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Jeremy Utley on Crafting Smarter Conversations with AI
Episode 2819th February 2024 • Data Driven • Data Driven
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Today, we're thrilled to welcome a special guest, Jeremy Utley, an academic marvel from Stanford, whose work on AI and idea flows is altering the landscape of business and innovation. In this episode, titled “Jeremy Utley on Getting the Most out of LLMs”, we dive into Jeremy's FIXIT approach for leveraging Large Language Models (LLMs) such as ChatGPT.

Jeremy will unpack the nuances of FIXIT, showing us the importance of providing context, iterative interaction, and team incubation while using AI. We'll reminisce about how technology has evolved from cell phone minutes to AI, which is becoming as ubiquitous as smartphones once were.

Frank will voice concerns about the technical aspects, like token length, while agreeing with Jeremy's method. We'll examine why AI needs to be seen as a collaborative partner rather than a magical solution. Jeremy will shine a light on his book "IdeaFlow" and share his insights on the psychological barriers hindering the effective use of AI in practice.

Expect to hear anecdotal wisdom about the transformative impact of ChatGPT, the importance of prompt engineering, and the potential of AI to refine negotiation skills. Jeremy will even offer examples of how generative AI can offer fresh perspectives on personal and emotional decisions.

Don’t forget Frank’s experiments with creating custom GPTs, such as for our character Bailey. Our lively discussion promises to leave you with a wealth of knowledge on interacting with and extracting maximum value from AI.

For all this and much more, stay tuned in as we journey through the possibilities and realities of AI as a tool for amplifying human capacity.

And before we kick things off, a quick reminder to check out Audible for the best in audiobooks, and please take a moment to rate and review Data Driven to help us grow and bring you content you love.

Now, without further ado, let's get data driven.

Show Notes

00:00 "Idea flows: the only business metric that matters."

05:35 Striving for the best is essential.

06:46 Expert hesitations on using AI for knowledge.

11:27 Asking for help, ended up with an image.

14:41 Convince family to take job offer role-play.

16:08 Learning new skills and fostering imagination through technology.

19:54 Seek understanding from personal experiences and examples.

25:48 Keanu Reeves movie sparks philosophical wonder.

28:42 AI prompts emotional epiphanies for life decisions.

32:11 Accidental query on creating GPU prompts explanations.

36:08 Instructions for using voice mode during coaching.

39:50 Ease of use and utility in busy life.

43:18 Key to AI success: Team collaboration is essential.

47:07 Kids don't care about data plans.

50:45 Released groundbreaking technology; implications for all industries.

53:18 Excited to buy internet access for chat.

54:54 Jeremy Utley wows with innovation and wisdom.

Transcripts

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Today on the data driven podcast, we have the privilege of hosting

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none other than Jeremy Utley. Now, Jeremy

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isn't just any guest. He's an academic marvel

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and entrepreneurial spirit rolled into 1. Hailing

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from the prestigious corridors of Stanford as an adjunct professor, he's

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the kind of chap who educates the future disruptors of Silicon

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Valley. He is here to tell us how to get the most out of

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generative AI. Now on to the show.

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Hello, and welcome back to Data Driven, the podcast where we explore the emergent fields

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of artificial intelligence, data engineering, and data science,

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and all the associated technologies. With me today is

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Jeremy Utley, who is a, adjunct

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professor, venture investor, and co author of the book,

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Idea Flow, The Only Business Metric That Matters. Welcome to the

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show, Jeremy. Thanks for having me. Hey, no problem.

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So Stanford. That's kind of a big

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deal. It's a it's a special place. Yeah. I'm

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just trying to not get found out. I'm sure it's, you know, similar to,

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the, the guy on Office Space. Right? At some point, there'll the clerical error

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will be revealed. You'll you'll know when they move you to the

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basement. Right? Exactly. Exactly. Yeah. But I've been teaching at

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Stanford since 2009, and I've been delighted to get to learn alongside some of

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the most incredible students in the world and and get to study some of those

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incredible innovators in the world. So, not just I may be a

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professor or an adjunct professor, but I really consider myself to be a front row

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student in in the classroom alongside my students. Very

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cool. Very cool. So, what

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what is the most important metric? I'll start right there.

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Well, the most important metric we call idea

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flows, the only business metric that matters. And the reason that we make that bold

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claim is because it's the only measure of your

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team's capacity to solve problems. And the the only

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constant in our day to day lives is problems. In in our businesses, I

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don't know, a single business that is facing a day without problems. And

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so if you think about problems as the constant, then your

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team's capacity to solve problems is really the most important thing

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that you should be measuring. And yet, nobody really even knows how to

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measure it. And so we talk about idea flow as the as the way to

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measure a team's capacity to solve problems.

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Interesting. Interesting. And is this is this changing now when we have the

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reality of AI assisted teams?

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Yeah. Yeah. Absolutely. That's it's a really insightful question. Yes.

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It does change or sorry. It has the

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potential to change. And yet, what our research suggests that we've

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conducted over the last year or so, is that sadly, it

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actually doesn't change in practice. In theory, it could change but in

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practice it often doesn't. What's interesting, so what

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what are the barriers to this? Right? Because I have some thoughts on this. I

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know that a number of companies have basically outright

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banned, use of AI tools

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with good intentions, right, because the privacy policies, etcetera, etcetera,

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but in reality, people are copying and pasting sensitive stuff anyway.

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So, it seems like banning something outright

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doesn't always work in a number of areas. But

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what what are the barriers? Right? Because it it it can, like

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you said, but in practice, what's what's what are the blockers?

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Ultimately, it's it's human psychology, really, is what what's,

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the challenge. It turns out that our expectations of the technology,

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are hamstringing our ability to make use of it. Because

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we're approaching the technology. Most teams that we studied

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approach the technology as an oracle. It's almost like a search

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box. It's gonna give them the best answer. Right?

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And that's the wrong way to approach the technology. It does feel somewhat

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magical when you type in, you know, an enigmatic query

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and get a seemingly intelligent response. I mean, that feels

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magical, but the teams that do that underperform. The teams

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that overperform are the teams that

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treat generative AI not as an oracle, but as a thought

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partner, as as a conversation partner, and iteratively

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work together with the AI to discover a better answer.

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And the irony of that is it's not very magical, actually. It feels

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like work. And yet, where teams that

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treat AI as a conversation partner arrive is

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light years better than teams that treat

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AI as an oracle perform.

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Interesting. So what are the what I think I know what you're

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getting at in terms of treating it like an oracle versus treating it like a

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conversation. Because I've seen that as I do more and more of this, I

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hate the term prompt engineering. I hate the strong word. I have mixed feelings about

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the term prompt engineering because there is no one single prompt to rule them

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all. Mhmm. At least that's been my experience where you kind of you kind

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of it's like a conversation, like, you're having. It's not a

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person I know. It's not a person I know. It's not a But it's but

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but it is a mindset, Frank. That's the thing. It's a mindset. And people

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don't come with the mindset of I want to have a conversation. People are lazy.

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Right? So so Herbert Simon, back in 1954,

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won the Nobel prize for what he deemed satisficing, which

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was the human tendency to settle for good enough. Right? And in most

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of our lives, it's fine. I need a good enough pair of jeans, I need

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a good enough cup of coffee, whatever it is. Right? But when we're trying to

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solve problems, good enough sometimes is is okay. But often, especially

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when it pertains to innovation, you don't just want the good enough thing. You want

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the best thing. And it's in that area where when we really

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want the best solution, that our tendency to settle for good enough

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really hurts us. Because what teams do is they put

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in a prompt and they get a pretty good answer and they go, woah,

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I I was prepared to take an hour working on this but we kind of

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got pretty good in 5 minutes. You guys want to go get coffee? And everybody

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just gives up because they got good enough. And so that's,

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you know, I I think it really is a mindset thing. Forget the word prompt

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engineering. It's all it's it's self engineering. It's human

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engineering. And one of the best things that a human being can

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do is say to the AI why they don't like

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the answer the AI gave. Right? So take your expertise.

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Here, this is something that anyone is listening can do right now. Take something

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that you know you're an expert on. So for example, I'm an expert

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on customer insights or or low resolution prototyping and

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experimentation. Right? So I might say to the AI, can you give me a

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step by step guide for how to conduct an experiment? K. If I

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did that, we can do it right now live if we wanted to. But if

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I do that, it's gonna give me like, you know, the average of the Internet.

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Right? And it's gonna draw from a bunch of stuff that may be good, may

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be bad. By the way, I'm an expert, so the chances of my knowledge surpass

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it are reasonable, you know, at least. But because it's gonna give me

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the average of the Internet, it's probably gonna find some corners that I don't know

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about and it's probably gonna say some stuff that I vehemently disagree with. Well, where

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most people give up and I think because they want AI to not

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be that good is they look at the response and they go, see.

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It didn't even know that you're supposed to test for desirability and not

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feasibility. Right? Whatever. And then they say, that's why AI is no

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good. Well, Human Engineering, not Prompt Engineering.

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Human Engineering is to say, okay, human, tell the AI

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what you disagree with and why you disagree with it,

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and ask the AI to regenerate an answer

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given the following considerations and put in your critique.

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Most people if they do that, just even that one thought exercise,

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will be blown away. Yeah. You get an order of magnitude better response.

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Absolutely. Right? Absolutely. Because you're kind of focusing the cone

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of, you know, inquiry with your own

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expertise. And what people want is they I mean, no one would

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ever if you think about, like, AI like an MBA intern. Right? No

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one gets an intern from Harvard Business School, gives them 2

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sentences of instruction and then at the end of the summer says, man, their workout

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was no good. I didn't interact with them at all. I didn't give them any

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guidance. But for crying out loud, what's

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Harvard doing these days? Right? No. Nobody gives a

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human being 2 sentences of input and then critiques how bad of a job they

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did, right? And yet we open chat gpt, we give

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2 sentences of input, if that by the way, and then we go, See, it's

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not very good, well, work with it. Garbage in garbage

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out. It's as old as possible. And the reason most people don't I think most

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people don't wanna work with it is because they don't want it to be any

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good. Yeah. I could see that. Totally.

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And the people who do want it to be good will be unlocked and

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unleashed. But it requires not prompt engineering, but

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human copilot engineering. I do like the

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fact that a lot of these tools that are coming out are being called copilots,

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right? Because I think it shifts the focus away from

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AI isn't going to do it all. AI is not

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probably gonna take your job, right? But it's just an

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assistant. Right? It's it's to help you out where you may

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want a little bit of boost. I also think that I think what you you

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described is good enough factor is I think people see

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large language models and they they assume it's a search box only

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better. Yes. Well, and part of our

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challenge, you know, I was talking with a with a psychologist, David

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McCraney, who wrote How Minds Change. He's a he's a journalist, an author,

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a podcaster. He's a he's the host of You Are Not So Smart, which is

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all, you know, obsessed with cognitive bias, which I love. Mhmm. I love

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that podcast. And one of the things that David and I were talking about yeah.

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I can't remember the the name for the cognitive bias, but when we see

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something that we think we understand, we just track into

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our kind of typical neuro pathways. Right? So we

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see a text box and we go, oh, I've seen one of these

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before. This is like that. And we so and this

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this being generative AI is not like that. That being

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search. Generative AI is not search. But because of the

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kind of the the UI, we

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approach it like search. We go, okay, I want the answer. Just give me a

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list of links that I'm gonna click through and decide on. And we don't

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interrogate Google, we don't critique Google or any search

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engine, right? We don't say why we want it

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or state our intention, right? But if you start to do

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some of these fundamental kind of human

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conversational tactics, if you start treating it more like a

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person than like a search box, you get

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exponentially better results. But you're right, even

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the UI itself predisposes us to treat the

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technology and to think about the technology in a particular way and

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that is actually holding us back. Interesting. I noticed

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this in a completely random thing. I was getting,

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I was using DALL E to generate images, This is before Chat GPG had it

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in there. And I wanted to make a painting that looked like a Rembrandt painted

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a portrait of a dachshund. I know this is the most ridiculous thing.

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Right? So I wrote the prompt, I said, you know, painting of a dachshund in

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style of Rembrandt, and it produced something. It was okay. Right? It was

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good. But I was like, I wonder what if I asked

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ChatCpt to help me with this prompt? So I went over. Now

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I could do it all in 1 window. But I said, like, hey. What would

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what would you write for a prompt? Like, what would do that? And it came

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back with, I mean, a paragraph to what you said, 2 sentences. This thing came

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back with a paragraph. I mean, stuff that only art historians and art,

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students would really appreciate. You know, this type of paint, this style of

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brush, like, just stuff that I remember from art history class, but, like, you

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know, I only took that class because I had to type thing, you know?

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But but then I I pasted that prompt in there, and, oh,

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okay. It's it's it's an image. It's art. It it it's somewhat subjective, but

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the the result was so much better. Like, it was just day

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and night, and That's true. That has changed the

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way I think about, dare I say, prompt engineering. Right? Like, because you can

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because I gave a talk on prompt engineering and, like, you know, the magic of

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it, and I was like, you can actually have the models help you build out

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prompts. Yes. Well, that's that's the thing that people don't understand

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is, you know, I mean, I I interviewed the other

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day on a I've got a podcast called Beyond the Prompt, which is all about

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AI in organizations. And we've interviewed a bunch of amazing people.

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You have co founder of Typeform, CEO of Section,

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CEO of Every, the head architect at Instacart, a bunch of

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interesting people. And one of the folks we interviewed last week is a

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documentary filmmaker named Juan Carlos. And Juan Carlos has made some

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amazing documentaries. And he said he's always wanted to build

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an Ios application, but he's never had a developer and he's always seen that as

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kind of prohibited. He can't do it. And then he said when ChatGPT came

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out, he had the thought, could ChatGPT teach me how to

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code? And he built an

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Ios app by treating ChattGPT like his computer

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science TA. And he would go to the TA and ask for

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instructions. He got Chad GPT to teach him

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how to build an Ios app. Nice. You would

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never imagine doing that with a search engine, right? No. You would find it on.

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You would find it on. But you would just, and anytime he got stuck, You'd

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come back to the TA. Right? And you get more. But your

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point about people's minds being open, I think they have to be

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hearing examples like this. He literally went to

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JIGBT and said I would love to build an Ios app but I've never

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built anything. I don't have the first you know, sentence

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of ways to even describe it. If you were gonna ask a developer or if

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I wanted to ask a developer to do this, how would I even ask them?

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What do I need to describe? Tell me everything you need from me in

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order to tell me how to proceed. And he basically worked

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with it's almost reversed. We're used to being in the driver's seat.

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He basically told Chad GVT, you're in the driver's seat, please tell me what to

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do. I'll be your hands, you tell me what I need to do.

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And to me, that's just we have to start shifting paradigms. I'll

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give you another example. I've got a good friend who

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is considering a job transition. He lives on the East Coast,

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wants to move back to where his family is, and he got a

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job offer at a new firm. And he felt the job

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offer wasn't a great offer. His wife felt, we don't wanna screw

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this up. We wanna give back to family and we got a job. Just take

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the offer. And he he kind of confided in me, I

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feel like I could negotiate, but I don't want to mess things up. And I

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said, well, have you role played it with Chad GPT? And he said,

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what do you mean? I said, well, you can role play the conversation just

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to see how it would go. He said, but they don't know anything about the

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firm. I said, well, you can tell them. Ask ChadGpt, what do you need to

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know about the firm and what do you need to know about the hiring manager

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in order to believably play their role in a back

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and forth role play with with me. Interview me about the company and interview me

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about the person until you know enough to believably play

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their role and then do a 1 on 1 negotiation with me.

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Be observing the negotiation the whole time, and give me feedback not

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only as my counterparty, but also as a negotiation

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coach. That's brilliant. That's some sci fi

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stuff right there. Dude, he came back and he was like, what do I

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do now? That was mind blowing. I said, now, ask him

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to play your counterparty, but be a little bit more aggressive as the counterparty, a

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little bit less friendly. So he did that and he said, Jeremy, 2

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things I learned. 1, or actually 3 things. 1, I was

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missing my key point of leverage and ChatGPT helped me see it.

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2, I forgot my negotiating strategy in the

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in the heat of the moment, and chat g p t alerted me to that.

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Now I'm prepared. 3, I'm no longer dreading

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this negotiation. I know I can do it.

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Wow. And to me, it's like that's it's it's so different than

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saying, you know, portrait of a dash hound and, in remember

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it's like people are doing that and going, that's all I can do is like,

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you know, it can teach you how to build an Ios app. It taught me,

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I got you at GBT to teach me how to code Python so I could

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build my own chatbot using Python. I've literally never written a line of code

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in my entire life, right? It's our imaginations are the

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primary bottleneck here. And and part of the reason that our

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imagination is constrained is because we've been

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trained by search to interact

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with technology in a particular way. And what I think most people need is they

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need to hearing examples like this and they need to be getting in conversations with

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other people who are trying stuff and going, I can do that. Yeah,

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you could. I could do that. Yeah, you could. And you need to be having

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these kinds of conversations to stimulate your own thinking to then discover

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your own novel applications. No. That's brilliant. I

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mean, the whole negotiation thing is amazing. I've seen a lot of

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chatter online about people using it to, you

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know, in the job search aspect of it.

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Right? Like, here's the job description. Here's my current resume.

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Have at it, you know? Write Reno, write a cover letter that is

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gonna hit all these points and it'll do it. And, you know, but

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I mean, the whole idea of role playing. I mean, that's just brilliant. Like, I

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think I think the the the the the the $1,000,000

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statement there is our imagination

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is a limit, which is something that historically, when it comes to computers, I

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would say beyond the the the the the search

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interaction experience, we're not used to computers outthinking

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us. Yeah. Yeah. And I think that that that's gonna have

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some interesting, societal

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consequences. Right? Because I mean, I think what what freaked people out about Chat

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GPT was, you know, it looks like it's doing something

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creative, which is something that we had naively assumed, was

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something only humans can do. Mhmm. And I I I think you're right. I

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mean, I think this is not just a chat search only better, but this is

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definitely like a whole new type of computing. Yeah. I

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think it really does require a behavior modification. And

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what I I there there are kind of 2 big questions in my mind

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for organizations or for leaders who are thinking about deploying these technologies.

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1 is, what percentage of my workforce is comfortable

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with these tools? And by the way, right now, I mean, sentiment

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I read an Ernst and Young report that says 70% of people are afraid

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of AI. You know, it's like, when the when the predominant

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sentiment is fear, you're not in a position of kind of maximizing

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opportunity. Right? So Right. You so fear is gonna hold you back from

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that sense of comfort, confidence, etcetera. But then 2, so if you say so 1

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question is, what percent of our workforce is comfortable? And then

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2, how do I grow my conversation abilities?

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Nobody knows how to have a conversation right now with with HHPT or with

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any LLM. Many people have lost the art of having conversations with

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human beings, right? So, but you you really have

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to almost it's like becoming literate in a new language.

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We need AI literacy courses. We've actually developed, my

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partners and I, developed a conversational coach who gives

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daily drills that send you into ChatTPT with kind of a

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drill to build your conversational fluency. Because what we're finding

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is, folks just they don't have any imagination. Do you know that you could

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take ChatGPT, for example, and tell her what are your 5 favorite books

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and why they're your favorite books and ask for recommendations.

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It'll blow your mind. It'll give you recommendations that no human being's ever given

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you. Interesting. You could tell it you could tell it your, you

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know, 5 favorite quotes and ask for what

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are what are patterns here and what does it tell me about myself and my

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world view and what are my blind spots given these things that I'm drawn

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to. Right? You can take your journal entries and, you

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know, a particular difficult day that you've had recently.

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And then you can you can ask ChargeG PTE, can you tell me

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what are the mental models that are inhibiting my

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ability from seeing this situation clearly? And it will tell

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you, right? If it's That's wild. I'm just drawing on I

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mean, by the way, I'm just kind of a purveyor of these examples. They're all

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examples I've been hearing from people. But the point is, you can do so

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much more than you imagine. And right now, nobody's putting themselves

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or very few people even have kind of the the the wherewithal

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to say, I've gotta be hearing more of these examples. I wanna know my

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what my cognitive biases are. I wanna learn that new tool. I wanna try that

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thing. And the more examples you hear,

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the more your own imagination will be stimulated. Right? I mean, going back to idea

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flow or kind of my area of expertise which is innovation, creativity,

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etcetera. What we know cognitively is that the imagination is

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stimulated by unexpected inputs. So, you

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know, think back to Johannes Kepler gazing up in the night sky. Right? At

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that time, the predominant paradigm was, it's the firmament, meaning it is

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a fixed substance. Right? And Kepler sees a

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shooting star, and his first thought is,

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why isn't the firmament cracking?

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Right. And that is what led to heliocentricity.

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And, you know, the the total paradigm shift in the in

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the understanding of our place in the universe starts

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with a shooting star. Right? Unexpected inputs, sparks

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the imagination. And so that's that's that's a tactic

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that whether it's AI or anything else, putting yourself

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in the mindset of I need to be seeking unexpected input.

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Most people's lives are ordered to insulate

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and protect themselves from anything unexpected. And yet it's the

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unexpected which actually stimulates our imaginations and creates possibilities and

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opportunities for us and ideas. This is wild. I

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mean, like, I mean, one of the things that blew my mind was when they

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added the ability to create custom GPTs. Right? So I started

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tinkering with it, like, you know, if you listen to the show,

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we have a character named Bailey. So I kind of taught it, like, what would

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Bailey say? You know, this is the the idea for the character. This is kind

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of the her tone, and this is her personality that

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we've kind of defined. And for the last, I would say,

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15 episodes, that's actually what generates most of or all of the

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text that she says. Right? So it's kind of like I have my own

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private it's not Jarvis by any stretch of the imagination, like, you

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know, Iron Man, But I mean, it's kind of like, it's kind of like the,

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the, the, I have enough raw material there. I can

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pretend. Right? Cause the, the AI will say things like

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the, like, oh, yeah, that works. I like the way, I like the way she

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phrased that. And then I say she, because I mean, it's just funny. Like

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it's just, and and you know, there's ones where,

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there was a GPT I made where, you know, to help with motivation. It's like,

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you know, pretend you're Tony Robbins and you're trying to, like, motivate

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somebody to to do the best they can do. And, yeah, I've interacted with that.

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I'm impressed. I mean, it's just mind boggling what,

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it's mind boggling what these what this thing can do. And when as

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the engineer in me, I know this is just some kind of vector representation

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of language. It's a predictive model. Yeah. It's it's statistics. I

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think, you know, here's one thing I would say to listeners who may be dabbling,

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may be curious, whatever. If you get

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a bad output from a large language model,

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you need to start with the assumption it's because it was a

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you gave it a bad input. Right. And that's a really

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hard thing because we're we're used to saying if I get a bad output, it's

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because it's the model's no good. And where I really

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think we have to change some of our fundamental assumptions

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is the following: The problem

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isn't the technology, the problem is the user.

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And if we will take the burden of providing

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better input to the model, what we find is our mind starts

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I mean, I talked to someone the other day who said, almost daily,

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the AI does something that makes me giggle.

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And I think that that should be a goal. Like like, it's it's possible. I've

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had that experience. I mean, I'll I'll give you one example, Frank. We've built this

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series of drills as I mentioned to you. Right? That folks can connect their

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Slack or their Microsoft Teams to. And for an enterprise, they can get access for

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their employees where every individual employee gets drills on

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how to use generative AI better. Right? Well,

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we've only got a certain library of drills. Right? You know, and

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we're we're growing that. And every time we do a podcast, we learn something, we

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then we create a new drill. Right? We build that into all of the

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training information. Well, but there's still kind of you can still get to the end

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of the road. And I had this experience, and I just kind of pushed the

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coach to to just rapidly go through all the drills because I kind of wanted

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to see what happens when the sidewalk ends, like the old Shel Silverstein. Right?

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Right. What do we do whenever there's no more drills? And

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lo and behold, it suggested a drill that I had

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never thought of that was actually amazing. And I

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know I was and and I had that moment. Point being, I had the moment

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where I was giggling. Right? I think every single

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human being should seek for a moment

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where generative AI makes you giggle with delight.

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Right. Or makes you sit down in your chair and smack your head far

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ahead and go, wow. Yes. You know, I always think of Keanu

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Reeves in in the the first major movie. Woah. Like, I have a

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lot of those moments where I'm, like, wait, what? You

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know, like, wow. It's it's it's an impressive,

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and and and again, like, I think maybe being an engineer, where I

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see it is a cognitive bias in itself, right? I see it as

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some kind of vector representation of language, as being run over by some

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kind of statistical processing. But clearly,

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the sum of the parts is is more

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than the whole is more than the sum. I don't know, like, it's just one

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of those things where it makes me stop and ponder, like, what what have we

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built here? Like, what

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and what what's it doing that we can't see? Or what what what else is

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beyond there at all? It it opens up a sense, for lack of a term,

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like a sense of wonder. Like, you know, what else could I ask it? Right?

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Right. Right. And I think that that's everybody needs to get to

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that moment. And right now, too many people are sitting on the sidelines rather

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than you know, one one thing that everybody can do sorry. I wanna

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say 2 things. 1, to your point, I heard Sam Altman the other

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day. Someone asked, well, how's OpenAI gonna make money? And he said, well, we'll just

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ask the AI. We thought that was great.

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But the other thing I was gonna say is if folks are seeking kind of

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one of these personal epiphanies, here's the first. Well, the 1st drill

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in the kind of coach architecture is download Chi

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ChiPT's app and put it on your home screen. You're not going to use something

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that you don't see regularly. Right? So put on your home screen, that's kind of,

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you know, that's assignment number 1. And then assignment number 2 is

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think of an emotional decision you're trying to make right now in your

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life. Just personally, not related to work. I mean, it could be, I guess.

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But it has to be emotional. The kind of thing that you would ordinarily

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talk to a human being about. It can be

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anything. For me, like, I recently, I

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was wondering whether I should move my family. We had an opportunity to

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move. And I didn't really know how to think about it. What the what like,

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how to, to weigh the pros and cons. And so I actually reached out to

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a number of mentors and folks who I trust to talk about that. That

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kind of a topic. I I have a friend who told me he did this

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with his grandma and she asked the question, when is the time to

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move into assisted living? Right. That's a tough one. Right.

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So, yeah. So it's big questions like that. Right? Take a question like that

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that you'd ordinarily ask a trusted human being and go to

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Chattopty and say, I'd like to ask you about, for

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me, whether I should move my family to a new home.

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Before I do, would you ask me 4 or 5 questions

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so that you can better understand where I am in my

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life so that your advice can be tailored to my situation.

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And then oh, and do it 1 at a time because I'm a human and

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I can't handle more than 1 question at a time. Right? Well, then what

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ChatGPT does is it starts asking questions. Well, tell me about your current living situation.

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Well, tell me about this new place. Tell me you know, and it will ask

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3 or 4 questions and then it'll give

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amazing advice that you go, wow. That's I

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mean, you know, my friend who did this with his grandma said

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she told him this is genuinely new

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information and perspective that I hadn't considered. And all

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it took was me being 1, being willing to ask a vulnerable question, and

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2, being willing to answer a handful of questions that the AI asked

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me before I'm open to receiving input. Right?

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And it's it's it's really so taking a personal

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kind of, emotional decision to the AI is a really great

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way to stimulate one of these epiphanies. I feel like

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once you have one of these, kind of, personal epiphanies, you're off to the

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races. My friend told me his grandma's like all of a sudden going, you know,

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at the family holiday party, We're out of cream of mushroom

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soup, for the green bean casserole. Could Jaijibiti

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give me a replacement for cream of mushroom soup? Like, in what world

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does the 90 year old grandma ask that kind of question of Chad

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GPT? It's the world in which she had already talked

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about whether she should move into Assisted Living. Right? And she's had that

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personal epiphany. I feel like in a lot of companies, the company is asking

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employees, what can Generative AI do for our business?

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And most employees can't answer the question because they don't know what Generative

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AI can do. Right. So how can they know what it can do for the

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business? And so you've had some of these personal experiences.

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Don't don't be thinking about the business. Think about it it seems

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paradoxical, but I find that you have to explore the kind

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of possibility space individually, and then you start

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sparking just like grandma on the kid. Could it

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recommend a substitute for cream of mushroom soup? Well, yeah, it

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could. Could it but you have to have that personal epiphany

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first. Right. Because it's not something you would think about

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when you think about computers. Computers have historically been seen as very very

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logical, very emotional. Right? I was watching an old episode of,

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Star Trek The Next Generation, and there was 1 episode where,

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Data was asked to be and there was a line in

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there that kinda stuck me as funny because when I remember watching this when it

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originally aired, but I hear it now, it kinda makes me laugh, where he

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says, Data can be the judge of this because he's an artificial intelligence,

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and artificial intelligence have no biases, and will act unemotionally.

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And I'm kind of like, wow, that didn't age well.

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Yeah. Yeah. You know, it's right now, it's limited by our biases.

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Right. And that's the problem is we have a lot of to your point, we

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have a lot of bias. Even what you said, right, about being an engineer and

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thinking it's just a predictive model. Right. That bias limits your

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own you can't imagine what quote just a predictive model can

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actually do. Right? 100% as long as you think about it As

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as long as you think about it's just a predictive model or it's just an

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AI and so it doesn't have bias, what you fail to realize is the bias

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you bring as the co pilot shapes the entire

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trajectory of the thing. It's like a giant chameleon, isn't it?

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It is. Yeah. That's a good way to put it. That's a great way to

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put it. And the more into that end, or using that

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metaphor, the more environments that you place it in, the

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more you can appreciate its complexity and range,

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etcetera. Yeah. And this isn't we've we've used

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ChatGPT as an example, but like, so there was a,

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somebody at work had built a, basically completely open

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source language model based on documentation for a product.

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And I had meant to ask the chatbot, how do you

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connect it? How do you connect this cluster to a GPU? Or how do you

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add GPU as a resource? But what I I meant to say, how do you

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make a cluster with GPU? But I ended up typing, how do you make a

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GPU? Right? And what was what was

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interesting was I've written chatbots, you know, pre,

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transformer, and it would basically say, don't understand the question or you can't make a

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GPU or get confused. This basically gave me

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an entire 2 sentences of hey, very nicely, by the

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way, I might add, where it said, I'm sorry, but you feel like I can't

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really create a GPU for you. GPU's are hardware. And it went through and

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explained, like, the manufacturing process of a GPU.

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Wow. I I thought that was funny. And I screenshotted to the

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guy who made it because for for me, it was a typo.

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But from you know, I thought it just it was beautiful the way it

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answered it. Right? Yeah. That's great. That's Which was

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it it made me laugh. And, I don't think

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people realize that. Like, it it just because he didn't

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program it for that. He basically, you know, took a base

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model and and and, you know, sent it all our docs as kind of

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a it wasn't quite rag, but close enough.

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But it was just funny, like but it was nice about it too, which I

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thought was also interesting. But it

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was the kind of question you would get from, like, like, you know, someone who's

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not in technology. Can you make me a GPU? I don't know. I just

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I for me, that that every time I interact with this, it always moves the

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bar on, you know, where my bias was. Like, you know. Well, it's and that's

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a good that's a good thing to mention is it's it's a

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function of reps and exposure. And right now, if you

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find your imagination isn't sparked, put in a little bit more time. And

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this is where you kinda have to take on faith, but just give it a

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try. You know, to spend a few hours a week. You know, if you haven't

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had minimum of 10 hours in ChatGPT, you have

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no basis for dismissing the technology. None whatsoever.

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100%. You don't have, you know, 5 I'm looking at just at my

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Chrome browser right now. I have 5 windows ChatGPT windows open right

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now. If you don't have at least 5 windows open right now, you have it,

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that's a really kind of funny, somewhat

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binary question. How many tabs of Chat GPT do you

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have open? Usually, it's 0 or 15.

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That's right. That's right. And if you're in the zero camp, that's

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fine, but you have to go, why are really smart people

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running 15 tabs of this thing right now? Like, what am I missing?

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And how could I be this is an Ironman suit. Right? How

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could I be amplified? How am I not being amplified that I could be?

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Right? And taking that a little bit of the burden of proof and placing it

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on yourself, I think is, again, that's not something that

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we are that we are apt to do as human beings. And

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yet those who have done it have they're experiencing incredible

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benefits, incredible, delight, to your point. There's a

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lot of delight to be had, but you've got to kind of put yourself in

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that position. And I I've used it, I'll admit I've used it where I'll I'll

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write something in both my personal and professional life, and I'm like, well, can you

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make that nicer? Can you make it more persuasive? That's

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great. And it does an awesome job of that, you know?

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I'm just I'm continually amazed by it, you know. But

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and and I don't I keep it to a couple of tabs. If

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you're actively, like, having it generate text Mhmm.

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Doesn't it lock you out of the other ones too, or is that just

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you can if you had the real okay. Now now this is gonna be mind

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blowing. Cool. Yeah. No. You you know what I'll do too. I mean, and even

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for, like, demos with this Right. With this coach with this, you know, kind of

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drill coach, I'll I'll say, you know, I'll be

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in the tab on my Chrome and I'll be saying, you know, I'll be kinda

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giving instructions and I say I wanna go to voice mode now I'll pick up

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my device and I'll go into that chat so it's got all the

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context of that chat and then I'll turn it on to voice mode

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and then and and so now the user is kinda watching me with the camera.

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Well, then I wanna go back into the chat after the voicemail because I

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wanted to evaluate the conversation and I just reload the page and now

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all of a sudden everything I said that they just watched me say and everything

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that ChatGPT sent back to me is now on the screen. That's wild.

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I have to try the app in the voice mode. You have to. No. That's

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it's, you know, I mean, that's another activity. You know, again, if if folks

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wanna learn more about this research, because there's a lot of research behind this, you

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can go to how to fix it dot ai. That's a simple website that we

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set up. Because fix it is the model that we've put forth, f

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I x I t. But and we can talk to that if you

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want to. But If if if you if you go to how to fix it

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dot ai, you can download our research paper, all that stuff.

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It's all there. But one of the one of the drills that we offer in

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this drill coach is after a phone call,

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just do a verbal vomit into chat g p t. Open it up on your

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device, on your, you know, on your on your mobile device,

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put it in voice mode, and then, you know, you and I, Frank, we're talking

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right now. I might go in after and say, hey, I had a great, you

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know, lit literally. Okay. Here, I'll do it right now. Just so you can see

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how it would work. It's it's this simple. So I'm opening

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TagTpT up on my phone for people who, you know, can see. I don't

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know. And now I'm gonna go into the and I'm just gonna hit the whisper

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button, which kind of gives you voice mode. Not the headphones. I don't like back

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and forth. I mean, you can do that, but just in the text box, you

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hit that. I'll say, hey. So I'm talking with Frank right now on his

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podcast, and I wanna send a quick thank you note. Let him know how much

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I appreciate not only his humility, but also how he can share

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personal examples. It really felt like a back and forth and like a conversation. And

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so many podcasts feel like, you know, bland and,

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like they're just rote. They're asking the same old questions. I really felt like he

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was very engaged and thoughtful and it meant a lot to me. So would you

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mind to make a quick memo? Oh, yeah. And don't forget to send them a

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link to how to fix it dot ai. If you don't mind,

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just compose a quick memo that I could read, and copy paste this

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in there. So I just noticed how unstructured

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I was. Right? Oh, yeah. It was very chaotic. Very normal. Vomiting. Right? Well, I

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just did I just converted all that to text. I hit the up arrow

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and instantaneously, sure thing, here's a heartfelt memo for Frank. Hey, Frank.

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Just wanted to drop you a quick note to express my sincere gratitude for having

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me on your podcast. Your humility and willingness to share personal stories

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truly transformed our chat into a dynamic conversation, far from the

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conventional scripted exchanges that are all too common. It was refreshing to

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engage in a dialogue that felt both meaningful and genuine. Okay. I'm

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also including a link to how to fix it.ai as I believe it could offer

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additional value to our conversation and your audience. Thanks again for the opportunity.

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Right? But the point is now watch this. Now you go. It

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feels a little bit emotional. Can you make it a little bit more

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impersonal and also half the length? Because I'm afraid you may not be able

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to read it through all this. Right? And

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then again, it's, you know, it's absolutely, let's streamline it.

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Hey, Frank. Thanks for our engaging conversation on the podcast. Appreciate your thoughtful approach

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you shared insights, making it more than just the usual q and a. Here's a

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link to how to fix it dot ai that might interest you and your listeners.

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Cheers, Jeremy. That is just

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But these seem like it's easy. Like whereas whereas I might forget to

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do that, right? I might never send you it. I'll send you this just

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for your fun, right? But the point is there's so many things that just slipped

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through the cracks because like we're we're moving well. You know, right after this

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podcast I wanna go on a run. Typically, I'm stretching for the run. And

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now, Chad GPT has transformed my stretch time from kind of mindless

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to I can, you know, just unload. I mean, maybe

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sometimes I have like 3 or 4 sales calls in the morning or I've or

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I've got office hours, I've got meetings with students, whatever it might be. But

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I can just do like a verbal vomit literally

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and then ask JGPT to synthesize it for me. Send me a note to myself

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that I don't forget after I go on a run. Right? These 5 things

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I need to do. Right? And the point is, it's it's just

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about learning. I can do that? Yeah. You can do that.

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Right? And that's what we're trying to do with our drill coach is just give

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people a bunch of things that, yeah, you can do that. Not because that's

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the end point, but because it's a starting point for their own imagination.

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Yeah. I mean, that's imp I mean, that's mind boggling because, you know, there's a

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lot of, I guess, brain spillage you could capture with this and kind of, you

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know, move it forward because that happens to me all the time. I can't wait

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to see if this is gonna be integrated with Apple Auto or Android Android Auto

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or Apple Car because that would be epic. Because I get my best

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ideas when I'm driving. So so tell me about this

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FIXIT framework. Because whenever I hear FIXIT, I have a 1 year old and I

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think Bob the Builder. That's hysterical. That's hysterical.

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Well, FIXIT is just the acronym. Right? FIXIT. And it's

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basically it's we think the way we converse with AI is broken. So here's

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how to fix it. F is to have a focused question. So really be

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you know, it's not how do I create a Scratchy prototype. It's I'm trying to

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create a chatbot that teaches people how to have a conversation with

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AI. Right now, all of my users are doing this annoying thing and I

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don't know what's happening. I'm trying to, increase

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how often they return to finish a lesson rather than leaving

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and having me re engage. So F is a focused question.

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That's an example of a focused question. I is individually

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ideate. Before you brainstorm with IGBT or with a team

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think for yourself. What do I think about this? Too often people come with like

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a like, they're thoughtless. And the thing is thoughtlessness

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inhibits the context you can provide to GPT. That's what the X is

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for, FIX. X is give, provide context.

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Upload documents, here's transcripts from previous interactions.

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Here's our one pager for the Drill Coach and how we've been

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describing it. Here's a video of a user navigating for the

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1st time. Right? Whatever it is, give minimum 400 characters,

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provide sufficient context for the AI. Next I, so f

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I x I, this is interact iteratively.

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So you're having a back and forth whatever chat gpt gives you, ask it to

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regenerate. Critique the response. I don't get this. This doesn't make sense. I

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never would've thought that, right? Many times you're going to get junk

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output that's fine. Iterate, iteratively interact.

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And then T is team incubation. So once you get

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input from JGPT take it to the team and think about how do we

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commission a series of experiments to test which of these

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ideas actually solves the problem in the best way. Right? And so,

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I had a guest on my podcast describe generative AI as like an

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electric bike for the mind, which I love. Right? It's not an

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autonomous vehicle. It's not gonna do everything in parallel park. An

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electric bike, you can climb bigger cognitive hills, you can

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climb greater cognitive distances, you still have to steer the thing. You've

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got to be aware of traffic. You've got to be watching the lights. You've got

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to park the car. Yeah and walk through the threshold of your

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destination, right? And so bringing it back to the team

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and having a conversation with the team is an essential part of maximizing

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the output of AI. Right? So FIXIT, we've seen that

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folks who really provide a focus problem, individually ideate,

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provide sufficient context, interact iteratively with the

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language model, and then include their team in the incubation process,

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those folks dramatically outperform folks who just

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interact with the with the LLM like it's an oracle.

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I mean, that's very well said. I think that sums it all up, which I

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I like to fix it. I have the little Bob the Builder theme song in

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my head. I won't sing or it for multiple reasons, not the

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least of which is copyright. Come on. But,

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but what's, I mean, it's just interesting, though, like,

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it's so simple in a lot of ways. Like, this is this is but but,

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like, it it all makes sense. Right? You know? And and here's the

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thing, maybe this is the engineer in me causing more problems, because he

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causes a lot of problems.

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I get worried about token length. Mhmm. Right? And

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for those that are not aware, we're talking is, it basically

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right now, it's about 32,000 tokens. One token is, what, 3

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fourths of a word, 3 5ths of a word. I guess,

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I maybe because I try to make the prompts kind of neat, inefficient, and small,

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and not do too many iterations or provide too many samples, but maybe

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that's at my detriment. I think so. I think the

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more context you provide, the better. Absolutely. And I'd really have to

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work at the cutting and paste job to hit that limit anyway.

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Yeah. Yeah. Exactly. No. I wouldn't I wouldn't be mindful of token length. I

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would I would really I would I would bias

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towards over contextualizing. Right. Not

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Yeah. I'm gonna have to experiment that and see how much better the results get,

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because I have I have a feeling I have a feeling that we get a

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lot better. Right? And I and I know tel token link is gonna be one

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of those things that we're probably not to worry about much longer. I know

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Anthropic has their model with a 100,000 tokens. There

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are rumors of, you know, the next

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GPT, GPT 5 is gonna blow past the

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100,000, so it's not even gonna be an issue. It's not even an

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issue today, just in my mind. Yeah. I think it's something

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like minutes. You remember minutes back on cell phones? You know? Like, how

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many you have, you know, it's like, you you rarely ever went

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over your minutes. Unless unless.

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When I moved back to the US well, yeah, that too.

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But, I moved back to the US, and I had just made the assumption,

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and we all know what happens when you assume that incoming calls were not

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counted against my minutes. That was a very

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nasty shock at the end of that bill cycle.

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But, but yeah. So but ever since then, I never ran past my

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minutes. Now if I've had heard to explain to my kids minutes, they don't

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get it. So, like, they don't understand. Like, what do you mean you were charged

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by yeah. You were charged by the minute. Like, try to explain long distance to

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your anyone under 25. You

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can't you can't do it. Or what is it? 1800,

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Al Bundy. I'm not the the actor who played Al Bundy used to do that.

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Like, you can't get much for a dollar, but with 1800 and then, like, whatever,

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you'd be able to make a, like, a 20 minute call for a dollar or

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something like that. I was like It was MCI. Yeah. Yeah. It was MCI. Yeah.

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Yeah. Yeah. Kids don't want you know, like, and the other thing that that struck

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me the other day was, data

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plans. Most people, unless you're a very small

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minority of people who really, really, really use up your data plans, I'm not

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worried about using my data allotment month to month. So when

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my my oldest was a baby, we, you know, or younger or

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toddler or whatever, we would, you know, hotspot on in the car

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so he can watch YouTube videos was a special treat with my

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middle child. He was, he, he doesn't understand that like, like,

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it's like, he was just horrified to hear, like, what do you mean? We had

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to ration mobile Internet? Like That's

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yeah. That's hysterical. And they're all in the same generation. You know, there's,

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a teenager, you know, a 3rd grader and

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now, like, a baby. So I wonder, like, what the baby's gonna

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like what's his perspective on things gonna be?

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That is also a fascinating thing because for his life, chat

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GPT or generative AI will always have been a thing to him.

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And kind of like color TV was for me,

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or, you know, cable TV,

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which I guess I'm showing my age. But No. No. I'm right here

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with you. I'm right here with you. I think, yeah, it's it's

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get involved, don't wait on the sidelines any longer,

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and, and start building your conversational fluency.

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Make it personal first. I think these are simple things that every single

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and and question whatever output you're given, not not for veracity.

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I mean, certainly you can, you know, they're they're likely hallucinations. That's

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fine. But imbue your own critical

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thinking onto the model in order to coach and

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refine the output you're giving. The output that you're given.

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I think that folks would really take that seriously and take that challenge. If I'm

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get getting bad output, it's because I've given bad input. If they'd really take

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that seriously, they would experience a paradigm shift in their own approach to the

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technology. Absolutely. And even adding a simple phrase to your your

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prompt that if you don't know it, don't make it up, just tell me you

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don't know it. Yeah. Or ask me what you need from me. Ask

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me what you need from me. Right. Oh, that's even better. I like that. I

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like that a lot. And it's just fascinating, Liz, how

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quickly this is gone. I mean,

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ChachiPT has been out a year and change, and

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it's changed everyone's perspective on AI, but I think the the

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true perspective is like you said, people are standing on the sidelines wondering what to

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do. But I think it's worth exploring, if you

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think of it less as a product, but more of a I'm

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trying to do this, right? And I appreciate your help in kind of

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realizing like, Hey, as an engineer, I do have a bias against this, or a

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bias in thinking of a certain way, is that this is a this is a

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large space to explore.

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Right? There are gonna be latent space and corners of things that are,

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amuse, wonder, and delight, and maybe even alarm.

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You know, so it it there's definitely it seems like it's something

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that's worth exploring. It's not just a tool to use, certainly is

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that, but it's also a tool to explore. Yeah. No.

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I I think that's exactly right. I think it's exactly right. And, you know, for

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me, I wrote or co wrote with with my incredible

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co author, Perry Clabaughn, the the

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world's greatest book on idea generation, idea flow. You know, and it

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came out 1 month before ChatGPT, by the way. Oh, interesting.

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I've been I'd spent, you know, 12, 13 years of my life developing all this

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expertise about how to generate ideas. And 1 month later,

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a fundamental paradigm shifting technology was released. It's like saying

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I wrote the world's greatest book on retail a month prior to the internet

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coming out. It's like everything about retail is going to change. And

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to me everything about idea generation and innovation is going to

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change. And so for me, I feel it's incumbent upon me not only

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as like a moral imperative to add an addendum to this work that I put

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in the world, but even for my own expertise to be saying to be

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exploring it. How does this work? What can I do? You

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know, And it it has implications for me, but I don't think

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there's any person or job that it doesn't really have implications

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for if the if you're a little bit imaginative and if

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you're if you're willing to experiment. And if you wanna bury your head in

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the sand, that's fine, you can. But you're gonna miss out on some delight

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and some incredible relief and opportunities. I mean, just

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think back to my friend who's, you know, settling that negotiation.

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It was only to his benefit to have explored the

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the a little bit of the possibility space with chat gpt. It's

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only to your whatever your listener might be, it's only to your benefit to explore

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a little bit of your own area of the possibility space.

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And I would just not accept the the, the

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conclusion of irrelevancy. I would just say whatever I do

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personally, I'm not going to accept the premise that it's irrelevant to

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me. And if you do that, I think you're gonna be you're gonna be ahead

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of the curve, you're gonna be ahead of the competition, and you're gonna be, you're

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gonna you're gonna be delighted and enjoy enjoy the next few years a lot

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more. Very cool. You mentioned the book, IdeaFlow. Is it

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on Audible? Yeah. Oh, yeah. Yeah. Oh, awesome. Gary and

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I read it. We we we alternate chapters, so you can let us know what

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you think about Reading Voices. And, we're,

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we've been we've been thrilled with the reception so far. It was named a

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Thinkers 50, you know, top eight innovation book, which is very cool.

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And then now, just doing a lot of research myself on AI building. As I

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said, building this trail coach, building models and frameworks for for leaders. I'm

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working right now with a handful of leaders to help them think about identifying

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opportunities for AI powered initiatives in their business. So really

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working to identify those opportunities, prioritize those opportunities, make the business case

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for those opportunities. So that's where a lot of my kind of call it next

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probably 5 years of my life is gonna be consumed, is helping businesses

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identify the opportunities to to have AI really accelerate

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workflows and and turbocharge their their results.

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Very cool. I have to say, I I I wasn't going to buy

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Internet access on my flight out west today, but,

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definitely gonna do that just so I could play with I have a nice quiet

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time. I can focus and play with chat gpt, and and do

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some of these experiments that you mentioned. So

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Audible is a sponsor of Data Driven Podcast. If you go to the data

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driven book.com, it will take you you'll get 1 free

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book on us, and if you decide to become a subscriber,

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you know, we'll get a little bit of a of a pat on the back

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in the form of some kind of commission and helps us run the

Speaker:

show, helps defray costs, and convince my wife that this

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is indeed a worthy endeavor.

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So where can folks find out more about you? So, they go

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to how to fix it dot ai, that's where you can find the research paper.

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And then my website, I've got a blog and things like that. Jeremyudley.design.

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Like like the baseball player, Utley, u t l e y.

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And then, you know, Twitter, LinkedIn, all the places that I I would love to

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hear. Folks find these tools, interesting and relevant. I

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love to hear from people about their unique use cases. It's one of my favorite

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things is now hearing stories from people who go, oh, I tried this and

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listen to what I found. So please please share your

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stories with me. As I mentioned earlier, I'm a connoisseur of these stories because I

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feel like the more people who hear these examples, the more imagination gets

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sparked. Yeah. And that that is the critical thing we're missing right now.

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That's very cool. So you thank you for listening to the Digiver Driven

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Podcast. I'll leave it to Bailey to close out the show. Well,

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what a splendid voyage of discovery we've had today with the incomparable

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Jeremy Utley. From the hallowed halls of Stanford to the

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cutting edge frontier of venture investing, and through the profound insights

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of idea flow, Jeremy has truly been a beacon of innovation and

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wisdom. Jeremy, it's been an absolute honor having

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you illuminate the complex world of generative AI for us and our listeners.

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Thank you ever so much for joining us on this intellectual escapade.

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And to our esteemed listeners, you're the reason we venture into these

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fascinating discussions week after week. If today's

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journey has sparked a light bulb moment for you, do us a kindness,

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won't you? Rate and review the data driven podcast

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Haven't subscribed yet? Well, now's your chance

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to rectify that oversight. Ensure you never miss an

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episode filled with the delightful blend of data, wit, and wisdom that

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we dish out with regularity. Until next time.

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Keep those neurons firing. Questions coming. And as

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always, stay data driven.

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