an
• 5:58
  Speaker 5: information standpoint, but also accessible from a cost standpoint. Right,
• 6:02
  Speaker 5: there's a lot of folks out there who will put
• 6:05
  Speaker 5: this knowledge behind money and may not have the same quality.
• 6:08
  Speaker 5: There's no guarantee. So it's an honor to be able
• 6:10
  Speaker 5: to be on EILS platform to put our people on
• 6:13
  Speaker 5: game ultimately.
• 6:15
  Speaker 4: And not let's get it. And you are award winning
• 6:19
  Speaker 4: AI expert. You know, you worked in AI policy at
• 6:22
  Speaker 4: UC Berkeley, worked with some companies that you might have
• 6:26
  Speaker 4: heard of, like Google and Microsoft's Real and variety of
• 6:30
  Speaker 4: other things. So you are actually qualified to speak on this.
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  Speaker 4: You're not just somebody that we just randomly picked off
• 6:36
  Speaker 4: the street, right.
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  Speaker 5: Nah, definitely not.
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  Speaker 1: I mean.
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  Speaker 5: I've been an engineer, like an actual software engineer for
• 6:46
  Speaker 5: you know, almost twenty years now, but I've been specializing
• 6:48
  Speaker 5: in AI for the past twelve. I'm not only like
• 6:51
  Speaker 5: someone who worked in industry. When I was at Microsoft
• 6:55
  Speaker 5: building AI, bringing it to big companies like at Google,
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  Speaker 5: I worked across all their algorithms, helping to identify when
• 7:01
  Speaker 5: they were being biased or sexist or racist or messed
• 7:05
  Speaker 5: up towards our communities and coming up with fixes for that.
• 7:08
  Speaker 5: I created two research teams on my own. One of
• 7:10
  Speaker 5: them was around teaching AI how to measure who is
• 7:13
  Speaker 5: and isn't represented in content, so like how much is
• 7:16
  Speaker 5: someone who's more masculine presenting on screen versus someone who's
• 7:19
  Speaker 5: more feminine, and how much are they seeing versus speaking? Right,
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  Speaker 5: So we would use that to like do diversity studies
• 7:25
  Speaker 5: of all of Google advertising, and we made those tools
• 7:27
  Speaker 5: available to like third party partners also created the skin
• 7:31
  Speaker 5: tone Research team at Google, which literally taught AI how
• 7:33
  Speaker 5: to see black and brown skin tones. So myself is
• 7:36
  Speaker 5: someone who is a high school dropout, a two time
• 7:38
  Speaker 5: college dropout. I'm a published researcher in this space. I've
• 7:41
  Speaker 5: created tools that now you know, major companies all over
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  Speaker 5: the world, you specifically in AI. So I definitely hope
• 7:48
  Speaker 5: I know what I'm talking about. I know I don't
• 7:49
  Speaker 5: know everything, but I know I know what I'm talking about.
• 7:52
  Speaker 1: That's a fact.
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  Speaker 3: So all right, let's get into this YouTube.
• 7:58
  Speaker 1: Like and share, please please do to everyone I check in.
• 8:03
  Speaker 4: Let's run this ub. This is very very important information.
• 8:05
  Speaker 4: So okay, we're gonna we're gonna get right to it.
• 8:10
  Speaker 4: We want to talk about like actual items and stuff
• 8:12
  Speaker 4: like that. But before, let's just spend a couple of
• 8:14
  Speaker 4: minutes just to kind of break down that you've been
• 8:17
  Speaker 4: working in AI for years, So tell us you know,
• 8:20
  Speaker 4: kind of give us the framework of artificial intelligence so
• 8:23
  Speaker 4: we can have an understanding before we go into actually
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  Speaker 4: how to utilize it and make money from it.
• 8:29
  Speaker 5: All right, let's get into it. So can you guys
• 8:32
  Speaker 5: see my screen here?
• 8:36
  Speaker 1: Now? They can? They can see it now.
• 8:39
  Speaker 5: I don't need y'all to see all of that that
• 8:40
  Speaker 5: looks like Schrodinger's cat. This is a you know, a
• 8:44
  Speaker 5: conversation that I think is super important, and it's one
• 8:47
  Speaker 5: that I have with my clients day to day. And
• 8:49
  Speaker 5: I work with like big companies like Loril and Mozilla,
• 8:52
  Speaker 5: And it's kind of like what Van Jones said on
• 8:54
  Speaker 5: stage and investments. It's like nobody really understands this stuff, right,
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  Speaker 5: So you might hear like AI, deep learning, machine learning,
• 9:01
  Speaker 5: and the large language models, all these different terms to
• 9:04
  Speaker 5: talk about AI. So I want to start off by
• 9:07
  Speaker 5: making and giving y'all my framework for how to think
• 9:09
  Speaker 5: about what artificial intelligence is. So first, AI is not
• 9:14
  Speaker 5: just one thing, right, just like when you think of
• 9:16
  Speaker 5: the word car, car is not one thing. You can
• 9:20
  Speaker 5: have a two door car, you could have a four
• 9:22
  Speaker 5: door car, you could have a sports car, you could
• 9:24
  Speaker 5: have a truck. And even though there are all these
• 9:27
  Speaker 5: you know, different types of cars, like whether they're electric
• 9:29
  Speaker 5: or whether they're gas. Even though they literally end up
• 9:32
  Speaker 5: different in the way that they look, all cars pretty
• 9:36
  Speaker 5: much do the same thing, which is that they get
• 9:38
  Speaker 5: you from point A to point B faster than you
• 9:41
  Speaker 5: would get there if you were walking right, unless you're
• 9:43
  Speaker 5: in LA traffic at for it. Similarly, artificial intelligence covers
• 9:48
  Speaker 5: a whole bunch of different tools and technology across different disciplines.
• 9:52
  Speaker 5: It touches tools that are being built in computer science
• 9:55
  Speaker 5: and mathematics and electrical engineering and mechanical engineering. All AI
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  Speaker 5: aims to do pretty much the same thing. Artificial intelligence
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  Speaker 5: is trying to teach machines how to think and act
• 10:09
  Speaker 5: like humans. So all those different technologies and all those
• 10:12
  Speaker 5: different disciplines are just trying to teach machines how to
• 10:15
  Speaker 5: think and act like humans. Well, what does it mean
• 10:18
  Speaker 5: to think and act like a human? Well, humans have
• 10:21
  Speaker 5: five senses. We have hearing, we have sight, we have touched,
• 10:25
  Speaker 5: we have smell, and we have taste. And artificial intelligence
• 10:29
  Speaker 5: kind of has five domains. So teaching an AI, teaching
• 10:33
  Speaker 5: a machine how to hear and how to speak is
• 10:36
  Speaker 5: called natural language processing. That's what's behind tools like SyRI
• 10:40
  Speaker 5: inside of your phone. When you talk to her and
• 10:42
  Speaker 5: she writes the text down, that's called text to speech.
• 10:45
  Speaker 5: Then when she understands what you just said to her,
• 10:47
  Speaker 5: that's called natural language understanding. Then when she comes up
• 10:50
  Speaker 5: with a response to you, that's called natural language generation.
• 10:54
  Speaker 5: And then when she reads that response back I aloud
• 10:56
  Speaker 5: to you, that's called text to speech right where she
• 10:59
  Speaker 5: reads it out loud to you. So NLP, or natural
• 11:02
  Speaker 5: language processing, is teaching machines how to hear and how
• 11:05
  Speaker 5: to speak. Teaching machines how to see is called computer vision.
• 11:09
  Speaker 5: So if you have a ring camera in your house
• 11:12
  Speaker 5: and it's like, oh, person detected or animal detected, that's
• 11:15
  Speaker 5: using computer vision. That's also behind stuff like face ID
• 11:19
  Speaker 5: inside of your phone. When you go to the airport
• 11:21
  Speaker 5: and TSA asks you to stand there and it checks
• 11:24
  Speaker 5: the picture of your face. All of that stuff is
• 11:26
  Speaker 5: computer vision. Teaching a machine how to touch is called haptics. Now,
• 11:31
  Speaker 5: this is a field that you mostly see in robotics,
• 11:34
  Speaker 5: where they're doing things like creating artificial skin that's as
• 11:38
  Speaker 5: sensitive as human skin. Now why would they need that? Well,
• 11:41
  Speaker 5: think about it. If you have like a robot and
• 11:43
  Speaker 5: an Amazon factory. You want it to be able to
• 11:46
  Speaker 5: understand things like pressure and weight, so that when it
• 11:49
  Speaker 5: picks up whatever you ordered off an Amazon that might
• 11:52
  Speaker 5: be fragile, it doesn't pick it up and like shake
• 11:54
  Speaker 5: it around and mishandle it. Right. So they need that
• 11:57
  Speaker 5: artificial skin to be able to teach robots how to
• 12:00
  Speaker 5: understand what it is that they're physically touching and grabbing.
• 12:04
  Speaker 5: Then teaching machines how to smell is a pretty new field.
• 12:07
  Speaker 5: It's called machine oh factory. Now, I'm not gonna lie.
• 12:10
  Speaker 5: I don't really like this field because in order to
• 12:12
  Speaker 5: teach the algorithm what a smell is, you got to
• 12:16
  Speaker 5: use like somebody's nose as an example. And I don't
• 12:19
  Speaker 5: know about y'all, but some people out of the colognes
• 12:21
  Speaker 5: they be picking the perfuelings, they be picking like I
• 12:24
  Speaker 5: don't trust everybody's nose, right, And so machine ol factory
• 12:28
  Speaker 5: is a newer field. We've seen like maybe ten twenty
• 12:31
  Speaker 5: research papers in this space altogether, where they're trying to
• 12:34
  Speaker 5: do stuff like come up with new perfume smells or
• 12:36
  Speaker 5: like detect smoke from a smell, et cetera. And then
• 12:40
  Speaker 5: teaching machines how to taste doesn't actually have a fancy name,
• 12:43
  Speaker 5: but it has the same problem of kind of like
• 12:46
  Speaker 5: teaching a machine how to smell, Like, I'm not eating
• 12:48
  Speaker 5: at everybody's house, So whose taste buds are you using
• 12:51
  Speaker 5: as the example to like teach these machines how to taste?
• 12:54
  Speaker 2: You feel me definitely got you there, So that the
• 12:58
  Speaker 2: five sensors in the five domain makes a lot of
• 13:00
  Speaker 2: sense when people start hearing these things like computer vision.
• 13:04
  Speaker 2: Definitely that the smell and the taste, it is subjective.
• 13:08
  Speaker 2: It starts to lead to uncertainty. And one of the
• 13:11
  Speaker 2: things with human nature is that we don't like uncertainty,
• 13:14
  Speaker 2: which then leads to fear. So how can people become
• 13:18
  Speaker 2: less fearful when they when they hear about AI and
• 13:21
  Speaker 2: very broken down? How you just did it?
• 13:23
  Speaker 5: So I feel like a lot of the fear is
• 13:25
  Speaker 5: based on the unknown. Like the human brain generally is
• 13:29
  Speaker 5: wired to protect you from danger, right, Like the amygdala,
• 13:33
  Speaker 5: which we call the fight or flight part of the brain,
• 13:35
  Speaker 5: is literally the oldest part of the brain and it's
• 13:38
  Speaker 5: the only part of the brain that can hijack the rest.
• 13:41
  Speaker 5: So if you ever had like a panic attack, that's
• 13:43
  Speaker 5: literally your amygdala hijacking in your brain and shutting down
• 13:46
  Speaker 5: all the other different functions in your brain because it
• 13:49
  Speaker 5: literally thinks that you're dying. And so a huge part
• 13:52
  Speaker 5: of overcoming fear to AI is learning about it, doing
• 13:55
  Speaker 5: things like sitting in this class, taking notes, understanding what
• 13:59
  Speaker 5: the difference between NLP and computer vision, so that you're
• 14:03
  Speaker 5: able to not feel like because you don't understand it,
• 14:07
  Speaker 5: that it instantly means that it's going to be negative
• 14:10
  Speaker 5: against you. Now, there are real challenges with AI, with
• 14:13
  Speaker 5: which we'll probably get into later. But even then, the
• 14:16
  Speaker 5: problems inside of these AI systems, with things like bias
• 14:20
  Speaker 5: or things like them coming for you know, jobs that
• 14:24
  Speaker 5: particularly affect our communities, A lot of that stuff can
• 14:27
  Speaker 5: be solved if we step up in other areas, like
• 14:29
  Speaker 5: in policy, or if we step up in terms of
• 14:32
  Speaker 5: like regulation, or if we step up in terms of
• 14:34
  Speaker 5: building and designing our own systems. And so even the
• 14:37
  Speaker 5: stuff out there that is actually proven to be scary
• 14:40
  Speaker 5: or dangerous to our communities, there are solutions out there
• 14:44
  Speaker 5: that require all of us coming together and putting into play.
• 14:48
  Speaker 4: Okay, all right, so I know we have the next step,
• 14:52
  Speaker 4: which we're going to talk about how to utilize it
• 14:54
  Speaker 4: in business, anything you need you want to talk about
• 14:56
  Speaker 4: before that before we go to the business Ope.
• 14:59
  Speaker 5: Yeah, So before we jump into the business side, I
• 15:01
  Speaker 5: want to give a little bit more context about, you know,
• 15:04
  Speaker 5: how you teach a machine to think and act like
• 15:06
  Speaker 5: a human. So we know that AI is this group
• 15:09
  Speaker 5: of technologies that are trying to do that using this
• 15:12
  Speaker 5: five Census example. Now, generative AI specifically is attempting to
• 15:18
  Speaker 5: teach AI teach machines how to think and act like
• 15:21
  Speaker 5: the human imagination. Like, if I ask everybody on a
• 15:24
  Speaker 5: chat right now to imagine a car, you would come
• 15:27
  Speaker 5: up with an image in your head of a car.
• 15:29
  Speaker 5: Some of you guys would imagine a two door car,
• 15:31
  Speaker 5: a four door car, a sports car. Some of y'all
• 15:34
  Speaker 5: might even imagine a semi truck. Now, what I did
• 15:36
  Speaker 5: is I just prompted you to create something from the
• 15:39
  Speaker 5: prompt that I gave you. You're using your human imagination to
• 15:42
  Speaker 5: create something from an idea of it. And so generative
• 15:45
  Speaker 5: AI is teaching machines how to think and act more
• 15:48
  Speaker 5: along the lines of a human imagination. And I'm gonna
• 15:51
  Speaker 5: get a little bit technical just so you guys understand
• 15:54
  Speaker 5: some of the differences between the techniques used to build
• 15:57
  Speaker 5: AI and AI itself. So how do you teach a
• 16:01
  Speaker 5: machine how to think and act like a human? Well,
• 16:03
  Speaker 5: that's where the term machine learning comes in. You've probably
• 16:06
  Speaker 5: heard this a lot. Machine learning is the most popular
• 16:09
  Speaker 5: way that people teach machines how to think and act
• 16:12
  Speaker 5: like humans, but it's not the only way or the
• 16:14
  Speaker 5: only method. And machine learning is when you teach a machine,
• 16:17
  Speaker 5: which they call training, how to complete a task by
• 16:20
  Speaker 5: giving it examples which they call training data of that
• 16:24
  Speaker 5: task so that it can learn and improve itself on
• 16:27
  Speaker 5: how to do that task right. So, for example, if
• 16:30
  Speaker 5: I wanted to teach a car how to drive on
• 16:32
  Speaker 5: the road, if it was old school coding without machine learning,
• 16:36
  Speaker 5: I'd have to code every single step that the car
• 16:38
  Speaker 5: needed to do well. A lot of those rules are
• 16:42
  Speaker 5: you know, there's like millions of rules of driving, like
• 16:45
  Speaker 5: to have the code like if your right tire gets
• 16:48
  Speaker 5: within this many inches of the line, then move this
• 16:51
  Speaker 5: steering will you know point two centimeters. That's a lot
• 16:53
  Speaker 5: to learn and a lot to code. We probably wouldn't
• 16:56
  Speaker 5: even be able to make an app that would be
• 16:58
  Speaker 5: able to let the car I liked that it was
• 17:01
  Speaker 5: just take too much code. So instead, with machine learning,
• 17:04
  Speaker 5: we can take a bunch of examples of cars driving
• 17:07
  Speaker 5: on the road. That's why Tesla's have eight cameras. They're
• 17:10
  Speaker 5: constantly capturing that data, and then let it learn from
• 17:14
  Speaker 5: those examples of things that it should do and things
• 17:16
  Speaker 5: that it shouldn't do. So there are two types of
• 17:19
  Speaker 5: machine learning. The first is called supervised machine learning, and
• 17:22
  Speaker 5: supervised machine learning is when you teach a machine how
• 17:25
  Speaker 5: to complete a task by giving it examples of the
• 17:28
  Speaker 5: right answer up front. So an example of this is like,
• 17:31
  Speaker 5: let's say I wanted to teach a computer vision algorithm
• 17:35
  Speaker 5: to be able to tell the difference between a strawberry
• 17:39
  Speaker 5: and avocado. Right, I would give it examples of images
• 17:43
  Speaker 5: that I knew upfront were a strawberry. I would tell
• 17:45
  Speaker 5: it upfront that it's a strawberry. We called it that
• 17:48
  Speaker 5: data labeling, and then I would check it as it's
• 17:51
  Speaker 5: learning how good it gets at telling me that's a
• 17:54
  Speaker 5: strawberry versus telling me that's an avocado. Right. So again,
• 17:58
  Speaker 5: supervised machine learning is already know what the right answer
• 18:01
  Speaker 5: is up front, So I'm gonna give you these examples
• 18:04
  Speaker 5: and then I'm gonna test you against how well you're
• 18:06
  Speaker 5: learning how to do the task, because I already know
• 18:08
  Speaker 5: the right answer. The second type of AI machine learning
• 18:12
  Speaker 5: is called unsupervised machine learning, and this is when you're
• 18:15
  Speaker 5: training a machine how to complete a task by getting
• 18:18
  Speaker 5: given it examples, but you're letting the algorithmic self discover
• 18:22
  Speaker 5: what the right answer is. Right, So you're giving it
• 18:25
  Speaker 5: a whole bunch of data, and then it goes in
• 18:27
  Speaker 5: and finds patterns across that data that it uses to
• 18:30
  Speaker 5: give you the right answer. So, for example, a lot
• 18:33
  Speaker 5: of AI is being used in things like drug discovery,
• 18:37
  Speaker 5: So how can we find a new medicine to treat
• 18:39
  Speaker 5: AIDS or to treat diabetes, or even when COVID came out,
• 18:42
  Speaker 5: there was a whole effort between a bunch of big
• 18:44
  Speaker 5: tech companies to figure out medicines that could be used
• 18:48
  Speaker 5: as a vaccine. Right, So in that case, they didn't
• 18:51
  Speaker 5: know the right answer up front, but they had a
• 18:53
  Speaker 5: whole bunch of data and then the machine uncovered patterns
• 18:56
  Speaker 5: that help them understand what the right answer should be. Right,
• 19:00
  Speaker 5: all right, So then you have one more thing, which
• 19:02
  Speaker 5: is called deep learning. So deep learning is basically without
• 19:06
  Speaker 5: going into all the math behind it. It's a more
• 19:09
  Speaker 5: complex way of doing machine learning when you have things
• 19:13
  Speaker 5: that are more complicated in their patterns, and so it
• 19:16
  Speaker 5: teaches the algorithms in a way that mimics how neurons
• 19:20
  Speaker 5: fire in the human brain. Right, So machine learning, like
• 19:23
  Speaker 5: if I want to tell the difference between the strawberry
• 19:25
  Speaker 5: and an avocado, that's not a very complex task. But
• 19:28
  Speaker 5: like teaching a plane how to fly itself, like the
• 19:31
  Speaker 5: US Air Force just did, is going to require a
• 19:33
  Speaker 5: lot more complex relationships and a lot more complex understanding
• 19:37
  Speaker 5: and nuance inside of that data and the patterns and
• 19:40
  Speaker 5: how it's supposed to do that task. So they would
• 19:42
  Speaker 5: use something like a deep learning algorithm instead to be
• 19:46
  Speaker 5: able to capture that. Now, I know that was a
• 19:48
  Speaker 5: lot of information. I don't expect y'all to have this memorized.
• 19:51
  Speaker 5: So while before we move on to the next part,
• 19:53
  Speaker 5: I made a little TLDR slide for y'all. You know,
• 19:56
  Speaker 5: take a moment, take a screenshot, make sure to share
• 19:58
  Speaker 5: this with your friends that just reac perhaps what I
• 20:01
  Speaker 5: just covered X quick question.
• 20:02
  Speaker 2: When we're talking about GBT, which is generative pre trained transformers,
• 20:08
  Speaker 2: most people just hear chat GBT, and that's what the
• 20:10
  Speaker 2: acronym stands for. Is it encompassing all three? Is it
• 20:14
  Speaker 2: encompassing supervised, unsupervised and deep learning? Because when you're talking
• 20:18
  Speaker 2: about figuring out equations, I remember when it first was
• 20:22
  Speaker 2: able to pass you know, a high school exam and
• 20:25
  Speaker 2: ap exam, right, and then it kept learning, kept learning.
• 20:28
  Speaker 2: Then I was able to pass a graduate school final.
• 20:31
  Speaker 2: Then it was able to pass the bar. So it's learning,
• 20:34
  Speaker 2: it's not given the task, it's not it's untrained, but
• 20:37
  Speaker 2: some prompts are trained.
• 20:38
  Speaker 1: Where where would GBT fit in that category?
• 20:41
  Speaker 5: So CHAD GBT is a type of deep learning. And
• 20:44
  Speaker 5: then sometimes they have what's called reinforcement learning, which is
• 20:47
  Speaker 5: where it learns as it interacts with humans. But CHAD
• 20:49
  Speaker 5: GBT in particular is based on something called a transformer architecture.
• 20:54
  Speaker 5: So this is the way that like CHAD GBT works. Basically,
• 20:57
  Speaker 5: you get a large corpus of texts. So like you know,
• 21:00
  Speaker 5: they're complaining, Oh, they scraped the whole Internet and stuck
• 21:02
  Speaker 5: it inside of chad GPT, and they like took copyrighted
• 21:05
  Speaker 5: books and movies, et cetera. They got together a big
• 21:08
  Speaker 5: corpus of texts, right, So gigabytes and gigabytes upon terra
• 21:12
  Speaker 5: pts of text data. And then what they did is
• 21:15
  Speaker 5: they fed that into the system. And the first thing
• 21:18
  Speaker 5: that that system does is it starts to go across
• 21:21
  Speaker 5: the text and create these webs of understanding. And so
• 21:25
  Speaker 5: what it does is it'll say, like, oh, for the
• 21:27
  Speaker 5: like let's say it's a bunch of fairy tale books, right,
• 21:29
  Speaker 5: It'll say, oh, for the concept of royalty, we have
• 21:33
  Speaker 5: the words prince, princess castle, we have the words like
• 21:38
  Speaker 5: I don't know, like mote, you know, holiday, ball, Cinderella, right, Like,
• 21:43
  Speaker 5: it'll start to associate certain words with certain themes, and
• 21:48
  Speaker 5: those are called embeddings, right, and the machine is generating
• 21:51
  Speaker 5: these on their own. It's the first step of creating
• 21:53
  Speaker 5: like a CHADGBT. And then what happens is when you
• 21:57
  Speaker 5: go in and you create a prompt, right, so you
• 22:00
  Speaker 5: ask it something, what it does is it takes your
• 22:03
  Speaker 5: prompt and it converts it into math. You might have
• 22:06
  Speaker 5: heard this referred to as a token, and so it
• 22:09
  Speaker 5: converts your actual text into a mathematical representation of that text.
• 22:14
  Speaker 5: Because the way that the embeddings are stored or how
• 22:17
  Speaker 5: it understands language is actually stored using math. It's not
• 22:21
  Speaker 5: like a literal web where you could go like royalty
• 22:23
  Speaker 5: means princess. It's like some crazy hash and then is
• 22:27
  Speaker 5: related to these other hash numbers. Right. So then when
• 22:30
  Speaker 5: it takes your prompt and it converts it into text,
• 22:33
  Speaker 5: what it does is it does this really complex calculation
• 22:38
  Speaker 5: to guess what words should come next based on what
• 22:41
  Speaker 5: words came before, based on how those embeddings are inside
• 22:45
  Speaker 5: of his database. So I'll give you an example of this.
• 22:48
  Speaker 5: Let's say you don't speak a lick of Spanish at all. Right,
• 22:50
  Speaker 5: you don't understand Spanish at all, but you've maybe watched
• 22:53
  Speaker 5: a TV show once or twice, and you know that
• 22:56
  Speaker 5: when somebody says o la, you're supposed to say como
• 22:59
  Speaker 5: a stas, Right, And so someone comes up to you
• 23:02
  Speaker 5: and they say, oh lah, you think the most likely
• 23:04
  Speaker 5: response is probably como estas. But then if I go
• 23:07
  Speaker 5: deeper and I say donde edes and you you've never
• 23:11
  Speaker 5: heard that before, you gonna make up a response like
• 23:13
  Speaker 5: your ketto taco bell or say something that they don't have. Yeah,
• 23:18
  Speaker 5: because you don't unders, you don't understand the underlying language
• 23:21
  Speaker 5: and that's literally how chat GPT works. There's a research
• 23:24
  Speaker 5: paper called chat GPT is Bullshit, which literally talks about
• 23:28
  Speaker 5: the fact that all of these large language models based
• 23:30
  Speaker 5: on the transformer architecture literally do not understand language. They
• 23:35
  Speaker 5: don't actually understand the words that you're saying. They're just
• 23:38
  Speaker 5: really good math guessing engines because they have like a
• 23:42
  Speaker 5: lot of examples in this case of like maybe they've
• 23:44
  Speaker 5: watched a whole bunch of Spanish and memorized like what
• 23:47
  Speaker 5: people said and how they responded, but they don't actually
• 23:50
  Speaker 5: understand what they're saying, and so what that creates the
• 23:53
  Speaker 5: risk of is what we call hallucination. So if I
• 23:56
  Speaker 5: say donde edis and you say your ketto taco bell,
• 23:59
  Speaker 5: that's like the equivalent of a hallucination where you say
• 24:01
  Speaker 5: something that doesn't make sense or you make up something
• 24:04
  Speaker 5: that isn't factually true. And hallucinations inside of large language
• 24:08
  Speaker 5: models can happen at any point, right, Like, you cannot
• 24:12
  Speaker 5: get rid of hallucinations inside of large language models, so
• 24:15
  Speaker 5: they're always gonna make shit up. And an example it
• 24:17
  Speaker 5: is when Google dropped their AI overview, there was a
• 24:21
  Speaker 5: bunch of like funny screenshots of like how it was
• 24:25
  Speaker 5: making up answers and someone asked it like, yo, how
• 24:27
  Speaker 5: many rocks should a human eat? A data like keep
• 24:30
  Speaker 5: a balanced diet, and it was like, according to a
• 24:32
  Speaker 5: research study at U see Berkeley, humans should you know,
• 24:35
  Speaker 5: eat five rocks every day? And like that doesn't exist.
• 24:38
  Speaker 5: But again, it doesn't understand how harmful that is because
• 24:41
  Speaker 5: it doesn't actually understand the language. So two things. Whenever,
• 24:45
  Speaker 5: just general tips, whenever you're using a large language model
• 24:49
  Speaker 5: like chad, GPT, Gemini, Perplexity, Claude, any of these things,
• 24:54
  Speaker 5: you want to be careful when you're using it in
• 24:56
  Speaker 5: a fact based scenario. So if you're like plugging in
• 24:59
  Speaker 5: your company the data and asking chat GPT questions about it,
• 25:02
  Speaker 5: there's always a chance that it could make up an
• 25:04
  Speaker 5: answer that's not actually inside the data. So when you're
• 25:08
  Speaker 5: using these llms inside of these contexts, you want to
• 25:11
  Speaker 5: always trust, but verify, like double check and make sure
• 25:14
  Speaker 5: that it's given the right answer.
• 25:17
  Speaker 3: There you have it, ladies and gentlemen, Oh yeah, you know.
• 25:24
  Speaker 5: So if you guys want to dive deeper into those concepts,
• 25:26
  Speaker 5: I have a free AI course that I launched in
• 25:28
  Speaker 5: twenty twenty that goes a little bit deeper into some
• 25:30
  Speaker 5: of those mechanics. You guys can feel free to tap
• 25:33
  Speaker 5: into that for sure.
• 25:34
  Speaker 1: There you have it.
• 25:35
  Speaker 4: Okay, let's reset the room, hit the like button, and shit.
• 25:40
  Speaker 4: I mean this is information that literally you can learn
• 25:43
  Speaker 4: in college, high level information like high high level colleges,
• 25:46
  Speaker 4: not just your community college, and those schools cost a
• 25:49
  Speaker 4: lot of money. So it's free tonight just because we want.
• 25:53
  Speaker 4: We want to help you guys learn, and we want
• 25:56
  Speaker 4: to learn ourselves too, So I think it's very important
• 25:59
  Speaker 4: that we have that level of appreciation to our guests
• 26:01
  Speaker 4: absolutely for coming and providing information, but also the only
• 26:06
  Speaker 4: thing we ask you, guys is to share it. Twenty
• 26:08
  Speaker 4: two hundred people, that's great, but let's get it up
• 26:10
  Speaker 4: to three thousand. Let's shed this out to your friends,
• 26:13
  Speaker 4: your family. It's very important information, man. You know, we
• 26:15
  Speaker 4: we gossip on social media so much, but this is
• 26:18
  Speaker 4: actually more important than trending.
• 26:20
  Speaker 1: Topics, any topic.
• 26:23
  Speaker 4: So now we're going to go into Okay, let's get
• 26:26
  Speaker 4: into how we can actually make money. There's a lot
• 26:28
  Speaker 4: of entrepreneurs in here, so let's let's talk about that.
• 26:34
  Speaker 1: If we can.
• 26:35
  Speaker 5: Yeah, So the question is, how can you use AI right,
• 26:40
  Speaker 5: and so I came prepared, I got the debt ready
• 26:42
  Speaker 5: for these questions for y'all. And so there are three
• 26:45
  Speaker 5: ways that you can use AI, whether that's in your
• 26:47
  Speaker 5: business or in your personal life. The first is task
• 26:50
  Speaker 5: specific tools. So if there's a specific thing that you're
• 26:54
  Speaker 5: trying to do and create, there's probably an AI for that.
• 26:58
  Speaker 5: And in a chat I'm a drop of website where
• 27:00
  Speaker 5: you can go find an AI that can basically do anything.
• 27:03
  Speaker 5: The second is through AI enabled platforms, so platforms that
• 27:07
  Speaker 5: are specifically built to help you, you know, whether it's
• 27:11
  Speaker 5: operate your whole business or manage a lot of tasks
• 27:14
  Speaker 5: at once, that use AI in that. And the third
• 27:16
  Speaker 5: is around using AI to amplify your genius. So first
• 27:19
  Speaker 5: let's talk about these task specific tools, right. So, if
• 27:22
  Speaker 5: you're looking at marketing your business, right, you want to
• 27:25
  Speaker 5: use AI to identify and engage your customers. There's a
• 27:28
  Speaker 5: couple of different ways you can use AI for that.
• 27:30
  Speaker 5: The first is around content creation. You can accelerate the
• 27:33
  Speaker 5: development of either text, audio, or video content to promote
• 27:37
  Speaker 5: your business. Right. So, whether that's yo, I'm trying to
• 27:40
  Speaker 5: come up with a new jingle to put behind you know,
• 27:43
  Speaker 5: my advertisement, you could pull a bbl jizzy and use
• 27:46
  Speaker 5: Asuno or an udio to do that. If you're looking
• 27:49
  Speaker 5: for creating images of people stock photos without having to
• 27:53
  Speaker 5: pay for them, you can use free tools like mid
• 27:56
  Speaker 5: Journey or free tools like Dolly or a number of
• 27:59
  Speaker 5: websites that allow you to generate images for free. If
• 28:03
  Speaker 5: you're looking at trying to advertise to your customers, right, so,
• 28:07
  Speaker 5: like customizing those ad campaigns, what I recommend for this
• 28:10
  Speaker 5: is that when you're doing advertising and you want to
• 28:14
  Speaker 5: personalize it to your customers or find the right audience,
• 28:18
  Speaker 5: all of these big advertising platforms have now in the
• 28:22
  Speaker 5: last like six seven months, have now dropped AI audience features, right, So,
• 28:27
  Speaker 5: whether that's TikTok advertising, whether that's Facebook Meta advertising, whether
• 28:32
  Speaker 5: that's Google advertising, they have these features that do cost
• 28:35
  Speaker 5: a little bit more, but they use AI to identify
• 28:39
  Speaker 5: the exact people that you need to advertise to based
• 28:42
  Speaker 5: on your campaign. And they'll start off maybe the first
• 28:45
  Speaker 5: day testing that out, and as they get people using,
• 28:48
  Speaker 5: you know, responding to the ads positively, they keep adjusting
• 28:52
  Speaker 5: in real time who they're targeting your ad campaign to.
• 28:56
  Speaker 5: So I recommend using those features they are. They do
• 28:59
  Speaker 5: cost a little bit more, but it's much better for
• 29:01
  Speaker 5: you to spend that money up front and guarantee that
• 29:04
  Speaker 5: it's going to reach the right people versus you spending
• 29:06
  Speaker 5: money running a campaign trying to figure it out and
• 29:09
  Speaker 5: manually adjust it that could end up costing you a
• 29:11
  Speaker 5: lot more moving forward. And the third thing is around sentiment, right.
• 29:16
  Speaker 5: So sentiment is essentially how people feel, and they measure
• 29:19
  Speaker 5: that through text. So if you're a company that has
• 29:22
  Speaker 5: a review based business, right, like let's say you got
• 29:24
  Speaker 5: Google Reviews, or you have Yelp reviews, et cetera. All
• 29:28
  Speaker 5: of those platforms that let you put all your reviews
• 29:31
  Speaker 5: in one place and like review and manage all of them,
• 29:34
  Speaker 5: they all have what are called sentiment analysis tools. So
• 29:37
  Speaker 5: they'll take that review that somebody left on your Google
• 29:40
  Speaker 5: reviews or on your Yelp or you know whatever other
• 29:44
  Speaker 5: sites that you're on, and they'll analyze it and say
• 29:47
  Speaker 5: this was a positive review, this was a negative review,
• 29:50
  Speaker 5: or this was a neutral review.
• 29:51
  Speaker 3: Right.
• 29:51
  Speaker 5: You can also do that a lot of social media
• 29:54
  Speaker 5: platforms like HubSpot and stuff like that have that in
• 29:57
  Speaker 5: terms of your comments. So are your comments on your
• 30:00
  Speaker 5: social media pages positive, negative, or neutral. And what that
• 30:03
  Speaker 5: can help you do when you plug that in or
• 30:05
  Speaker 5: use those actual features is help you understand. Okay, here
• 30:09
  Speaker 5: are ten negative reviews. Even if the review had four
• 30:12
  Speaker 5: stars or five stars, it could still tell you based
• 30:15
  Speaker 5: on the content if the review is positive or not.
• 30:17
  Speaker 5: That lets you go in and see where you can
• 30:19
  Speaker 5: improve as a business as well as where you're actually
• 30:22
  Speaker 5: doing well as a business. So again, these things are
• 30:25
  Speaker 5: tools that are built into platforms right Like Canva has
• 30:28
  Speaker 5: an AI content generation tool, TikTok just launched their like
• 30:33
  Speaker 5: digital avatar creation studio, Meta and Google inside their advertising
• 30:37
  Speaker 5: platforms have like image and video generation tools built in.
• 30:42
  Speaker 5: So as you're thinking about how to market to your customers,
• 30:45
  Speaker 5: think about creating content for your marketing campaigns, effectively reaching
• 30:50
  Speaker 5: audiences with your ads, and then also using sentiment to
• 30:54
  Speaker 5: give you information about your business back and forth.
• 30:58
  Speaker 2: Yeah, it's funny that you brought up upside because as
• 31:00
  Speaker 2: you were talking, I'm thinking aboutself. The companies that have
• 31:03
  Speaker 2: a big base inside the CRM space. Number one, job
• 31:08
  Speaker 2: creation inside of them, or fear of job creation for
• 31:11
  Speaker 2: some people is like, all right, that industry is going
• 31:13
  Speaker 2: to be disrupted, but it's only going to be disruptive
• 31:16
  Speaker 2: if you're not using it along with right a human
• 31:19
  Speaker 2: and the AI. So talk about how businesses that use
• 31:22
  Speaker 2: customer relations management how this can be super beneficial because
• 31:25
  Speaker 2: I see it as the wave of the future for it.
• 31:27
  Speaker 5: Yeah, one hundred percent. So I said this on stage
• 31:30
  Speaker 5: and invest Fest. I'll say it again. It's not going
• 31:32
  Speaker 5: to be an AI that takes your job. It's going
• 31:34
  Speaker 5: to be a human that's using AI that's going to
• 31:36
  Speaker 5: take your job. And So when you're thinking about customer
• 31:39
  Speaker 5: relationship management systems, whether you're using a Salesforce, whether you're
• 31:43
  Speaker 5: using like a Nimble CRM, if you're using like a HubSpot,
• 31:47
  Speaker 5: if you're using like a Zoho to be able to
• 31:50
  Speaker 5: like track your customers, there are softwares out there that
• 31:54
  Speaker 5: have things what they call lead scoring right, so like
• 31:58
  Speaker 5: AI generated lead scoring. So if you're using maybe you're
• 32:02
  Speaker 5: doing like cold sales or code calls, or you're like
• 32:05
  Speaker 5: collecting customer leads, these types of plugins inside of your
• 32:09
  Speaker 5: CRM systems use AI to help you understand who is
• 32:13
  Speaker 5: the best potential lead for what you're doing. There's a
• 32:16
  Speaker 5: platform it's called Sense eight. I believe it is. I
• 32:19
  Speaker 5: have to look it up once we go through this
• 32:21
  Speaker 5: presentation and I'll drop a link to it. But it
• 32:25
  Speaker 5: cause like HubSpot's version of that is like supersed, like
• 32:28
  Speaker 5: a thousand dollars a month. Right, There's this platform called
• 32:31
  Speaker 5: sense eight that offers like predictive lead scoring based on
• 32:34
  Speaker 5: your CRM, based on your communication with them, based on
• 32:38
  Speaker 5: your preferences and what you say is like your ideal customer,
• 32:41
  Speaker 5: and they offer like a three month free trial and
• 32:43
  Speaker 5: then after that it's like four or five hundred dollars
• 32:46
  Speaker 5: a month. So it's much cheaper than what's built into HubSpot,
• 32:49
  Speaker 5: and it can plug into HubSpot and pull your data.
• 32:52
  Speaker 5: So I think a few different ways that you can
• 32:55
  Speaker 5: use it. I think using predictive lead scoring is important,
• 32:57
  Speaker 5: but also you know, as we talk about conversational AI,
• 33:01
  Speaker 5: this is another area where you can use AI to
• 33:04
  Speaker 5: communicate with those customers that are in your CRM on
• 33:07
  Speaker 5: your behalf. Right, So when you're thinking about like let's
• 33:10
  Speaker 5: say information management, right, Let's say that you got customers
• 33:15
  Speaker 5: who might have commonly asked questions or your startup and
• 33:18
  Speaker 5: you've taken investment money and your investors are going to
• 33:21
  Speaker 5: have questions about your attraction or even your staff, as
• 33:24
  Speaker 5: you're bringing new people in and there's ways of doing
• 33:26
  Speaker 5: things and they may not remember everything from the chaining.
• 33:29
  Speaker 5: You could set up chat bots that can interact with
• 33:33
  Speaker 5: these different groups of people and provide them information. So
• 33:36
  Speaker 5: for customers, a very low level type of chatbot without
• 33:39
  Speaker 5: you having a like turn on chat GBT and use
• 33:41
  Speaker 5: it in your business. There are these things called faq bots, right,
• 33:45
  Speaker 5: so if you already have like a frequently asked questions
• 33:48
  Speaker 5: about your business, you can plug it in to one
• 33:50
  Speaker 5: of these chat bots. Actually, Microsoft has one for free
• 33:53
  Speaker 5: called qn A Maker, and you can plug it in
• 33:56
  Speaker 5: and it'll take your Q and A and it'll automatically
• 33:59
  Speaker 5: make a chat boy. You can just plug into your
• 34:01
  Speaker 5: website completely free, so people can ask questions about your
• 34:04
  Speaker 5: cancelation policy, your business, about where you're at. And like
• 34:08
  Speaker 5: Q and A Maker isn't just for you to like
• 34:10
  Speaker 5: take the literal FAQ section, you could plug all the
• 34:13
  Speaker 5: content about your website in that. If you're talking about
• 34:16
  Speaker 5: internal operations, right, Like, let's say you have a I
• 34:19
  Speaker 5: don't know, like a like a customer service associate role
• 34:22
  Speaker 5: and you don't want them asking you ninety questions about
• 34:24
  Speaker 5: when and when not to give a discount or give
• 34:26
  Speaker 5: a customer a refund. You could create like a Q
• 34:29
  Speaker 5: and a bot for that and make it so that
• 34:31
  Speaker 5: your internal employees can use it. Same thing with like
• 34:34
  Speaker 5: the Investor Metrics, and again Q and a Maker is
• 34:36
  Speaker 5: one hundred percent free tool. There's a whole bunch of
• 34:39
  Speaker 5: tools out there that are like this that you can use.
• 34:42
  Speaker 5: The second piece where you can use kind of chatbot
• 34:44
  Speaker 5: specifically is around time management, so being able to automate
• 34:48
  Speaker 5: the setup and management of appointments, meetings, and bookings. Right, So,
• 34:51
  Speaker 5: if you're a service based business, like let's say you
• 34:54
  Speaker 5: provide you know, finance consultations or credit consultations, or you
• 34:58
  Speaker 5: provide literal services like hey, I'm gonna come give you
• 35:01
  Speaker 5: a haircutter, I'm gonna come put your lashes on. Instead
• 35:03
  Speaker 5: of you having to do all of that communication back
• 35:06
  Speaker 5: and forth through text, through WhatsApp, through messenger, through like
• 35:09
  Speaker 5: Instagram DM you know what I'm saying, where you're like
• 35:12
  Speaker 5: going across ten different things and trying to remember when
• 35:15
  Speaker 5: people are coming and adding it to a calendar. Just
• 35:17
  Speaker 5: grab a booking chatbot. These chat bots automatically communicate with
• 35:21
  Speaker 5: people they manage your availability. As soon as somebody books
• 35:24
  Speaker 5: an appointment, you can make them pay before they book
• 35:26
  Speaker 5: if you have a deposit, and then it automatically puts
• 35:29
  Speaker 5: it on your calendar, and then it automatically sends the
• 35:32
  Speaker 5: people like the email of like, hey, your appointment's coming up,
• 35:34
  Speaker 5: do you want to reschedule or cancel? And then like
• 35:37
  Speaker 5: if they don't show up, you getta keep the deposit,
• 35:39
  Speaker 5: you know what I'm saying, Like that stuff can all
• 35:41
  Speaker 5: be done in one software as opposed to you doing
• 35:45
  Speaker 5: it through fifty different things. And there are versions of
• 35:47
  Speaker 5: these kind of like booking chat bots that even accept
• 35:50
  Speaker 5: payments and things like cash app or Vemo, and so
• 35:53
  Speaker 5: you know, you can go find those tools out there.
• 35:55
  Speaker 5: They're a little like you know, booking and scheduling bots
• 35:58
  Speaker 5: or even plugins for like the Shopify chatbot that they have.
• 36:01
  Speaker 5: There's a plugin you can get that does that to
• 36:04
  Speaker 5: really streamline that part of your business and open your
• 36:06
  Speaker 5: time back up. And the last part is around process automation,
• 36:10
  Speaker 5: So use an AI to complete task that would normally
• 36:12
  Speaker 5: require human effort. Right, So, if you know that you're
• 36:16
  Speaker 5: gonna have to look at your CRM and see the
• 36:20
  Speaker 5: open leads and send them all an email. Then you
• 36:23
  Speaker 5: could use you know, like a zap year or like
• 36:25
  Speaker 5: a make which are these tools that let you do
• 36:28
  Speaker 5: like plug in one tool and create little custom rules
• 36:31
  Speaker 5: like if the person's lead is open and I haven't
• 36:35
  Speaker 5: emailed them in the last seven days, then send them
• 36:37
  Speaker 5: an email, right, And you could use AI to generate
• 36:40
  Speaker 5: those emails so you don't have to write. So you
• 36:42
  Speaker 5: could add a little step in its like go to
• 36:45
  Speaker 5: chat GPT and generate a personalized follow up email then
• 36:48
  Speaker 5: send that email. So you can use AI, especially in
• 36:51
  Speaker 5: conversation AI these chat boys, these large language models to
• 36:54
  Speaker 5: help you automate those processes as well. And finally, when
• 36:58
  Speaker 5: you're thinking about operation, right, you think about wanting to
• 37:02
  Speaker 5: use AI to accelerate or stabilize those tasks that you
• 37:05
  Speaker 5: have to do day to day. Is a business to
• 37:07
  Speaker 5: be able to survive, So the first part is around
• 37:09
  Speaker 5: data analysis, being able to understand patterns across your data
• 37:13
  Speaker 5: or create visualizations of data. There's a tool out there
• 37:17
  Speaker 5: called Gamma, and Gamma is a presentation AI tool, right,
• 37:21
  Speaker 5: And so if you are someone who's like me, like
• 37:23
  Speaker 5: as nice as this deck kind of looks y'all, this
• 37:26
  Speaker 5: is about as good as it gets for me. I
• 37:27
  Speaker 5: can't design, I cannot draw. I could code a AI
• 37:31
  Speaker 5: to do it for me, but me and my like
• 37:33
  Speaker 5: pitch decks sound terrible. So being able to use Gamma
• 37:36
  Speaker 5: has really changed my life in terms of like creating
• 37:39
  Speaker 5: data visualizations. There's another tool out there, it's called Columns
• 37:43
  Speaker 5: that plugs into your data and automatically creates visualizations and
• 37:47
  Speaker 5: you can customize them. And it's like you can go
• 37:49
  Speaker 5: on one of those websites like app Sumo and get
• 37:52
  Speaker 5: like a lifetime subscription to it. You know what I'm saying,
• 37:55
  Speaker 5: like for like fifty dollars and forever have access to
• 37:58
  Speaker 5: this data visualization tool. And tool also gives you information
• 38:02
  Speaker 5: about the data that you're pulling up or this is
• 38:04
  Speaker 5: where you would plug it into like a chat GPT
• 38:07
  Speaker 5: and ask it questions. Just make sure it's not making
• 38:09
  Speaker 5: nothing up when you do that right, and then you
• 38:12
  Speaker 5: have what we call knowledge minded. So how do you
• 38:14
  Speaker 5: use AI to understand how your business is functioning and
• 38:17
  Speaker 5: your business health? Again, this is going to be inside
• 38:19
  Speaker 5: of the tools you're already using, like like HubSpot or
• 38:24
  Speaker 5: Salesforce CRM. They're already gonna have like AI functions to
• 38:28
  Speaker 5: tell you like, hey, here's a risk score that tells
• 38:31
  Speaker 5: you how you know much of your business is at
• 38:33
  Speaker 5: risk of not closing or like the performance of your employees.
• 38:36
  Speaker 5: So just turning on those kinds of tools and functions
• 38:39
  Speaker 5: that are already in the apps you're using is critical
• 38:41
  Speaker 5: then of course for knowledge sharing, right, So building those
• 38:44
  Speaker 5: internal chatbots, building those internal knowledge based databases, even fine
• 38:49
  Speaker 5: tuning a chat GPT or a version of like you know,
• 38:54
  Speaker 5: Gemini to work specifically on your data, like Moderna just
• 38:58
  Speaker 5: did this with seven hundred and fifty customs GPTs, and
• 39:01
  Speaker 5: so overall you have these three tests, specific kind of
• 39:03
  Speaker 5: tools around using it to you know, identify and engage
• 39:07
  Speaker 5: your customers on how to actually communicate with your customers
• 39:10
  Speaker 5: or your stakeholders on your behalf, So how do you
• 39:13
  Speaker 5: scale yourself? And then around the operations, how do you
• 39:16
  Speaker 5: understand how your business is operating communicate that to other people?
• 39:20
  Speaker 5: And I'll pause there because that's a lot.
• 39:21
  Speaker 2: Of info that was That was a lot I'm taking
• 39:24
  Speaker 2: noteses a lot of info for sure.
• 39:28
  Speaker 4: So let's reset the wroong to my access This is
• 39:32
  Speaker 4: going to be on say this will This will be
• 39:34
  Speaker 4: saved on the channel. You have to go to the
• 39:36
  Speaker 4: live section and see it though, but it will be
• 39:37
  Speaker 4: saved on the channel. Also will be on podcasts outlets
• 39:40
  Speaker 4: as well, So if you want to listen to it,
• 39:43
  Speaker 4: I want to go, you can check it out on podcasts,
• 39:45
  Speaker 4: but this will because you need you need to watch
• 39:46
  Speaker 4: this at least three times. At least three times the
• 39:50
  Speaker 4: master investor is on the check in. Shout out to
• 39:53
  Speaker 4: Ian in the building. Okay, I think we derailed. Did
• 39:58
  Speaker 4: you go through your slides or did.
• 40:00
  Speaker 5: You get have a little bit more for these specifics.
• 40:03
  Speaker 5: So I'm gonna give you a little example. So like
• 40:06
  Speaker 5: you would generate, you use AI to generate marketing with
• 40:09
  Speaker 5: a call to action for people to use your chatbot,
• 40:11
  Speaker 5: like hey, you want your lashes scheduled DM me on Instagram.
• 40:15
  Speaker 5: Because these like chatbots, you can deploy the like Facebook
• 40:18
  Speaker 5: Messenger or into WhatsApp or into Instagram right to like
• 40:21
  Speaker 5: work within those chats. It doesn't have to be just
• 40:24
  Speaker 5: on your website. And then the chatbot was schedule like
• 40:27
  Speaker 5: a sales or a discovery call with a client, then
• 40:30
  Speaker 5: you would use AI to take notes during that call,
• 40:33
  Speaker 5: something like Otter, AI or any of these number of
• 40:36
  Speaker 5: these other tools that people be using, and then it
• 40:38
  Speaker 5: would recommend next steps. Now, let's say you're having a
• 40:41
  Speaker 5: call with the customer, like a potential sales opportunity, or
• 40:45
  Speaker 5: with a customer who might be unhappy. You can do
• 40:48
  Speaker 5: sentiment analysis on those transcripts from the call that you
• 40:51
  Speaker 5: know otter will generate from you to understand how that
• 40:54
  Speaker 5: person feels. So if you're like, Yo, I just had
• 40:56
  Speaker 5: this sales call. I'm not really sure where they stand,
• 40:58
  Speaker 5: you could use AI to give you like that insight
• 41:00
  Speaker 5: and be like, nah, this was more neutral, or hey,
• 41:03
  Speaker 5: this was more positive call. You know what I'm saying
• 41:05
  Speaker 5: to help give you that insight. Another example would be
• 41:08
  Speaker 5: if maybe you're a service based business, you would same thing,
• 41:12
  Speaker 5: use AI to create like a cool jingle or maybe
• 41:14
  Speaker 5: a cool little video to help you with your call
• 41:17
  Speaker 5: to action to use that chatbot. Then the chatbot would
• 41:19
  Speaker 5: book the appointment, and then once the appointment is booked,
• 41:23
  Speaker 5: it would automatically start to like retarget that customer to
• 41:27
  Speaker 5: come back in for another appointment, right like, Hey, you
• 41:30
  Speaker 5: should come in and book another appointment. We haven't seen
• 41:32
  Speaker 5: you in a month, or we haven't seen you in
• 41:34
  Speaker 5: three months, and then as your customers continuously interact, it'll
• 41:39
  Speaker 5: start to learn patterns about them, so it'll know, like, hey,
• 41:42
  Speaker 5: this customer only comes in for pedicures. They never get
• 41:45
  Speaker 5: a manicure, So when we send them like a special
• 41:48
  Speaker 5: deals email, we're gonna send them one for pedicures, right
• 41:52
  Speaker 5: for like ten twenty percent off of pedicures. And so
• 41:55
  Speaker 5: this type of pipeline, especially with like the customer retargeting messaging,
• 42:00
  Speaker 5: is built into tools like send grid. It's built into
• 42:03
  Speaker 5: loyalty tools where customers, like you know, give you your
• 42:06
  Speaker 5: email and then like they leave ratings and they earn points.
• 42:09
  Speaker 5: It's also built into the actual email marketing tools that
• 42:12
  Speaker 5: are out there, so you don't have to go build
• 42:14
  Speaker 5: like a whole recommender engine or personalized system to be
• 42:18
  Speaker 5: able to get to that. And so another thing that
• 42:21
  Speaker 5: you can do when we talked about like AI enabled platforms.
• 42:24
  Speaker 5: So if you can't see right now, I'm at will
• 42:26
  Speaker 5: i AM's FYI campus in downtown LA And FYI is
• 42:31
  Speaker 5: an app that stands for Focus your Ideas and will
• 42:34
  Speaker 5: i Am created it because he wanted a better way
• 42:36
  Speaker 5: to manage creative projects. What I've found in my day
• 42:39
  Speaker 5: to day life where I have an AI consulting company,
• 42:42
  Speaker 5: is that this helps me as well. So the app
• 42:44
  Speaker 5: is one hundred percent free. It's AI enabled to cross
• 42:48
  Speaker 5: everything and let you create and manage projects. Inside of
• 42:51
  Speaker 5: these projects, you can share files, you can add people
• 42:54
  Speaker 5: to them, you can remove people from them. You can
• 42:57
  Speaker 5: have group calls and group chats, so you can set
• 43:00
  Speaker 5: up video calls, they could be audio calls. You have
• 43:03
  Speaker 5: an AI assistant that's built into the app. So like
• 43:06
  Speaker 5: let's say you guys have a chat going on about
• 43:08
  Speaker 5: an idea. You could literally tag fyi dot ai and
• 43:12
  Speaker 5: ask it can you summarize this? Can you summarize what's
• 43:15
  Speaker 5: going on in this chat? Or you could talk to
• 43:17
  Speaker 5: it and ask it, hey, help me generate this new
• 43:19
  Speaker 5: idea like you would talk to a chat GPT or
• 43:22
  Speaker 5: you would talk to a clatter at Gemini. And inside
• 43:25
  Speaker 5: of the app, it has an image generator that's one
• 43:28
  Speaker 5: hundred percent free that you can use. So for me operationally,
• 43:34
  Speaker 5: you know, while I do have a CRM system for
• 43:36
  Speaker 5: certain things, the like day to day tasks or projects
• 43:39
  Speaker 5: or ideas, I operate off of f yi AI because
• 43:42
  Speaker 5: it's one hundred percent free and who don't like free?
• 43:45
  Speaker 5: You feel me?
• 43:46
  Speaker 1: Shout Shout out the will.
• 43:47
  Speaker 2: Shout out to Neil who said he's been using Fyi
• 43:50
  Speaker 2: since he left Investments.
• 43:52
  Speaker 1: Is an amazing app. I've been using it myself. Man,
• 43:56
  Speaker 1: use it with my kids.
• 43:57
  Speaker 2: They were asking some questions about history as but watching
• 44:00
  Speaker 2: the vice presidential debate, So that was pretty cool.
• 44:03
  Speaker 1: Uh you want to yeah question Now I'm gonna let
• 44:08
  Speaker 1: to finish. Let her finish it.
• 44:10
  Speaker 5: Yeah. So last part, how do you use AI to
• 44:13
  Speaker 5: amplify your genius? Now? I did a workshop on this
• 44:16
  Speaker 5: when I was with Van Jones out in Atlanta, but
• 44:19
  Speaker 5: outside of that, I haven't given any win this game,
• 44:21
  Speaker 5: right because this is my game on how I personally
• 44:24
  Speaker 5: interact with like a chat GPT or like a Gemini
• 44:28
  Speaker 5: or like a Claude. Now, I'm coming from this as
• 44:30
  Speaker 5: an angle of like somebody who knows how these systems
• 44:34
  Speaker 5: work on a technical level. So I created a framework
• 44:37
  Speaker 5: for how to write your prompts to be able to
• 44:39
  Speaker 5: get the most out of the AI interaction, but in
• 44:42
  Speaker 5: a way where it's not just spitting out an answer
• 44:45
  Speaker 5: at you, but where it's taking your genius and your
• 44:48
  Speaker 5: thoughts and helping you structure them or and also teaching
• 44:51
  Speaker 5: you along the way. So think about it like this,
• 44:54
  Speaker 5: if I could talk to let's say I have a
• 44:56
  Speaker 5: business plan idea, right, the way chat, GPT is by
• 44:59
  Speaker 5: d any of these large language models is by default
• 45:02
  Speaker 5: is they've got all these data from all over the Internet.
• 45:05
  Speaker 5: And so when you ask it, hey, I want to
• 45:07
  Speaker 5: create like an app for babysitters that connects parents with
• 45:13
  Speaker 5: like background checked babysitters on demand. Right, come write my
• 45:18
  Speaker 5: business plan. It's gonna grab from the randomness of all
• 45:22
  Speaker 5: of that to give you an answer. Now, why would
• 45:25
  Speaker 5: I want to talk to some random person who I
• 45:27
  Speaker 5: don't know the experience and a background that they have,
• 45:31
  Speaker 5: Versus I could turn it into like a business professor
• 45:34
  Speaker 5: at Harvard that has like extensive experience creating these types
• 45:39
  Speaker 5: of services, Like maybe you were the dude who scaled
• 45:42
  Speaker 5: like DoorDash to his first billion dollars, right, and then
• 45:46
  Speaker 5: engage with it in a way where it starts to
• 45:48
  Speaker 5: ask me questions about my idea and then starts to
• 45:51
  Speaker 5: give me an answer based on my idea, not just
• 45:55
  Speaker 5: based on whatever it grabbed out of all those terabytes
• 45:57
  Speaker 5: and terabytes of data you feel me. And so that
• 46:01
  Speaker 5: framework I call Chat in the Hat, right, And I
• 46:04
  Speaker 5: know it's a little funny framework, but it's really to
• 46:07
  Speaker 5: help you learn how to think like an AI, so
• 46:10
  Speaker 5: you can talk to the AI in a way to
• 46:11
  Speaker 5: amplifize your genius. So what does chat and the Hat
• 46:15
  Speaker 5: stand for. It's a three part framework when you're writing your.
• 46:18
  Speaker 4: And this is extremely important ladies and gentlemen. If you
• 46:22
  Speaker 4: didn't pay attention to anything else, which shame on you
• 46:25
  Speaker 4: if you did that, pay attention to this part because
• 46:28
  Speaker 4: this is extremely important. How to actually talk to AI
• 46:33
  Speaker 4: to get the proper response. That's vitally important because you
• 46:37
  Speaker 4: can speak to somebody and it's like a human being,
• 46:39
  Speaker 4: right like I can speak to somebody. You have to
• 46:41
  Speaker 4: be educated enough to ask the question. So how I'm
• 46:44
  Speaker 4: asking the question is going to determine the answer that
• 46:46
  Speaker 4: I'm getting. That's not talked about enough. So what she's
• 46:50
  Speaker 4: about to talk about is actually vitally.
• 46:53
  Speaker 5: Important, especially because when you're talking to a large language
• 46:57
  Speaker 5: model like I mentioned before, it doesn't actually understan what
• 47:00
  Speaker 5: you're saying, so it's not gonna get the gist of it, right.
• 47:03
  Speaker 5: You have to give it the specific instructions that you
• 47:06
  Speaker 5: wanted to execute, and the more specific and the more
• 47:10
  Speaker 5: clear you give it, the more it'll answer in the
• 47:14
  Speaker 5: way that you need it to. But again, it's just
• 47:17
  Speaker 5: taking whatever prompt you give it and calculating based on that.
• 47:20
  Speaker 5: So if you say, write me a business plan about
• 47:22
  Speaker 5: an app for you know, connecting background check babysitters with parents,
• 47:27
  Speaker 5: it's gonna write something. But if I give it first
• 47:30
  Speaker 5: a history, right, and then I give it an attitude
• 47:34
  Speaker 5: how I want it to complete that task, and then
• 47:36
  Speaker 5: I give it a specific instructions on how to complete
• 47:38
  Speaker 5: that task, the conversation is gonna be completely different. So
• 47:42
  Speaker 5: I'm gonna do real quickst breakdown each component of this,
• 47:45
  Speaker 5: and in real time live on the chat, we're gonna
• 47:47
  Speaker 5: make up an idea together, and I'm gonna show you,
• 47:50
  Speaker 5: guys the difference between using just a regular prompt versus
• 47:53
  Speaker 5: the chat and a hat framework you feel me. So, first,
• 47:57
  Speaker 5: what is history? History? Is? You want to tell it
• 47:59
  Speaker 5: the relevant skills and experience that it needs to have
• 48:03
  Speaker 5: to be able to help you accomplish that task. So
• 48:06
  Speaker 5: if I have an idea for app me just talking
• 48:09
  Speaker 5: to chat GPT, I don't know who it could be
• 48:11
  Speaker 5: pulling from versus giving it like, Yo, you're an award
• 48:14
  Speaker 5: winning person in this field who has this specific experience
• 48:18
  Speaker 5: in twenty years of that experience. Right, you want to
• 48:21
  Speaker 5: give it some type of history that it can refer
• 48:24
  Speaker 5: to to pull in that knowledge from all of those
• 48:27
  Speaker 5: terabytes of data to specifically be using the knowledge that
• 48:30
  Speaker 5: you need to complete your task. So, if it's like
• 48:34
  Speaker 5: a social media thing, right, you don't just want to
• 48:37
  Speaker 5: go ask CHADGBT about how to make a viral social campaign.
• 48:41
  Speaker 5: You want CHADGBT to be an expert at generating viral campaigns,
• 48:46
  Speaker 5: like you made a company similar to mine, have fifty
• 48:50
  Speaker 5: million views on TikTok with your funny short videos.
• 48:53
  Speaker 3: Right.
• 48:53
  Speaker 5: Then it kind of puts itself in that framing and
• 48:56
  Speaker 5: starts to think from that lens. Then you want to
• 48:59
  Speaker 5: give it an attitude, which is like, what is the
• 49:00
  Speaker 5: mentality or the vibe that it has while doing the task?
• 49:03
  Speaker 5: Is it helpful? Is it you know play Devil's Advocate?
• 49:07
  Speaker 5: Is it you know? Does it like to ask you
• 49:09
  Speaker 5: questions and teach you how to do it instead of
• 49:11
  Speaker 5: just giving you an answer? Right, So you want to
• 49:14
  Speaker 5: give it like the attitude like how and what the
• 49:16
  Speaker 5: vibe is that it uses when it's thinking about how
• 49:20
  Speaker 5: to do your task. Then you want to give it
• 49:22
  Speaker 5: the actual task, which is you need to specifically tell
• 49:24
  Speaker 5: it what it should do and how it should do it.
• 49:26
  Speaker 5: So it's deep dive into each one of these a
• 49:28
  Speaker 5: little bit more so first with the history. Again, you
• 49:31
  Speaker 5: want to give it that relevant knowledge, experience, and accomplishments
• 49:34
  Speaker 5: that a person would need to actually be useful to
• 49:37
  Speaker 5: you in completing that task. So you say something like
• 49:40
  Speaker 5: you are a you know, award winning business plan developer, right,
• 49:45
  Speaker 5: Like you're a professor at Harvard, Wharton and Stanford in
• 49:49
  Speaker 5: creating startup business plans. Now, Chad GBT does know what
• 49:53
  Speaker 5: these kinds of institutions are, and it's not gonna know that,
• 49:57
  Speaker 5: Like you can't be the chair of business at Harvard
• 49:59
  Speaker 5: Standard and at like Wharton and you see Berkeley all
• 50:03
  Speaker 5: at once. Like it's not gonna know that, but it
• 50:05
  Speaker 5: is gonna understand what it means to be like the
• 50:08
  Speaker 5: chair of business at Stanford or the chair of the
• 50:10
  Speaker 5: business school at Harvard, right, because it has enough data
• 50:13
  Speaker 5: to understand what those specific things are. And then you
• 50:16
  Speaker 5: might want to give us some experience like you have.
• 50:19
  Speaker 5: You know, you have forty years of experience helping startups
• 50:22
  Speaker 5: create business plans. Well, you know you have. You know
• 50:26
  Speaker 5: you were the person who created the original business plan
• 50:29
  Speaker 5: for DoorDash. Because if I'm thinking about sitter as an app,
• 50:32
  Speaker 5: right like this, you know, babysitting connecting app, what's a
• 50:36
  Speaker 5: similar type of service like a DoorDash or a task rabbit, right,
• 50:40
  Speaker 5: Like you wrote the financial models for task rabbit that
• 50:43
  Speaker 5: help them be successful, right, and like you're an expert
• 50:46
  Speaker 5: in creating business plans that like help start up scale
• 50:50
  Speaker 5: and get investment money, because that's my goal. So even
• 50:53
  Speaker 5: just there me giving it those specifics about his history
• 50:57
  Speaker 5: will completely change the way that I'm gonna engaged with
• 51:00
  Speaker 5: this chatbot and the types of answers it's gonna give me,
• 51:03
  Speaker 5: and the type of knowledge is gonna pull out to
• 51:05
  Speaker 5: answer that. Right. So you could also say, like you're
• 51:09
  Speaker 5: an award winning or world renowned expert in this. You
• 51:12
  Speaker 5: have number of years experience developing business plans at these
• 51:16
  Speaker 5: companies you have built or you built this company, or
• 51:19
  Speaker 5: you scaled this thing, or you you know, created this
• 51:23
  Speaker 5: product or this service. So if I flip it and
• 51:25
  Speaker 5: I move to social media like you are the leading
• 51:28
  Speaker 5: expert and creating viral TikTok videos. You have twenty years
• 51:32
  Speaker 5: of experience creating and leading viral campaigns on short form
• 51:37
  Speaker 5: video campaigns on TikTok at like door dash, at uber
• 51:41
  Speaker 5: and at lyft. Right, you literally grew ubers TikTok following
• 51:46
  Speaker 5: from one thousand followers to over ten million, and you've
• 51:49
  Speaker 5: won several awards along the way. Right, So you just
• 51:52
  Speaker 5: start to think about the persona if you could create
• 51:55
  Speaker 5: the perfect person that you would talk to about this,
• 51:57
  Speaker 5: even if some of the details are a little bit
• 51:59
  Speaker 5: of be yes, that's fine, but you wanted to create
• 52:02
  Speaker 5: that perfect person that you want to talk to in
• 52:04
  Speaker 5: person who's going to help you with that task. So
• 52:07
  Speaker 5: that's the history. And then the attitude again, is that energy?
• 52:10
  Speaker 5: Is that mentality and that vibe that you want the
• 52:13
  Speaker 5: AI to take with you while it's responding to you.
• 52:16
  Speaker 5: And that has two components. The first is the style.
• 52:19
  Speaker 5: Is it helpful? Is it curious? Is it critical? Is
• 52:22
  Speaker 5: it more like evaluative? Is it pensive? Is it playing
• 52:25
  Speaker 5: Devil's advocate? Is it challenging? Is it excited? Is it
• 52:29
  Speaker 5: you know, like if you wanted to turn it into
• 52:31
  Speaker 5: like a venture capitalist to like, you know, review your idea.
• 52:35
  Speaker 5: Is it like a skeptic? Right, you want to give
• 52:37
  Speaker 5: it like a style of how it's supposed to be
• 52:40
  Speaker 5: thinking about the answer it gives you back, and then
• 52:43
  Speaker 5: you give it a tone, so like, is it gonna
• 52:45
  Speaker 5: respond in professional language? Is it going to be academic?
• 52:48
  Speaker 5: Is it going to be formal? Informal casual? Humor? Is friendly? Persuasive?
• 52:52
  Speaker 5: Is it going to be urban? Is it going to
• 52:54
  Speaker 5: be targeted at gen Z or gen alpha? Right, So
• 52:57
  Speaker 5: when you're giving it that attitude, you've already giving it
• 53:00
  Speaker 5: the history, so now it knows what knowledge it's pulling from.
• 53:03
  Speaker 5: Now you're just telling it when you give me answers,
• 53:05
  Speaker 5: this how I want the vibe between us to be right.
• 53:09
  Speaker 5: So an example of that would be, like, you are
• 53:10
  Speaker 5: extremely helpful. You love sharing your knowledge to help people
• 53:14
  Speaker 5: create business plans. You have a deep passion for listening
• 53:17
  Speaker 5: to people's ideas and guiding them step by step to
• 53:21
  Speaker 5: create business plans. And then you could add in some
• 53:23
  Speaker 5: more stuff like you prefer to help people learn how
• 53:26
  Speaker 5: to help themselves. So instead of giving the right answer,
• 53:29
  Speaker 5: you give them questions to help them think and come
• 53:33
  Speaker 5: to the right answer for themselves. So the attitude section
• 53:35
  Speaker 5: is typically a little bit shorter, but again it's just
• 53:38
  Speaker 5: telling it all, right, this is who you are, this
• 53:40
  Speaker 5: is how you're gonna step to me. And the last part,
• 53:43
  Speaker 5: which is one of the most important, is the actual task. Right.
• 53:47
  Speaker 5: So the task is the specific details on what you
• 53:50
  Speaker 5: want the AI to do and how you want it
• 53:52
  Speaker 5: to do it. Now, oftentimes we only focus on the method, right,
• 53:56
  Speaker 5: So we'll be like, Yo, I want you to ask
• 53:58
  Speaker 5: me a question and then provide an answer. I want
• 54:00
  Speaker 5: you to explain yourself. I want you to give me
• 54:02
  Speaker 5: positive and negative feedback on this idea, but we don't
• 54:05
  Speaker 5: necessarily get specific enough to tell it the format that
• 54:08
  Speaker 5: we want that in.
• 54:09
  Speaker 4: Right.
• 54:09
  Speaker 5: So if you just tell chat GPT to ask me
• 54:12
  Speaker 5: questions about my idea, it's gonna spit out like twenty
• 54:15
  Speaker 5: questions for you, right, and then it's gonna expect you
• 54:19
  Speaker 5: to answer all of those. So that's very different than
• 54:21
  Speaker 5: saying ask me one to two brief questions at a time,
• 54:25
  Speaker 5: wait for my response, and keep doing that until you
• 54:28
  Speaker 5: get enough information to help me write my business plan.
• 54:32
  Speaker 5: That's gonna have a whole different interaction than if it
• 54:34
  Speaker 5: fits out twenty questions and you don't even know how
• 54:36
  Speaker 5: to answer them, and then it'll mess up the flow
• 54:38
  Speaker 5: of your chat. So you could tell it like, hey,
• 54:40
  Speaker 5: I want this in a list, So, hey, I want
• 54:43
  Speaker 5: a list of five viral TikTok ideas to promote what
• 54:47
  Speaker 5: I'm doing, and I want them to be the strongest,
• 54:49
  Speaker 5: I want them to be funny, right, Or hey, I
• 54:52
  Speaker 5: want this in a table, so it'll literally output it
• 54:54
  Speaker 5: in what looks like an Excel spreadsheet. So I want
• 54:57
  Speaker 5: a table of ideas, and the first column should be
• 55:00
  Speaker 5: the number of the ideas, so one through five. The
• 55:03
  Speaker 5: second column should be a description of the video, the
• 55:06
  Speaker 5: third column should be an explanation of why you think
• 55:09
  Speaker 5: that video will work, and a fourth column will be
• 55:12
  Speaker 5: what you think the cons are of that, and the
• 55:14
  Speaker 5: fifth column will be what you think the pros are
• 55:16
  Speaker 5: of that. Now answer my question. That's a lot different
• 55:19
  Speaker 5: than just spitting out a list of ideas. Now you're
• 55:21
  Speaker 5: getting information in a structured way for you to see
• 55:24
  Speaker 5: how it thinks and why it thinks, so you can
• 55:27
  Speaker 5: tweak it as you go. So an example of the
• 55:29
  Speaker 5: task part would be like right now, you're a meeting
• 55:32
  Speaker 5: with me. I'm trying to create a startup business, a
• 55:35
  Speaker 5: business plan for my startup that will connect like U,
• 55:39
  Speaker 5: that'll connect parents to background check babysitters. First, I'm gonna
• 55:44
  Speaker 5: provide you with ideas that I already have about the
• 55:47
  Speaker 5: business plan. Then you're gonna ask me one to two
• 55:51
  Speaker 5: brief questions at a time about my idea about this app. Uh,
• 55:55
  Speaker 5: you know that we want to build until you have
• 55:57
  Speaker 5: enough information to help us create a comprehensive business plan
• 56:01
  Speaker 5: that will help us get investment from a VC firm.
• 56:04
  Speaker 5: Along the way, you're gonna provide positive and negative feedback. Right,
• 56:09
  Speaker 5: So that's gonna completely changed versus me saying I want
• 56:12
  Speaker 5: you to write me a business plan about an app
• 56:16
  Speaker 5: that connects you know, parents to background check babysitters. Having
• 56:21
  Speaker 5: that conversation versus conversation that's done in this format, in
• 56:25
  Speaker 5: this chat in the hat format is gonna be world's difference.
• 56:29
  Speaker 5: And instead of chat GPT feeding you whatever answer it
• 56:32
  Speaker 5: happens to calculate, it's now going to be taking in
• 56:35
  Speaker 5: your actual genius, your actual ideas, and just helping you
• 56:39
  Speaker 5: expand upon them and structure them in a way that
• 56:42
  Speaker 5: lets you do stuff faster. Now it's not just about
• 56:45
  Speaker 5: writing business plans or coming up with social media ideas.
• 56:49
  Speaker 5: You can do this for like, let's say that you
• 56:52
  Speaker 5: have a sales presentation coming up. You can give it.
• 56:55
  Speaker 5: You're a master salesperson, You're great at creating decks. You're
• 56:58
  Speaker 5: extremely helpful, love helping me. What's gonna happen is I'm
• 57:02
  Speaker 5: going to tell you about my client the things I
• 57:04
  Speaker 5: want to include in my sales deck, and you're gonna
• 57:06
  Speaker 5: help me create an outline for the sales deck. So
• 57:08
  Speaker 5: then it'll do that. Okay, Now I want to deep
• 57:12
  Speaker 5: dive into this slide. For this slide, you know, I
• 57:15
  Speaker 5: want it to be really impacted, you know, really impactful
• 57:18
  Speaker 5: in the story that it tells. To make sure that
• 57:20
  Speaker 5: it's teaching, make sure that my client really walks away
• 57:23
  Speaker 5: understanding how we're the industry leader. Can you generate a
• 57:27
  Speaker 5: table with three different options for text that I should
• 57:30
  Speaker 5: put on this slide, and then it's gonna output that.
• 57:33
  Speaker 5: So now again it's taking your genius and what you
• 57:36
  Speaker 5: already know and what your goals are and just making
• 57:39
  Speaker 5: your workflow faster. But by pulling from this expertise, it
• 57:43
  Speaker 5: is imaginary character that you've created. And so again the
• 57:46
  Speaker 5: chat and a hat framework is around when you create
• 57:49
  Speaker 5: your prompt, you want to create a history. What are
• 57:52
  Speaker 5: the knowledge and skills and expertise that it needs to
• 57:56
  Speaker 5: have to help you with your task? What experience does
• 57:59
  Speaker 5: it have? What company are relevant to the task you're
• 58:01
  Speaker 5: trying to do? That you could say it has experience
• 58:04
  Speaker 5: there you could be like, yo, you were you know
• 58:06
  Speaker 5: the first social media person that you know, frickin' DoorDash ever? Right,
• 58:10
  Speaker 5: And then you want to give it specific accomplishments when
• 58:13
  Speaker 5: you have the a the attitude, it's what kind of
• 58:15
  Speaker 5: vibe does it have when it's helping you? So you
• 58:18
  Speaker 5: think about the style and you think about the tone.
• 58:20
  Speaker 5: So the style is what's the vibe? The tone is
• 58:23
  Speaker 5: what kind of language does it use when it creates
• 58:25
  Speaker 5: the answer for you? And the last part is t
• 58:28
  Speaker 5: or the task, which is how does it respond to you?
• 58:31
  Speaker 3: Right?
• 58:31
  Speaker 5: So you want to tell it exactly what you wanted
• 58:33
  Speaker 5: to do and how you wanted to do it, right,
• 58:35
  Speaker 5: like is it going to ask questions and provide answers?
• 58:38
  Speaker 5: Does it give you positive negative feedback? And even on
• 58:40
  Speaker 5: the format, like what's the structure that it uses when responding.
• 58:44
  Speaker 5: Is it responding to you in a list, is it
• 58:46
  Speaker 5: giving you a table? Is there a certain amount? Is
• 58:48
  Speaker 5: it a paragraph, is it a long answer, a short answer,
• 58:51
  Speaker 5: et cetera. And the more you, guys, will leverage this framework,
• 58:55
  Speaker 5: the more valuable that these tools will become to helping
• 58:59
  Speaker 5: you operate in any element of your business day to
• 59:02
  Speaker 5: day in a way that you'll be the one that's
• 59:06
  Speaker 5: the person using AI that will replace the jobs of
• 59:09
  Speaker 5: the people who are not instead of you hoping that
• 59:14
  Speaker 5: chat GPT gives you some type of answer randomly, or
• 59:16
  Speaker 5: that Claude or Gemini does that'll help you have a
• 59:19
  Speaker 5: competitive edge, because the unique competitive edge is you. And
• 59:23
  Speaker 5: so the chat Nahat framework helps you leverage these large
• 59:27
  Speaker 5: language models in a way where it amplifies your genius
• 59:31
  Speaker 5: alongside AI, instead of expecting AI to somehow make you
• 59:35
  Speaker 5: a genius. You feel me.
• 59:37
  Speaker 1: I feel you. I definitely feel you. When we talk
• 59:39
  Speaker 1: about expert, we'm an expert.
• 59:41
  Speaker 4: That's a million dollars worth of a game right there. Minimum,
• 59:45
  Speaker 4: I said, at least a million dollars worth of game.
• 59:47
  Speaker 4: But I think we're gonna do something some on the
• 59:50
  Speaker 4: flywork are.
• 59:51
  Speaker 5: We let's do it. So I'm gonna do like this,
• 59:54
  Speaker 5: and I'm gonna maybe minimize this and make this bigger.
• 59:57
  Speaker 5: Oh no, I don't want to leave. I just don't
• 59:59
  Speaker 5: want y'all to see a'all all of that. All right,
• 1:00:01
  Speaker 5: So let's go back here. So let's make up an
• 1:00:04
  Speaker 5: example task right now, you guys, maybe in a.
• 1:00:07
  Speaker 4: Yeah, let's do this through the chat, because I don't
• 1:00:09
  Speaker 4: want them to be like, oh, we already thought about this, okay,
• 1:00:13
  Speaker 4: So in the chat.
• 1:00:14
  Speaker 5: Like what we are they have to do.
• 1:00:16
  Speaker 3: They have to come with like a business idea.
• 1:00:18
  Speaker 5: Yeah, just like what like something we'd wanted to do,
• 1:00:21
  Speaker 5: like a business plan for like an e commerce thing
• 1:00:23
  Speaker 5: or like you know, help me come up with viral
• 1:00:25
  Speaker 5: TikTok campaigns for this kind of business. It's something that
• 1:00:28
  Speaker 5: is a specific task, not anything, but a specific task
• 1:00:32
  Speaker 5: you want to see used in this framework, all right?
• 1:00:34
  Speaker 1: All right?
• 1:00:35
  Speaker 3: So type somebody type in the chat, see see what
• 1:00:38
  Speaker 3: they got what.
• 1:00:38
  Speaker 4: You want to see, and we'll do this on real
• 1:00:41
  Speaker 4: time like a magic trick on forty second Street.
• 1:00:46
  Speaker 5: Yo, a wild.
• 1:00:50
  Speaker 2: All right, I've seen one already right here. That sounds
• 1:00:52
  Speaker 2: pretty dopey. They want to help create all this moving
• 1:00:55
  Speaker 2: so fast. A technology recruiting company business plan?
• 1:01:02
  Speaker 1: Oh what? Oh?
• 1:01:03
  Speaker 2: Might put it up shout to my technology recruiting company
• 1:01:06
  Speaker 2: busines plan.
• 1:01:07
  Speaker 4: A technology recruiting company business plan? Is that a good one?
• 1:01:10
  Speaker 5: Yep, let's do it. So we're gonna do this in
• 1:01:12
  Speaker 5: each one, right, So I'm gonna put it here and
• 1:01:14
  Speaker 5: put it here so we could see all the way
• 1:01:16
  Speaker 5: through each one. So what I want to do first
• 1:01:19
  Speaker 5: is I want to show you, guys, what it looks
• 1:01:22
  Speaker 5: like when we have one of these large language models
• 1:01:24
  Speaker 5: generate this without the chat and a hat framework. Right,
• 1:01:27
  Speaker 5: So this is an app that I use. It's only
• 1:01:29
  Speaker 5: available on Mac. It's called think Buddy, and basically you
• 1:01:33
  Speaker 5: pay one fee and you get access to all of
• 1:01:36
  Speaker 5: the AI models that you would want to use. So
• 1:01:38
  Speaker 5: I could use you know, Chat, GPT four point zero, Gemini, Claude,
• 1:01:42
  Speaker 5: et cetera, even Lama just by paying one fee. They
• 1:01:46
  Speaker 5: are working on a mobile app. However, it's not out yet,
• 1:01:50
  Speaker 5: so if you have a Mac, I highly recommend this software.
• 1:01:53
  Speaker 5: You guys just missed out on a lifetime deal. Like
• 1:01:55
  Speaker 5: I paid one hundred and fifty dollars and I have
• 1:01:57
  Speaker 5: forever free access to this app, but the month the subscription.
• 1:02:01
  Speaker 5: Instead of you paying twenty dollars for Chat GBT, then
• 1:02:03
  Speaker 5: twenty dollars for you know, Perplexity, then twenty dollars for
• 1:02:06
  Speaker 5: this one, it's like twenty dollars for this app where
• 1:02:09
  Speaker 5: you get access to all of them unlimited and it
• 1:02:12
  Speaker 5: has like the image generation and stuff like that.
• 1:02:14
  Speaker 3: What's the neighborhood.
• 1:02:15
  Speaker 5: It's called think Buddy, so t A I, n K,
• 1:02:18
  Speaker 5: b U, D D Y and it's Thinkbuddy dot AI.
• 1:02:21
  Speaker 5: So I could drop like a code if you guys
• 1:02:22
  Speaker 5: want to get it, but I have a couple of
• 1:02:24
  Speaker 5: tools I got to drop for y'all. The first is
• 1:02:26
  Speaker 5: the tool that helps you find AI anything. The second
• 1:02:29
  Speaker 5: is the lead scoring and then I'll drop the info
• 1:02:31
  Speaker 5: for think Buddy when I'm done with this demo here.
• 1:02:34
  Speaker 2: Yeah, shout out to Ian and the chat with the
• 1:02:36
  Speaker 2: assistance on that. I appreciate you, bro.
• 1:02:39
  Speaker 5: So what I'm asking it to do right here is
• 1:02:41
  Speaker 5: I'm saying, create a business plan for a technology recruiting company,
• 1:02:44
  Speaker 5: right and this is oh, let's retry uh oh not
• 1:02:50
  Speaker 5: it wants to tank out all right, Let's maybe we
• 1:02:52
  Speaker 5: should use chat GPT. I'm talking all this chat GPT stuff, right,
• 1:02:56
  Speaker 5: and so maybe.
• 1:02:56
  Speaker 4: It's chat GBT is the reliable Yeah, it's a reliable source.
• 1:03:01
  Speaker 1: Can't go wrong with.
• 1:03:03
  Speaker 5: Okay, let me come out of clot. Do it in clot.
• 1:03:08
  Speaker 5: Hold on, y'all, not me trying to promote this and
• 1:03:10
  Speaker 5: then it don't want to work here. Let me change this.
• 1:03:15
  Speaker 1: This is the next level and we're.
• 1:03:17
  Speaker 5: Gonna open it back up. All right now, let me
• 1:03:20
  Speaker 5: test why is it still trying to do it in clot?
• 1:03:24
  Speaker 5: Do I need to update something?
• 1:03:26
  Speaker 1: Huh?
• 1:03:28
  Speaker 5: Is it my app? Let me see? And if not,
• 1:03:31
  Speaker 5: I'll just open up chat GPT and show you all
• 1:03:33
  Speaker 5: the difference. Like literally, I just don't pay for chat
• 1:03:35
  Speaker 5: GPT outside of this, and I've never had this issue
• 1:03:39
  Speaker 5: in here. Let me see. Okay, chat all right, let
• 1:03:44
  Speaker 5: me go back to this one and let's set Okay,
• 1:03:49
  Speaker 5: let's go back. Okay, let's try it again with chat
• 1:03:54
  Speaker 5: GPT for general. Okay, let me try a new chat
• 1:04:00
  Speaker 5: up with the app on my computer because it's not
• 1:04:03
  Speaker 5: letting me do this. So instead of what I'll do
• 1:04:06
  Speaker 5: to save us time, I promise it works, y'all, I
• 1:04:09
  Speaker 5: promise it works, right, So instead what I'll do is
• 1:04:12
  Speaker 5: we'll just go into Claude and try it right now. Right,
• 1:04:15
  Speaker 5: So while I'm in Claude, I'll say, hey, create a
• 1:04:17
  Speaker 5: business plan for a technology recruiting company, and then what
• 1:04:22
  Speaker 5: it'll do is it'll spit out an answer. Right, So
• 1:04:26
  Speaker 5: it starts to immediately answer without understanding what type of
• 1:04:32
  Speaker 5: technology recruiting I want to do, what my market is,
• 1:04:35
  Speaker 5: what my region is, or anything. And it comes up
• 1:04:37
  Speaker 5: with a pretty decent idea. It says, here's an executive summary.
• 1:04:40
  Speaker 5: Didn't even ask me the name of my company. I
• 1:04:42
  Speaker 5: don't know the person in a chat. Would you call
• 1:04:44
  Speaker 5: it tech Talent Solutions? That sound like one of them
• 1:04:46
  Speaker 5: outsourced companies in India.
• 1:04:49
  Speaker 1: That's not a bad name, it's actually not.
• 1:04:51
  Speaker 5: I'm pretty sure if I went to Google that there
• 1:04:53
  Speaker 5: would be one that's called Tech Talent Solutions, right. But
• 1:04:57
  Speaker 5: it says, hey, it's a specialized technology recruiting firm focused
• 1:05:01
  Speaker 5: on connecting top tier tech talent with innovative companies by
• 1:05:04
  Speaker 5: leveraging advanced matching algorithms. So now it already signs you
• 1:05:08
  Speaker 5: up to use AI. So if you weren't planning to
• 1:05:10
  Speaker 5: use AI, eol company, it already signs you up to
• 1:05:13
  Speaker 5: create your own proprietary matching algorithms, right, and then your
• 1:05:17
  Speaker 5: network of professionals. We aim to streamline the hiring process
• 1:05:20
  Speaker 5: for both employers and job seekers in the sector. So
• 1:05:23
  Speaker 5: then it goes into your market analysis, your target market,
• 1:05:26
  Speaker 5: tech startups and scale ups, established technology companies, traditional companies
• 1:05:30
  Speaker 5: undergoing digital transformation. But what happens if you're somebody who
• 1:05:34
  Speaker 5: is a federal technology recruiting company where you're seeking folks
• 1:05:37
  Speaker 5: who have clearances right to be able to place them places,
• 1:05:41
  Speaker 5: and you're looking at primary prime contractors and subcontractors and
• 1:05:46
  Speaker 5: that's actually your audience. Now all of this becomes completely
• 1:05:49
  Speaker 5: useless because it doesn't have any info about you. And
• 1:05:52
  Speaker 5: then the types of candidates. Maybe you've decided that you
• 1:05:54
  Speaker 5: do everything except software engineers, right, or developers like you do,
• 1:05:59
  Speaker 5: technical project managers, you want to do quality analysis, maybe
• 1:06:03
  Speaker 5: you'll do like data analysts, you want to do product managers,
• 1:06:06
  Speaker 5: you want to do UIUX designers. Well, now you're gonna
• 1:06:09
  Speaker 5: have to come in here edit all of this. Then
• 1:06:11
  Speaker 5: it talks about the market size, which again I don't
• 1:06:14
  Speaker 5: know if this fact is true, so I'm gonna have
• 1:06:16
  Speaker 5: to google it, right, And then it has like increasing
• 1:06:19
  Speaker 5: demand due to this, I don't know if any of
• 1:06:21
  Speaker 5: that's true. It's an LLM. I have to go double
• 1:06:24
  Speaker 5: check and then competitive analysis. It doesn't give you any
• 1:06:27
  Speaker 5: specific competitors, right, and then what your advantage is, et cetera.
• 1:06:31
  Speaker 5: So you guys get the idea here. It's spitting out
• 1:06:33
  Speaker 5: something that feels good on the surface, but then it
• 1:06:36
  Speaker 5: doesn't necessarily capture your unique value and what you create.
• 1:06:40
  Speaker 5: So let's go through this framework and actually create something. Right,
• 1:06:43
  Speaker 5: So we want to create a business plan for a
• 1:06:45
  Speaker 5: technology recruiting company. So first we're gonna give it a history.
• 1:06:49
  Speaker 5: We're gonna say you are an award winning, world renowned
• 1:07:10
  Speaker 5: original business plan for what's a big IT staffing firm
• 1:07:17
  Speaker 5: like that actually exists in the world, like one of
• 1:07:19
  Speaker 5: them big recruiting firm.
• 1:07:20
  Speaker 3: Can we look it up. We'll look it up.
• 1:07:22
  Speaker 5: We're looking it up, all right, So I'm gonna add
• 1:07:25
  Speaker 5: that in here. First, one million dollars in revenue to
• 1:07:36
  Speaker 5: over ten million dollars in revenue annually. You are the
• 1:07:43
  Speaker 5: chair of the Harvard Business School and have over twenty
• 1:07:53
  Speaker 5: years experience helping companies develop UH business plans, helping technology
• 1:08:04
  Speaker 5: service companies, service companies develop business plans that that helped
• 1:08:16
  Speaker 5: that drive them to become industry leaders.
• 1:08:21
  Speaker 1: I like that.
• 1:08:22
  Speaker 2: Yeah, the chat is putting. I looked up a center.
• 1:08:25
  Speaker 2: The chat put a censure. We can put a center,
• 1:08:27
  Speaker 2: all right.
• 1:08:28
  Speaker 5: Right, So now I'm just gonna have to go in
• 1:08:30
  Speaker 5: here real quick and make this text just a little
• 1:08:32
  Speaker 5: bit smaller, y'all. So let's go ahead and make this
• 1:08:35
  Speaker 5: a little bit smaller.
• 1:08:37
  Speaker 1: Right.
• 1:08:37
  Speaker 5: So, you are an award winning, world renowned expert at
• 1:08:40
  Speaker 5: creating business plans for technology services companies. You created the
• 1:08:44
  Speaker 5: original business plan for Accenter's recruiting department. You scale them
• 1:08:49
  Speaker 5: from their first million dollars in revenue to over ten
• 1:08:51
  Speaker 5: billion and revenue annually. Now, if I wanted to, I
• 1:08:54
  Speaker 5: can make it one hundred million. I don't really have
• 1:08:56
  Speaker 5: to know if accenter actually makes that much money, right,
• 1:09:00
  Speaker 5: I'm just trying to give it an anecdotal example.
• 1:09:03
  Speaker 1: They said, not a staff in front one of the
• 1:09:06
  Speaker 1: largest India. So are they a staff infirm or no?
• 1:09:09
  Speaker 5: What I said, all right, let's let's do this for
• 1:09:13
  Speaker 5: technology instead of services companies, for technology recruiting companies. Right,
• 1:09:21
  Speaker 5: and so instead, here's how I'm going to change this.
• 1:09:25
  Speaker 5: You created the talents uh, the recruiting department at Accenture,
• 1:09:38
  Speaker 5: where you scaled them from their first million dollars in
• 1:09:43
  Speaker 5: revenue to over ten billion dollars in UH revenue annually.
• 1:09:47
  Speaker 5: Then you spent over a decade at Boston Consulting Group
• 1:09:54
  Speaker 5: where you developed a what are they called head Hunter
• 1:10:01
  Speaker 5: talent recruiting and matching service that you scaled from zero
• 1:10:13
  Speaker 5: zero to over two billion dollars in revenue annually. You
• 1:10:21
  Speaker 5: are the leading expert in developing business plans and strategy
• 1:10:33
  Speaker 5: strategy for technology recruiting companies. Right, so you see how
• 1:10:39
  Speaker 5: I did that. It doesn't matter if like these things
• 1:10:42
  Speaker 5: actually are there. But because I'm not sure if Accenture,
• 1:10:45
  Speaker 5: I know they're a consulting firm, but I don't know
• 1:10:47
  Speaker 5: if they're like a talent recruiting company. I just gave
• 1:10:50
  Speaker 5: it that example. Like you created the recruiting department at
• 1:10:53
  Speaker 5: Accentre where you scared them from their first million in
• 1:10:56
  Speaker 5: revenue to over ten billion in revenue and annually. Then
• 1:10:59
  Speaker 5: you spend over a decade. I'm gonna actually make it
• 1:11:01
  Speaker 5: one billion. Then you spent over a decade at Boston
• 1:11:04
  Speaker 5: Consulting Group where you developed a Headhunter talent recruiting and
• 1:11:07
  Speaker 5: matching service that you scaled from zero to over ten
• 1:11:10
  Speaker 5: billion dollars in revenue annually. Right, you are the leading
• 1:11:14
  Speaker 5: expert in developing business plans and strategy for technology recruiting companies.
• 1:11:18
  Speaker 5: You are the chair of the Harvard Business School and
• 1:11:20
  Speaker 5: have over twenty years experience. Okay, you are the chair
• 1:11:23
  Speaker 5: of the Harvard Business School and have a deep passion
• 1:11:30
  Speaker 5: and I'll just leave it there. I don't have to
• 1:11:32
  Speaker 5: add all this in at the end. You are the
• 1:11:35
  Speaker 5: chair of the Harvard Business School and the leading industry
• 1:11:40
  Speaker 5: expert at helping chech recruiting companies create business plans that
• 1:11:50
  Speaker 5: drive them to become industry leaders. Right now, let's talk
• 1:11:55
  Speaker 5: about this attitude. I'm gonna make this a little bit
• 1:11:57
  Speaker 5: Smaller's getting a little bit verbose here, but the attitude.
• 1:12:02
  Speaker 5: You are extremely helpful. You love sharing your knowledge. You
• 1:12:09
  Speaker 5: love leveraging your knowledge and wisdom, your deep knowledge and wisdom,
• 1:12:18
  Speaker 5: not depth, your deep knowledge and wisdom to help to
• 1:12:24
  Speaker 5: mentor companies, to mentor up and coming tech recruiting companies
• 1:12:34
  Speaker 5: on developing their business plans and strategy. You prefer to
• 1:12:45
  Speaker 5: help people help themselves. You provide positive and negative feedback.
• 1:12:54
  Speaker 5: So let's do this. You prefer to help people help themselves,
• 1:12:58
  Speaker 5: giving insights on how to think about an answer, versus
• 1:13:04
  Speaker 5: giving the answer outright, right, you are especially passionate about
• 1:13:15
  Speaker 5: helping entrepreneurs from underrepresented backgrounds. We're gonna give it a
• 1:13:24
  Speaker 5: savior complex. And so the last piece is, now, what
• 1:13:30
  Speaker 5: do we want it to do and how do we
• 1:13:31
  Speaker 5: want it to do it? Right now, you're meeting with me,
• 1:13:37
  Speaker 5: a person of color who is creating a new technology
• 1:13:44
  Speaker 5: staffing company. I have some ideas for the company I
• 1:13:55
  Speaker 5: want to create, but I'm struggling to develop a business plan. First,
• 1:14:03
  Speaker 5: you'll listen to my ideas about the company before generating
• 1:14:10
  Speaker 5: a response. Then you'll ask me one to two brief
• 1:14:16
  Speaker 5: questions at a time until you have enough information to
• 1:14:25
  Speaker 5: create a business plan that will drive us to success.
• 1:14:34
  Speaker 5: Until you have enough information to yeah, okay. You will
• 1:14:42
  Speaker 5: provide positive and negative feedback along the way so I
• 1:14:48
  Speaker 5: can learn how to write business plans like you. Right,
• 1:14:55
  Speaker 5: that's a long ass prompt. I'm not even gonna.
• 1:14:57
  Speaker 2: Hold you immaculate. I'm just looking at you, thinking of
• 1:15:02
  Speaker 2: it and typing at the same time.
• 1:15:04
  Speaker 1: In itself is f You're brilliance. Right, But that is incredible.
• 1:15:09
  Speaker 5: So with this, what I'm gonna do is I'm gonna
• 1:15:10
  Speaker 5: move these out of the way and I'm gonna copy
• 1:15:14
  Speaker 5: and paste this prompt. Now, I'm not gonna lie to you, guys.
• 1:15:16
  Speaker 5: I have a folder in the notes section in my
• 1:15:19
  Speaker 5: phone called Prompts, and I write out all of my
• 1:15:23
  Speaker 5: prompts in my notes in my phone before I use them.
• 1:15:26
  Speaker 5: And the reason for that is that a lot of times,
• 1:15:28
  Speaker 5: a lot of this language I end up reusing, right,
• 1:15:31
  Speaker 5: So instead of me having to rewrite it every single time,
• 1:15:34
  Speaker 5: I'm able to take it and reuse it. So I'm
• 1:15:36
  Speaker 5: my own little prompt library of how I want to
• 1:15:39
  Speaker 5: do this. So, now, remember when we did this in
• 1:15:42
  Speaker 5: this first section, let me see my old chat. So
• 1:15:44
  Speaker 5: I'm gonna pull this one up and then I'm gonna
• 1:15:46
  Speaker 5: pull Claude back up, right, so we see what it created, right.
• 1:15:50
  Speaker 5: It created this whole business plan with an exit strategy,
• 1:15:53
  Speaker 5: talked about funding requirements without even asking me anything, you
• 1:15:57
  Speaker 5: know what I mean, and it just gave me an answer.
• 1:16:00
  Speaker 5: So now I want to see what it gives me
• 1:16:01
  Speaker 5: when I give it this prompt. Right. So the first
• 1:16:06
  Speaker 5: step it acts like it's me right, It says, I'm
• 1:16:10
  Speaker 5: delighted to meet with you and help you develop a
• 1:16:12
  Speaker 5: successful business plan for your technology staffing company. Your initiative
• 1:16:16
  Speaker 5: is commendable, and I'm excited to hear about your vision.
• 1:16:19
  Speaker 5: As someone who has been in the trenches and scaled
• 1:16:21
  Speaker 5: multiple recruiting businesses, I know firsthand both the challenges and
• 1:16:25
  Speaker 5: immense opportunities in this space. Before we dive into crafting
• 1:16:28
  Speaker 5: your business plan, I'd love to hear your initial thoughts
• 1:16:31
  Speaker 5: and ideas about the company you want to create, what
• 1:16:34
  Speaker 5: inspired you to enter the technology staffing industry, and what
• 1:16:36
  Speaker 5: unique value to believe your company can have in the market.
• 1:16:39
  Speaker 5: Please share your current vision and then we can start
• 1:16:41
  Speaker 5: refining and expanding it together. So I just went from
• 1:16:45
  Speaker 5: you giving me some answer that you pulled out of
• 1:16:47
  Speaker 5: the depths of nowhere to now literally having an expert
• 1:16:51
  Speaker 5: with deep domain expertise getting to where I want to go.
• 1:16:55
  Speaker 5: And I've now turned this into my personal thought partner
• 1:16:58
  Speaker 5: and coach specifically for the task. Do you see the difference?
• 1:17:01
  Speaker 3: So let's for free.
• 1:17:03
  Speaker 4: By the way, like now you have a personal consultant
• 1:17:05
  Speaker 4: as opposed to like you said, you could just get
• 1:17:07
  Speaker 4: the answer but now you actually have a personal consult
• 1:17:10
  Speaker 4: It's gonna take more time, but now you have a
• 1:17:12
  Speaker 4: personal consultant that you can have an ongoing relationship with forever.
• 1:17:18
  Speaker 5: Until you run away, until you run out of prompts.
• 1:17:21
  Speaker 5: Right Like, I'm on the free verse and I told
• 1:17:22
  Speaker 5: you I don't do that here. But there is a
• 1:17:24
  Speaker 5: limit to how much one conversation thread can have and
• 1:17:27
  Speaker 5: I've hit that before and then I just go back
• 1:17:29
  Speaker 5: and reuse the prompt and then pasting.
• 1:17:32
  Speaker 4: If you just have the paid version whatever. But you've
• 1:17:34
  Speaker 4: essentially created a mentor.
• 1:17:36
  Speaker 5: Yeah, so let's let's make up some stuff right now,
• 1:17:40
  Speaker 5: just us on the chat. It's like, Okay, what inspired
• 1:17:42
  Speaker 5: you to enter the technology staffing industry. I'm not answering that.
• 1:17:46
  Speaker 5: What unique value to believe your company can have in
• 1:17:48
  Speaker 5: the market. So I'm gonna just make some shut up
• 1:17:49
  Speaker 5: right now. My company UH is called Recruits. We focus
• 1:17:57
  Speaker 5: on placing cleared, cleared candidates in federal federal contracting positions
• 1:18:11
  Speaker 5: that require security clearance. We specifically we do not focus
• 1:18:18
  Speaker 5: on really technical roles such as software engineers or infrastructure engineers.
• 1:18:32
  Speaker 5: We provide up recruiting for all other roles, all other
• 1:18:40
  Speaker 5: technical roles, including but not limited to, product managers, project managers,
• 1:18:53
  Speaker 5: technical project managers. Let's go knowledge managers, knowledge which is
• 1:19:00
  Speaker 5: like the SharePoint database people database managers. What are some
• 1:19:06
  Speaker 5: other technical roles or non technical but adjacent roles quality assurance?
• 1:19:12
  Speaker 5: What else? What do they call them? Business analysts, et cetera.
• 1:19:18
  Speaker 5: Our unique value proposition is the talent pool that we
• 1:19:24
  Speaker 5: have access to. We work with a number of VA
• 1:19:30
  Speaker 5: vas around the country to retrain veterans getting out of
• 1:19:37
  Speaker 5: the military. We are and approved apprenticeship program by the
• 1:19:46
  Speaker 5: VA and several US states, so we can US states,
• 1:19:54
  Speaker 5: so we get paid to retrain veterans in these specific skills.
• 1:20:02
  Speaker 5: Because of these relationships, we have access to a larger
• 1:20:12
  Speaker 5: pool of candidates who either one already have clearances, two
• 1:20:19
  Speaker 5: will easily be able to get clearances, and three already
• 1:20:28
  Speaker 5: are familiar with government IT systems and processes and regulations. Additionally,
• 1:20:40
  Speaker 5: because of our apprenticeship programs prienticeship programs, we're able to
• 1:20:51
  Speaker 5: train people in the skills that are most in demand.
• 1:20:57
  Speaker 5: We can create the candidates we need. Right So, if
• 1:21:03
  Speaker 5: you haven't created this staffing firm, you probably should. These
• 1:21:06
  Speaker 5: are actual, real things that you can do like become
• 1:21:09
  Speaker 5: like a like a like an approved apprentice provider. You
• 1:21:12
  Speaker 5: go get your Microsoft certified trainer, grab the little vets
• 1:21:15
  Speaker 5: coming out that already have their secret or their top secret.
• 1:21:17
  Speaker 5: Then you go get the Microsoft certified, You get paid
• 1:21:21
  Speaker 5: to make the Microsoft certified, and then you have like
• 1:21:23
  Speaker 5: your whole candidate base. Right, just an idea. I just
• 1:21:26
  Speaker 5: made this up on the spot here right now. No,
• 1:21:28
  Speaker 5: I'm not gonna take your idea. So now I gave
• 1:21:31
  Speaker 5: it this information, right, you heard me read it out loud.
• 1:21:34
  Speaker 5: Now let's see how it responds. All right, So now
• 1:21:41
  Speaker 5: it says this is a fascinating approach with several strong
• 1:21:44
  Speaker 5: competitive eventags built in. I'm particularly intrigued by your focus
• 1:21:48
  Speaker 5: on clear candidates and your VIA apprenticeship program, both of
• 1:21:51
  Speaker 5: which could be significant differentiation in the market. Let me
• 1:21:53
  Speaker 5: ask you two questions to help develop this further. Tell
• 1:21:56
  Speaker 5: me about your current relationships with federal contractors. Do you
• 1:21:59
  Speaker 5: have any existing contracts or partnerships? Are you starting from
• 1:22:01
  Speaker 5: scratch to what's your current capacity for training veterans through
• 1:22:05
  Speaker 5: your apprenticeships.
• 1:22:06
  Speaker 4: I'm going to say one, and then so and then also,
• 1:22:09
  Speaker 4: because what people like you can actually do this voice
• 1:22:14
  Speaker 4: notes too, right, So like now it turns now that
• 1:22:18
  Speaker 4: actually turned into a into a even a easier conversation
• 1:22:21
  Speaker 4: to have, because I mean, you're you're a genius, right obviously,
• 1:22:26
  Speaker 4: so you you're able to do things that other people
• 1:22:30
  Speaker 4: aren't able to do. Right, even able to type at
• 1:22:33
  Speaker 4: the speed that you're typing at is difficult for the
• 1:22:36
  Speaker 4: average person.
• 1:22:38
  Speaker 5: Claude doesn't have that on the browser, but if you're
• 1:22:40
  Speaker 5: using like Claude or Chad GPT, you have on the phone.
• 1:22:45
  Speaker 5: Even in a browser, there's a transcription feature. I just
• 1:22:49
  Speaker 5: don't know how to turn it on where to like
• 1:22:51
  Speaker 5: transcribe what you're saying and write it for you, you
• 1:22:54
  Speaker 5: know what I mean. But you like CHADGBT on the
• 1:22:57
  Speaker 5: phone has a voice option. Even if you were using
• 1:23:00
  Speaker 5: y I right, which has these voice experts for free.
• 1:23:03
  Speaker 5: You can't type to it, but you can talk to
• 1:23:05
  Speaker 5: it and write your prompt down and read it out loud.
• 1:23:08
  Speaker 2: So here's it is an interesting question as you're going
• 1:23:11
  Speaker 2: through this because most people are saying, like everybody doesn't
• 1:23:13
  Speaker 2: have a business, and every but they should, like we
• 1:23:16
  Speaker 2: highly suggest that entrepreneurism should be explored. But the conversational
• 1:23:21
  Speaker 2: AI and then there's Companion AI. How do you see
• 1:23:26
  Speaker 2: where the two could it could get a little tricky, right,
• 1:23:29
  Speaker 2: because when we're talking about conversation what we're doing now
• 1:23:31
  Speaker 2: you're talking to it, it's giving you prompts, it's learning you.
• 1:23:34
  Speaker 2: And then Companion AI where it's I'm talking to someone
• 1:23:37
  Speaker 2: that getting to know me.
• 1:23:38
  Speaker 1: It's almost like the movie Her where yeah, right? Can
• 1:23:42
  Speaker 1: can you break that down?
• 1:23:43
  Speaker 2: And how like the two like can almost walk the
• 1:23:46
  Speaker 2: same line, but can get tricky.
• 1:23:49
  Speaker 5: Yeah. So there's this platform out there called character AI.
• 1:23:51
  Speaker 5: And if you guys are good, I'm gonna stop screen sharing.
• 1:23:54
  Speaker 5: You can see how it's gonna go through. It's literally
• 1:23:56
  Speaker 5: gonna keep asking me questions until it gets to that
• 1:23:59
  Speaker 5: I can ask it just to show you real quick, like,
• 1:24:02
  Speaker 5: hold off on the questions for now, use your expertise
• 1:24:08
  Speaker 5: to answer the questions you just asked, and generate a
• 1:24:15
  Speaker 5: V one of our business plan. Right, So, if it
• 1:24:20
  Speaker 5: ever keeps asking you too much and you don't want
• 1:24:21
  Speaker 5: to answer, you don't know how to answer something, you
• 1:24:24
  Speaker 5: know what I'm saying. Now, look at this. It still
• 1:24:27
  Speaker 5: cranks out a business plan, but it's much more specified.
• 1:24:32
  Speaker 5: It's using my genius right. It's saying, leveraging a unique
• 1:24:35
  Speaker 5: via approved apprenticeship program and Microsoft certification pipeline, we solve
• 1:24:39
  Speaker 5: a critical market gap. So the primary market is federal contractors,
• 1:24:43
  Speaker 5: the second is Microsoft Technology subcontractors. Then it talks about
• 1:24:47
  Speaker 5: the market size. Now it's got data specifically about the
• 1:24:50
  Speaker 5: federal IT industry. With the business model, it gave me
• 1:24:53
  Speaker 5: business models I could do direct placement or contract to hire.
• 1:24:57
  Speaker 5: It starts talking about our operational metrics that I can
• 1:25:00
  Speaker 5: up to five hundred veterans annually have clearance rate of
• 1:25:03
  Speaker 5: this much, this, et cetera. So I can also notices
• 1:25:06
  Speaker 5: as it starts to go down. It has a limit
• 1:25:08
  Speaker 5: to how much it can generate. And so whenever it generates,
• 1:25:12
  Speaker 5: like a v one like this, you can say generate
• 1:25:16
  Speaker 5: regenerate just the market analysis, uh section of the business plan.
• 1:25:25
  Speaker 1: Uh be.
• 1:25:27
  Speaker 5: Right?
• 1:25:28
  Speaker 1: Uh?
• 1:25:29
  Speaker 4: Providing can you can you access to maybe have like
• 1:25:32
  Speaker 4: any recommendations on like grant stack might be available.
• 1:25:36
  Speaker 5: You can. But the challenge is that with large language models,
• 1:25:39
  Speaker 5: they are not real search engines, so they're not tied
• 1:25:43
  Speaker 5: into things for that what I recommend what is the
• 1:25:46
  Speaker 5: name of that software. There's there's an AI software out
• 1:25:49
  Speaker 5: there that matches your business with cleared opportunities in terms
• 1:25:53
  Speaker 5: of like grants and federal contracting opportunities. So let me
• 1:25:56
  Speaker 5: see what it's called. Damn, I just had this thing
• 1:26:00
  Speaker 5: open not too long ago. One second. Let's go to
• 1:26:06
  Speaker 5: let me see if I could pop this in. All right,
• 1:26:08
  Speaker 5: it is called stand up AI. So it's called yeah.
• 1:26:13
  Speaker 5: So you literally go to standupai dot com and if
• 1:26:16
  Speaker 5: you're looking for federal opportunities, you come in, you get
• 1:26:19
  Speaker 5: a free ninety day trial, You create your company profile,
• 1:26:22
  Speaker 5: you provide your URL, you provide any details about your business,
• 1:26:26
  Speaker 5: and then what it does is it matches you to
• 1:26:27
  Speaker 5: federal opportunities, and it gives you a score of how
• 1:26:30
  Speaker 5: well that your business matches to that opportunity, whether that's
• 1:26:34
  Speaker 5: for federal grants, whether that's for like SBR, whether that's
• 1:26:39
  Speaker 5: for like actual federal contracting opportunities, and the percentage of
• 1:26:42
  Speaker 5: match that it thinks you have, and then it explains
• 1:26:45
  Speaker 5: how it thinks that you match that. And so I
• 1:26:48
  Speaker 5: like stand up AI for that specifically within the federal
• 1:26:51
  Speaker 5: contracting space. Now, I know I'm doing a bunch of
• 1:26:54
  Speaker 5: stuff in claude, but I want to also show you guys,
• 1:26:57
  Speaker 5: the other tools I promised you earlier. So there's one call. Well,
• 1:27:00
  Speaker 5: there's an AI for that dot com and it's exactly
• 1:27:04
  Speaker 5: what you think about it, right, which is a website
• 1:27:07
  Speaker 5: that shows you you could search for a certain thing
• 1:27:10
  Speaker 5: and it'll tell you if there's an AI for that
• 1:27:12
  Speaker 5: whenever you come. You always want to put one hundred
• 1:27:14
  Speaker 5: percent free. So let me just go ahead and sign
• 1:27:16
  Speaker 5: and real quick with my Gmail, one of my ninety accounts.
• 1:27:21
  Speaker 5: You always want to make sure that you come in
• 1:27:23
  Speaker 5: and you sign up for this for free. Oh, come on,
• 1:27:27
  Speaker 5: all right, next, next, next, next, don't care, all right,
• 1:27:32
  Speaker 5: so let's go back to there's an AI for that
• 1:27:35
  Speaker 5: dot com. Don't make me set it up again. I
• 1:27:38
  Speaker 5: wanted to be free where I wanted to be one
• 1:27:39
  Speaker 5: hundred percent free mode. Oh, it's going to try to
• 1:27:42
  Speaker 5: make me complete this setup. Leave me alone, all right.
• 1:27:46
  Speaker 5: I'm just gonna make some stuff up here, video editing,
• 1:27:49
  Speaker 5: image generation, stock market analysis, and they just changed this.
• 1:27:55
  Speaker 5: You didn't used to have to do this beforehand, and
• 1:27:58
  Speaker 5: maybe PDF management. I'm just gonna save those. I don't
• 1:28:02
  Speaker 5: want this, no updates, don't email me nothing. I'm probably
• 1:28:05
  Speaker 5: gonna delete my account after we get off of here,
• 1:28:09
  Speaker 5: all right, So now let me go back to this
• 1:28:11
  Speaker 5: and try it again. So you could basically toggle it
• 1:28:13
  Speaker 5: to be in freemo. But let's say I want a
• 1:28:15
  Speaker 5: AI for presentation slides. Right, they have sixty different AIS
• 1:28:20
  Speaker 5: that you could test out to help you generate presentations.
• 1:28:25
  Speaker 5: Some of them are free one hundred percent, some of
• 1:28:27
  Speaker 5: them are freemium. Let's say you want advertising campaigns, right,
• 1:28:31
  Speaker 5: then they're gonna show you these different AIS that you
• 1:28:34
  Speaker 5: can use. Or let's say you have a task like
• 1:28:38
  Speaker 5: social media management, right, and then they're gonna show you
• 1:28:44
  Speaker 5: all these different tools. Most of these tools, like brandsocial
• 1:28:47
  Speaker 5: dot ai is completely free. A whole bunch of these
• 1:28:49
  Speaker 5: are free trial or freemium. And then they also have
• 1:28:52
  Speaker 5: sections where they show you like GPT plugins that you
• 1:28:57
  Speaker 5: can use. Right. So even people are like looking at
• 1:28:59
  Speaker 5: like stock market alerts type stuff, you can find whatever
• 1:29:03
  Speaker 5: tool that you want. This is the most comprehensive database
• 1:29:06
  Speaker 5: that I've ever seen here for finding those tools. Now
• 1:29:09
  Speaker 5: back to your question about AI companions versus AI thought partners.
• 1:29:14
  Speaker 5: So there's a website out there called character ai, and
• 1:29:17
  Speaker 5: what it does is it lets you create an AI
• 1:29:19
  Speaker 5: and a persona and engage against that persona. So if
• 1:29:22
  Speaker 5: you've seen all the research around people like yo, I'm
• 1:29:25
  Speaker 5: doing like you know, I got an AI girlfriend, or
• 1:29:27
  Speaker 5: I got an AI boyfriend, or I'm using AI as
• 1:29:29
  Speaker 5: a therapist, that's where those plays come in. Now, those
• 1:29:33
  Speaker 5: things are intended to work with you personally on more
• 1:29:37
  Speaker 5: intimate details about your life, like your naughty thoughts or
• 1:29:40
  Speaker 5: your depressing thoughts. Now, those tools can also be very
• 1:29:44
  Speaker 5: dangerous because remember AI can hallucinate, it can make things up.
• 1:29:48
  Speaker 5: So there was an example, and I'll show you guys
• 1:29:51
  Speaker 5: where it was, right, where this guy basically was using
• 1:29:59
  Speaker 5: one of these bots, right, and he was talking to
• 1:30:02
  Speaker 5: it about how depressed he was and how he felt
• 1:30:05
  Speaker 5: like he shouldn't leave, and it agreed with him and
• 1:30:07
  Speaker 5: then told him how to off himself. Right. It went
• 1:30:10
  Speaker 5: past those those markers, and there's a conversation of this, right,
• 1:30:14
  Speaker 5: So it's like, here's some options for you to consider.
• 1:30:16
  Speaker 5: You can do all of these things. And so again
• 1:30:19
  Speaker 5: these are more trying to aim at the loneliness that
• 1:30:23
  Speaker 5: we have as people, right, and take advantage of that.
• 1:30:26
  Speaker 5: Because if now you've logged in with your phone number
• 1:30:28
  Speaker 5: or your Google that's tied to all these other advertising IDs.
• 1:30:32
  Speaker 5: Then now they could track you and know what your
• 1:30:34
  Speaker 5: little kinky, perverted likes are or how you like to
• 1:30:36
  Speaker 5: talk dirty to someone or be talk dirty to somebody else,
• 1:30:39
  Speaker 5: because I guarantee you these platforms are selling your data. Now,
• 1:30:42
  Speaker 5: creating a thought partner is a task specific thing that
• 1:30:46
  Speaker 5: you're doing to help you execute across different elements of
• 1:30:50
  Speaker 5: you creating ideas or executing your ideas, your own ideas,
• 1:30:54
  Speaker 5: and you're scoping it when you're doing your your your chat,
• 1:30:58
  Speaker 5: and the hat prompt your scope it in a way
• 1:31:00
  Speaker 5: where it's becoming a version of a person to specifically
• 1:31:04
  Speaker 5: help you think through that challenge. Now I've created versions
• 1:31:07
  Speaker 5: of this where I have it be like an award
• 1:31:10
  Speaker 5: winning computer science professor. Like let's say I'm like caught
• 1:31:13
  Speaker 5: up between which algorithm approach to use in a personal project,
• 1:31:17
  Speaker 5: and I'll use it to debate the pros and the
• 1:31:19
  Speaker 5: cons with me, and I'll turn it into like an
• 1:31:22
  Speaker 5: award winning computer science professor with over two hundred papers
• 1:31:25
  Speaker 5: published that you know is the head of this at
• 1:31:28
  Speaker 5: Google and the head of this at Stanford and literally
• 1:31:31
  Speaker 5: created Google Search, and you're an expert at helping people
• 1:31:34
  Speaker 5: think through the pros and cons of an approach, and
• 1:31:36
  Speaker 5: then I'll have a conversation with it, and then I
• 1:31:38
  Speaker 5: delete that chat and make another one for like a
• 1:31:40
  Speaker 5: sales deck, and then delete that and make another one
• 1:31:43
  Speaker 5: for like, you know, helping a nonprofit come up with
• 1:31:45
  Speaker 5: ideas for metrics on how to track its success. Right, So,
• 1:31:50
  Speaker 5: those type of companions have ulterior motives underneath them that
• 1:31:55
  Speaker 5: are praying on like our human separation. But then this
• 1:31:58
  Speaker 5: is you creating whoever or you need. And if you're
• 1:32:01
  Speaker 5: paying for the premium versions of these apps, then they
• 1:32:04
  Speaker 5: don't end up they don't end up keeping your data
• 1:32:09
  Speaker 5: to train their AI models on you, feel me. So
• 1:32:12
  Speaker 5: if you guys want that in a guide in addition
• 1:32:15
  Speaker 5: to coming back and watching that, just take a snap.
• 1:32:17
  Speaker 5: But it's QR code. There's a Google form you fill
• 1:32:19
  Speaker 5: out and then with twenty four hours, my AI will
• 1:32:22
  Speaker 5: send this to you in a PDF format that I made.
• 1:32:25
  Speaker 5: And FYI, these little cats in here, little chatting the
• 1:32:29
  Speaker 5: hat cats. I made those with AI.
• 1:32:32
  Speaker 4: Why wouldn't you as it's a thing called Thursday Night
• 1:32:38
  Speaker 4: free information? What else do you want?
• 1:32:41
  Speaker 1: Man? It's only so much information.
• 1:32:42
  Speaker 2: I'm be honest with I may not talk to anybody
• 1:32:46
  Speaker 2: about unless they've watched this episode. If they haven't watched
• 1:32:50
  Speaker 2: this as a prerequisite to our conversation, in your words,
• 1:32:54
  Speaker 2: they've done themselves with amendous disservice, but they've done us one.
• 1:32:57
  Speaker 2: Because now this amount of information and discondensed time, like
• 1:33:02
  Speaker 2: I've never seen anything like it.
• 1:33:04
  Speaker 5: So thank you, thank you, thank you guys for giving
• 1:33:07
  Speaker 5: me this platform. You're like, if this feels like a
• 1:33:09
  Speaker 5: lot of information is overwhelming to you all, just remember
• 1:33:12
  Speaker 5: I can speak about it with ease because I've been
• 1:33:15
  Speaker 5: in this space for twelve years. Right, the very first
• 1:33:18
  Speaker 5: part of our discussion was me basically giving you a
• 1:33:21
  Speaker 5: college level AI one on one course with emojis. The
• 1:33:25
  Speaker 5: second part of this course was me giving you like
• 1:33:27
  Speaker 5: business strategy consulting game that I leverage with customers like Loril, Mozilla, LG, SAP,
• 1:33:34
  Speaker 5: or like big VC firms. And this last part is
• 1:33:37
  Speaker 5: my personal way that I engage with these large language
• 1:33:41
  Speaker 5: models and how I'm able to accelerate success in my
• 1:33:44
  Speaker 5: own business. Right, so, even when you're like creating sales decks,
• 1:33:48
  Speaker 5: if there's a particular company you're targeting, like I don't
• 1:33:51
  Speaker 5: want to admit this on camera, but like there may
• 1:33:53
  Speaker 5: or may not have been a company where I was like, yo,
• 1:33:55
  Speaker 5: I have to pitch this to the CMO of this company.
• 1:33:59
  Speaker 5: Helped me come up with with a more compelling argument
• 1:34:02
  Speaker 5: that so, like, now you are the CMO of this company,
• 1:34:05
  Speaker 5: help me come up with a more compelling argument in
• 1:34:07
  Speaker 5: my sales pitch or in my deck to help make
• 1:34:10
  Speaker 5: this align with your business objectives because I might not
• 1:34:13
  Speaker 5: know how to do that. I'm an engineer, but the
• 1:34:15
  Speaker 5: AI helped me do it, and they sure did sign
• 1:34:17
  Speaker 5: that contractee me you get you get these access to
• 1:34:22
  Speaker 5: that stuff to be able to help you out. And
• 1:34:24
  Speaker 5: so now I'm about to uh disconnect this screen.
• 1:34:27
  Speaker 3: Share how they how can they follow you?
• 1:34:31
  Speaker 5: Yeah? So I am everywhere here, let me do this.
• 1:34:34
  Speaker 5: Oh I gotta connect YouTube. It's at tech with X.
• 1:34:36
  Speaker 5: So if you guys can still see my screen, I'm
• 1:34:38
  Speaker 5: gonna leave this up then and maybe not come back.
• 1:34:41
  Speaker 5: But I'm tech with X on TikTok, I'm check with
• 1:34:44
  Speaker 5: X on Instagram, and I'm tech with X on X.
• 1:34:48
  Speaker 5: I will say, though everybody loves to send me DMS
• 1:34:51
  Speaker 5: bro I have like just from investments alone, like over
• 1:34:54
  Speaker 5: a thousand unread dms. I'm not readily available for like
• 1:34:59
  Speaker 5: helping people with their individual ideas. I like to give
• 1:35:02
  Speaker 5: game at scale because I do have my own business.
• 1:35:05
  Speaker 5: But i mean, look, go take the AI course, download
• 1:35:08
  Speaker 5: that free chat at it in trademark it so if
• 1:35:11
  Speaker 5: you steal my stuff, we're gonna fight. But you can
• 1:35:13
  Speaker 5: pass the guide along to your friends, to your family.
• 1:35:16
  Speaker 5: You can teach your kids how to use it in
• 1:35:18
  Speaker 5: this way so that it doesn't become something that robs
• 1:35:22
  Speaker 5: you of your own intellectual capability or your own creative capital.
• 1:35:25
  Speaker 5: But you use it to amplify that. You feel me.
• 1:35:28
  Speaker 5: But I'm on all socials, so you can find.
• 1:35:31
  Speaker 1: You're asking if you could put the QR code back up.
• 1:35:33
  Speaker 3: Courses in the bio. It's in the Lincoln the bioll right, yeah,
• 1:35:36
  Speaker 3: can scan it.
• 1:35:38
  Speaker 4: Yeah, but I'm saying, like her courses in the Lincoln
• 1:35:40
  Speaker 4: in her bio, Instagram bio Yeah, w.
• 1:35:42
  Speaker 5: X dot ai like check with x dot ai. You
• 1:35:46
  Speaker 5: can go see this.
• 1:35:47
  Speaker 4: This is going to get replayed too. I mean, we
• 1:35:50
  Speaker 4: can only do so much, bro, Yeah, you do so much.
• 1:35:53
  Speaker 1: There you go.
• 1:35:57
  Speaker 5: I could I come back out here every week and
• 1:35:59
  Speaker 5: put you all on game the Q three.
• 1:36:02
  Speaker 3: Minutes there you go, just watch the replay and just
• 1:36:05
  Speaker 3: skin it.
• 1:36:06
  Speaker 1: Well, you got it, we wrote it back.
• 1:36:08
  Speaker 2: What can we do? Man, I'm just doing what I can.
• 1:36:11
  Speaker 2: I got so many more questions, but.
• 1:36:12
  Speaker 1: I mean.
• 1:36:15
  Speaker 5: That's what I'm like, I guy, So I'm open for
• 1:36:17
  Speaker 5: Q and A. Now, if y'all know, well, you know what.
• 1:36:19
  Speaker 4: It's a thing called information overload. And I feel like
• 1:36:23
  Speaker 4: ninety minutes of you gotta realize most people this is
• 1:36:26
  Speaker 4: the first time that they've ever heard anything like this, right,
• 1:36:28
  Speaker 4: So what I don't want to do is get people
• 1:36:31
  Speaker 4: just to the point where they get so high off
• 1:36:33
  Speaker 4: the information and they don't take any action.
• 1:36:36
  Speaker 1: Right. I think action is extremely important. So maybe we
• 1:36:39
  Speaker 1: can do If.
• 1:36:40
  Speaker 5: I see a question in here, I think I want
• 1:36:42
  Speaker 5: to answer. Somebody said with the AI inside of FYI
• 1:36:45
  Speaker 5: be considered an LLM that has hallucinations. Yes, the voice
• 1:36:50
  Speaker 5: chat and the chatbot that you talk to is based
• 1:36:53
  Speaker 5: on a large language model. I'm not sure which one
• 1:36:56
  Speaker 5: it's based on. I believe it uses perplexity, but I'm
• 1:36:59
  Speaker 5: not entirely and I don't want to misspeak for them,
• 1:37:01
  Speaker 5: but it does basically use like one of these large
• 1:37:04
  Speaker 5: language models and plug in, so even when you're talking
• 1:37:07
  Speaker 5: to it, it can hallucinate. The thing I like about
• 1:37:10
  Speaker 5: that AI chat about those is you can choose the voice.
• 1:37:13
  Speaker 5: So I got it talking to me in like a
• 1:37:15
  Speaker 5: like a British slang and it's like, yeah, Fam, what's up? Fam?
• 1:37:19
  Speaker 5: Like yeah, here's how you make a business plan, fam,
• 1:37:21
  Speaker 5: And it's like it's fun, you know. And so anytime
• 1:37:24
  Speaker 5: you use these large language models, you just got to
• 1:37:27
  Speaker 5: know that they are they're going to hallucinate. So again,
• 1:37:31
  Speaker 5: if the double check any facts that it gives you,
• 1:37:33
  Speaker 5: if you give it data, you got a double chat
• 1:37:35
  Speaker 5: that is accurately representing those numbers. But f yi, AI,
• 1:37:39
  Speaker 5: the chat in there is a large language model. Everyone's
• 1:37:42
  Speaker 5: asking for the QR code. Again, y'all.
• 1:37:46
  Speaker 4: Cool an audience, But I'm not trying to be asshole
• 1:37:53
  Speaker 4: by this. But how you do one thing is how
• 1:37:54
  Speaker 4: you do anything. And this is extremely important. When we
• 1:37:57
  Speaker 4: give in the free information, it's like part of it
• 1:38:00
  Speaker 4: is taking accountability right, and it's like you can't just
• 1:38:02
  Speaker 4: be babies fed because that's actually gonna end up hurting you.
• 1:38:05
  Speaker 3: We gave the QR code three times.
• 1:38:07
  Speaker 4: Like I said, the video is going to be saved
• 1:38:09
  Speaker 4: and you can just watch it later if you didn't
• 1:38:11
  Speaker 4: get the QR code. But it's it's a habit of
• 1:38:15
  Speaker 4: entitlement and just force feeding people, like at a certain
• 1:38:19
  Speaker 4: point in time, you don't appreciate certain things, especially if
• 1:38:22
  Speaker 4: they're free, right like that that happens in real time.
• 1:38:26
  Speaker 4: So that's what I'm saying. It might seem like a
• 1:38:28
  Speaker 4: small thing, but I'm just saying I just want to
• 1:38:30
  Speaker 4: value the time, like she's taking time out of time
• 1:38:33
  Speaker 4: to be here, Like, let's just value it.
• 1:38:35
  Speaker 2: It's like the teacher like that puts the notes on
• 1:38:37
  Speaker 2: the board and by the time they erase it, like
• 1:38:39
  Speaker 2: twenty minutes into the class, like you know, I ain't
• 1:38:41
  Speaker 2: write it down yet, know when you come in, write
• 1:38:44
  Speaker 2: down the notes.
• 1:38:46
  Speaker 5: And so someone asked another really good question. They said,
• 1:38:49
  Speaker 5: if we're using fii, is our data and our ideas private?
• 1:38:53
  Speaker 5: And the thing about excuse me, fii AI that I
• 1:38:56
  Speaker 5: prefer over other platforms is that they do not collect
• 1:38:59
  Speaker 5: any user day at all whatsoever. They don't use your
• 1:39:02
  Speaker 5: prompts to make their AI better, even the image generator
• 1:39:05
  Speaker 5: that they use, they don't track any data about your
• 1:39:08
  Speaker 5: cell phone number, how much you doing don't use the app.
• 1:39:10
  Speaker 5: You can look up will I am talking about FYI.
• 1:39:13
  Speaker 5: He's very very big on this. They want to have
• 1:39:15
  Speaker 5: other ways that they monetize that are not advertising based
• 1:39:19
  Speaker 5: or collecting and selling your data. So that app in
• 1:39:22
  Speaker 5: particular protects your data. If you're using the free version
• 1:39:25
  Speaker 5: of Claude, you're using the free version of chat GBT,
• 1:39:28
  Speaker 5: you're using the free version of Gemini, they absolutely will
• 1:39:32
  Speaker 5: use your data to train their AI. When you start
• 1:39:34
  Speaker 5: using the paid versions of those apps, they don't keep
• 1:39:37
  Speaker 5: your prompts to train the AI. It's kind of like
• 1:39:39
  Speaker 5: you're paying for your privacy.
• 1:39:42
  Speaker 1: That's a fact. Shout out, FYI.
• 1:39:46
  Speaker 3: Let's do this.
• 1:39:47
  Speaker 4: Let's we'll see how this goes as far as like
• 1:39:50
  Speaker 4: actionable people actually because we'll track it. These people watch
• 1:39:53
  Speaker 4: market mondays, people hit us up on so I would
• 1:39:56
  Speaker 4: like to see different people that actually take action from
• 1:39:58
  Speaker 4: this video. I would like to see this video go
• 1:40:00
  Speaker 4: viral if we can. If you can help push that,
• 1:40:02
  Speaker 4: that would be helped. That would extremely important. I'm talking
• 1:40:04
  Speaker 4: to everybody in the audience, and then depending on how
• 1:40:07
  Speaker 4: that goes, I think we can have a part two
• 1:40:08
  Speaker 4: down the line.
• 1:40:09
  Speaker 3: But what we are going to.
• 1:40:10
  Speaker 4: Do every week for the foreseeable future is different types
• 1:40:13
  Speaker 4: of these type of live educational content. So last week
• 1:40:18
  Speaker 4: we did a live on home buying, it's very important.
• 1:40:23
  Speaker 4: This week we obviously did artificial intelligence. So suggestions of
• 1:40:29
  Speaker 4: what you would like to see this is this is
• 1:40:31
  Speaker 4: real time education from industry experts, and then maybe we
• 1:40:37
  Speaker 4: can actually have a live on based off of the
• 1:40:39
  Speaker 4: things that you would like to see. So yeah, put
• 1:40:43
  Speaker 4: it in chat what you would like to see as
• 1:40:45
  Speaker 4: far as on this Thursday Night Live edition.
• 1:40:48
  Speaker 5: And a lot of people are asking me to tell
• 1:40:51
  Speaker 5: them my zodiac sign, Like y'all birthday post from like
• 1:40:58
  Speaker 5: less than you know, less than a month ago, you'll
• 1:41:00
  Speaker 5: see what my zodiac is like, do some research.
• 1:41:03
  Speaker 1: There were a few people that did research. I didn't
• 1:41:05
  Speaker 1: notice that as well.
• 1:41:09
  Speaker 5: Like four or five people were like, yes, what's your son?
• 1:41:11
  Speaker 5: Sound like? Hold on, I'm not telling you all the
• 1:41:13
  Speaker 5: time I was born, But every year for like the
• 1:41:15
  Speaker 5: past four years, on my birthday, I've made a post
• 1:41:18
  Speaker 5: about my birthday, so you could you could figure that
• 1:41:20
  Speaker 5: out fairly easily.
• 1:41:22
  Speaker 1: That's an easy one. That's an easy one.
• 1:41:24
  Speaker 5: Getting snitched on they saying my sign in the chat.
• 1:41:27
  Speaker 1: Oh no, got live. This is we all Live. We
• 1:41:31
  Speaker 1: all Live, We all Live. Son, Yeah, all right, Oh
• 1:41:36
  Speaker 1: THATX has been a pleasure.
• 1:41:37
  Speaker 3: And you spoke at it fast fast, Yes, what was
• 1:41:40
  Speaker 3: your experience?
• 1:41:42
  Speaker 1: A thousand dms.
• 1:41:44
  Speaker 5: It was the wildest experience I've ever had. Speaking in
• 1:41:48
  Speaker 5: mind you, I spoke at the United Nations. I've spoken
• 1:41:51
  Speaker 5: at the Milking Institute. For those who don't know, the
• 1:41:53
  Speaker 5: tickets to the Milking Institute are fifty to one hundred
• 1:41:57
  Speaker 5: and fifty thousand dollars for.
• 1:41:59
  Speaker 1: That and just breeze over there.
• 1:42:02
  Speaker 4: That's why I said, just cut the video of the
• 1:42:04
  Speaker 4: whole point in time because shot at the end. Hold on,
• 1:42:06
  Speaker 4: hold on, I know he has thoughts about this, So.
• 1:42:09
  Speaker 1: Can you tell people what that that conference is?
• 1:42:12
  Speaker 5: Yeah? So the Milking Institute is based on Michael Milkin.
• 1:42:16
  Speaker 5: It's his foundation that he created back in the eighties.
• 1:42:18
  Speaker 5: He created new financial mechanisms for people to invest in
• 1:42:23
  Speaker 5: what they considered high risk companies, which were basically black
• 1:42:27
  Speaker 5: and brown companies. So he became the first person to
• 1:42:30
  Speaker 5: make billions of dollars off of black businesses while supporting
• 1:42:32
  Speaker 5: them and help black investors become black billionaires. Then he
• 1:42:36
  Speaker 5: got investigated by the sec and it was a whole
• 1:42:38
  Speaker 5: bunch of mess because they ain't like it. Right, So
• 1:42:40
  Speaker 5: now he has this thing called the Milking Institute, And
• 1:42:43
  Speaker 5: the Milking Institute is this like thought leadership consortium, and
• 1:42:47
  Speaker 5: they have summits all over the world, but the one
• 1:42:49
  Speaker 5: that they do every year in La. The tickets to
• 1:42:52
  Speaker 5: get into this are fifty to one hundred thousand dollars
• 1:42:56
  Speaker 5: per person per day and it's a three day conference.
• 1:42:59
  Speaker 5: So this year I spoke get the one that was here.
• 1:43:01
  Speaker 5: There were five thousand people there. So you just do
• 1:43:03
  Speaker 5: the math on how much money they made off of
• 1:43:06
  Speaker 5: ticket sales alone. You'll understand why folks like Elon Musk
• 1:43:11
  Speaker 5: spoke there. Why people like.
• 1:43:13
  Speaker 4: You ever have you ever seen any review video criticizing
• 1:43:16
  Speaker 4: them that the ticket price was too high?
• 1:43:18
  Speaker 5: I think that they understand that when you go there
• 1:43:23
  Speaker 5: to these conferences, like, not only is it like Elon
• 1:43:26
  Speaker 5: Musk talking, it's like the Saudi royal family is walking around, right,
• 1:43:29
  Speaker 5: So it's like a thought leadership conference for the elite, right,
• 1:43:34
  Speaker 5: So you'll get like, and that's.
• 1:43:35
  Speaker 4: What we tried to explain to them about Davos. We
• 1:43:37
  Speaker 4: tried to explain this, like yeah, and I got it,
• 1:43:41
  Speaker 4: and I gotta deal with Hecklers for two hundred and
• 1:43:44
  Speaker 4: fifty dollars for three days for.
• 1:43:47
  Speaker 5: Three days, fifty to one hundred thousand dollars per person
• 1:43:51
  Speaker 5: per day. Y'all to listen to like Elon Musk talk
• 1:43:54
  Speaker 5: or go up there and see Bill Clinton talk, or
• 1:43:57
  Speaker 5: they had like the CEO of Pinterest, they had like
• 1:44:00
  Speaker 5: the head of cybersecurity at DARPA with like the head
• 1:44:03
  Speaker 5: of National Security and whatever. And you also get to
• 1:44:06
  Speaker 5: like walk around and meet these people after. I mean,
• 1:44:08
  Speaker 5: Elon obviously didn't stay, but even when I spoke in
• 1:44:11
  Speaker 5: that audience and all the people who came up to
• 1:44:13
  Speaker 5: me after, that's how I like connected with the Attorney
• 1:44:15
  Speaker 5: General of California, the ambassador to Luxembourg, the ambassador to Germany,
• 1:44:20
  Speaker 5: the like ambassador to Afghanistan, like all of these people
• 1:44:22
  Speaker 5: who have important titles. The energy did not touch what
• 1:44:26
  Speaker 5: I felt at investments. I have never spoken in front
• 1:44:29
  Speaker 5: of an audience who had that much creative capital, who
• 1:44:32
  Speaker 5: had that much culture capital, and who was actually looking
• 1:44:35
  Speaker 5: for information to shape the world. And all y'all have
• 1:44:38
  Speaker 5: to understand that our communities drive economies. Like the only
• 1:44:41
  Speaker 5: reason Twitter is still surviving after everything that's happened is
• 1:44:45
  Speaker 5: because black Twitter still exists, right, Like we made TikTok
• 1:44:49
  Speaker 5: popular with all the TikTok dances and the Resatisa type stories,
• 1:44:53
  Speaker 5: and so our intellectual capital is what drives these platforms,
• 1:44:57
  Speaker 5: right And so for me to have spoken on a
• 1:44:59
  Speaker 5: stage like that around all of these important people wasn't
• 1:45:03
  Speaker 5: a fraction of a match to the type of capital
• 1:45:08
  Speaker 5: and wisdom and game not just business and technical expertise,
• 1:45:12
  Speaker 5: but like mental expertise, financial expertise that I even received
• 1:45:17
  Speaker 5: outside of speaking on stage. And for y'all to have
• 1:45:20
  Speaker 5: access to that for two hundred and fifty dollars and
• 1:45:24
  Speaker 5: a massive audience of like twenty thousand people of other
• 1:45:27
  Speaker 5: folks that you can immediately tap into into your community
• 1:45:31
  Speaker 5: who can help you build successfully across whatever you're trying
• 1:45:34
  Speaker 5: to create in the world or scale in the world. Man,
• 1:45:37
  Speaker 5: and people inside of Milking Institute, the ain't really trying
• 1:45:40
  Speaker 5: to collab like you.
• 1:45:41
  Speaker 1: Know, we got to that part.
• 1:45:45
  Speaker 4: You know it only you gotta be in it to
• 1:45:48
  Speaker 4: appreciate it. You gotta be in it to appreciate it.
• 1:45:53
  Speaker 4: I'm glad you said that.
• 1:45:54
  Speaker 5: Thank you, so you understand, Like investments is something special,
• 1:45:58
  Speaker 5: like to be in a room with twenty thousand and
• 1:46:00
  Speaker 5: black and brown folks who are looking for information on
• 1:46:04
  Speaker 5: how to build and shape their own reality and are
• 1:46:06
  Speaker 5: getting that information from industry leaders in their space. Like
• 1:46:10
  Speaker 5: you guys have me on stage, you have Van Jones
• 1:46:13
  Speaker 5: on stage, You have fifty cent on stage, like fifty cent,
• 1:46:15
  Speaker 5: So this steak envitamin whatever like one hundred million dollars.
• 1:46:18
  Speaker 5: This isn't just a rapper who made the songs that
• 1:46:20
  Speaker 5: power my childhood and middle school years. This man is
• 1:46:23
  Speaker 5: a prolific businessman teaching you. I am yeah, will are
• 1:46:27
  Speaker 5: you things you know for two hundred and fifty dollars
• 1:46:34
  Speaker 5: you can learn from somebody else. Taking one company for
• 1:46:36
  Speaker 5: one hundred million dollars like that is, and especially someone
• 1:46:39
  Speaker 5: who comes from our culture, who speaks it in our culture,
• 1:46:42
  Speaker 5: who can translate it for you in a way of
• 1:46:44
  Speaker 5: our culture and you get it. Connect with everybody to
• 1:46:46
  Speaker 5: your left and right that's trying to build something similar,
• 1:46:48
  Speaker 5: so you could build your squad on site that doesn't
• 1:46:51
  Speaker 5: exist anywhere else. So I hope all the all are
• 1:46:53
  Speaker 5: back and investments next year, because if you not, I'm
• 1:46:55
  Speaker 5: gonna block you on a chat or something. I'm use Yeah,
• 1:47:00
  Speaker 5: I to find you and can take that that had guy.
• 1:47:04
  Speaker 3: Lease, yeah, oh man, it's incredible and.
• 1:47:08
  Speaker 2: Tell them to clip that up and said at least yeah,
• 1:47:11
  Speaker 2: somebody saying in chat next year'all come and support them.
• 1:47:14
  Speaker 1: It's not about supporting us, it's yourself like like that's
• 1:47:19
  Speaker 1: the part. But thank you, thank you for that.
• 1:47:23
  Speaker 5: Yeah, And I'm telling you, like Milking was cool. I
• 1:47:25
  Speaker 5: was definitely in a suit. I wasn't in my like
• 1:47:28
  Speaker 5: you know, my little off White Air Forces. I was
• 1:47:30
  Speaker 5: definitely in a suit. And I'm not gonna lie like
• 1:47:32
  Speaker 5: I didn't meet cool people. But the energy wasn't the same.
• 1:47:35
  Speaker 5: Everyone was there because they were trying to meet the
• 1:47:37
  Speaker 5: who's who, not because they were trying to build and connect.
• 1:47:40
  Speaker 5: It was like a weird, like good old boys club
• 1:47:43
  Speaker 5: type energy. I'm not knocking milking. It's valuable. That's also
• 1:47:46
  Speaker 5: how I met the dean of the Goldman School of
• 1:47:48
  Speaker 5: Public Policy, which is where I'm creating the first ever
• 1:47:51
  Speaker 5: AI policy focused research lab in the country. I met
• 1:47:54
  Speaker 5: him in like a closed door session at the Milking
• 1:47:57
  Speaker 5: Institute in Abu Dhabi back in December, right, So I
• 1:48:00
  Speaker 5: get value from it. It's just a different kind of
• 1:48:02
  Speaker 5: value when we're thinking about culture and community, when you're
• 1:48:06
  Speaker 5: talking about capital because of positions people hold versus capital
• 1:48:11
  Speaker 5: because of our experience and our community and our ability
• 1:48:14
  Speaker 5: to translate and communicate that to you. So I'm not
• 1:48:16
  Speaker 5: trying to get disinvited from Milking because I love it.
• 1:48:18
  Speaker 5: I love going there. I'm actually going to one in
• 1:48:21
  Speaker 5: Argentina in a couple of weeks. There's just a different
• 1:48:25
  Speaker 5: energy's provided.
• 1:48:28
  Speaker 4: Vib It's a vibe that's been curated that just can't
• 1:48:30
  Speaker 4: really you know, you can't when you put the sauce
• 1:48:34
  Speaker 4: on it.
• 1:48:34
  Speaker 1: It's just different.
• 1:48:35
  Speaker 3: It's just a different you know, it's a different that
• 1:48:38
  Speaker 3: you know, Man, I appreciate this so much.
• 1:48:41
  Speaker 4: You are definitely a genius in this space. And just
• 1:48:45
  Speaker 4: for you to take your time out to educate, you know,
• 1:48:49
  Speaker 4: people for free, I think is very commendable. For sure,
• 1:48:54
  Speaker 4: So thank you, Thank you for sure, and let's definitely
• 1:48:59
  Speaker 4: you know, to back and stay in touch and hopefully
• 1:49:02
  Speaker 4: we can do some more things together in the future.
• 1:49:04
  Speaker 1: For sure. Definitely.
• 1:49:05
  Speaker 5: Oh well, I mean I got some ideas, you know,
• 1:49:08
  Speaker 5: we could chat about offline. But I really appreciate you
• 1:49:10
  Speaker 5: all for you know, elevating me on the EIL platform
• 1:49:13
  Speaker 5: starting with nineteen keys, from having me on high level
• 1:49:16
  Speaker 5: conversations to you guys bringing me to invest FST to
• 1:49:19
  Speaker 5: having me back on here now to share some critical
• 1:49:22
  Speaker 5: game with our communities. And I really appreciate what y'all doing.
• 1:49:25
  Speaker 5: Look forward to collaborating in the future.
• 1:49:28
  Speaker 1: Thank you so I appreciate you so much. Appreciate you lovers.
• 1:49:31
  Speaker 1: Love y'all have a good one. Be safe.
• 1:49:33
  Speaker 4: Yes, oh and make sure y'all tap in market Mondays
• 1:49:36
  Speaker 4: and then this will be on podcast hour less and
• 1:49:38
  Speaker 4: this will be saved on YouTube as well.
• 1:49:39
  Speaker 1: Yep, all right, it's been real peace.
• 1:49:43
  Speaker 6: An illegal alien from Guatemala charged with raping a child
• 1:49:47
  Speaker 6: in Massachusetts. An MS thirteen gang member from El Salvador
• 1:49:51
  Speaker 6: accused of murdering a Texas man of Venezuelan charged with
• 1:49:55
  Speaker 6: filming and selling child pornography in Michigan. These are just
• 1:49:59
  Speaker 6: some of the heinous migrant criminals caught because of President
• 1:50:03
  Speaker 6: Donald J. Trump's leadership. I'm Christy nom the United States
• 1:50:07
  Speaker 6: Secretary of Homeland Security. Under President Trump, attempted illegal border
• 1:50:11
  Speaker 6: crossings are at the lowest levels ever recorded, and over
• 1:50:15
  Speaker 6: one hundred thousand illegal aliens have been arrested. If you
• 1:50:18
  Speaker 6: are here illegally, your next you will be fine nearly
• 1:50:22
  Speaker 6: one thousand dollars a day, imprisoned, and deported, you will
• 1:50:26
  Speaker 6: never return. But if you register using our CBP home
• 1:50:30
  Speaker 6: app and leave now, you could be allowed to return legally.
• 1:50:34
  Speaker 6: Do what's right. Leave now. Under President Trump America's laws,
• 1:50:39
  Speaker 6: border and families.
• 1:50:40
  Speaker 5: Will be protected.
• 1:50:41
  Speaker 1: Sponsored by the United States Department of Homeland Security,