Sam Altman & Reid Hoffman | AI Field Notes

Hi everyone. Welcome to Grey Matter, the podcast from Greylock, where we share stories from company builders and business leaders. I'm Heather Mack, head of editorial at Greylock. Today, Greylock general partner Reid hoffman talks with OpenAI CEO Sam Altman. They discuss Impromptu, Hoffman's new book that he co wrote with GPT4, which is OpenAI's most advanced language model to date. The past year has been marked by launch after launch of groundbreaking AI products, including OpenAI's earlier generative text tools, GPT3, ChatGPT, and the text to Image generator Dall E. Additionally, Google recently introduced its AI chatbot Bard, and companies like Tome and Databricks have released integrated AI tools for their platforms. And of course, the Internet has been abuzz with a proliferation of AI generated images so realistic they became memeified before they're discovered to be so called deep fake. Keeping up with all the AI advancements and their immediate impact is why Hoffman wrote Impromptu. As he describes the book is intended to act as a travelogue of his experience with GPT4. Above all, he sees AI as a human amplifier, but urges it must be developed safely. Safety is exactly what OpenAI is striving for, Altman says. And Hoffman's detailed chronicle of his experience with GPT4 is exactly the kind of data the organization needs to continue developing the technology with safety in mind. In this conversation, they discuss what they've learned through the development and release of each product, the various ways AI can be used for good, the potential risks of unregulated and unrestrained advancement of AI, and the need for public involvement. You can read a transcript of this conversation on our website and you can find Reid's book on Amazon. Both are linked in the show notes. Now here's Reid Hoffman and Sam Altman.

So I am here with delight with my friend Sam Altman, who has assembled an amazing team at OpenAI, who has obviously made a lot of amazing and wonderful progress demonstrating a lot of the good things that are capable with AI. One of the things I love about Sam and I think is accurate is he says, look, I help amazing people do their work and I bring a little bit of my own high ambition to help, you know, add some spice into the mix. And we do. And I that's the thing I loved about Sam and the whole team. So, Sam, welcome to the podcast. Thank you.

Thanks for having me.

You know, you were, I think, the second person I talked to about writing a book with GPT4, and the discussion came out of this. Oh my God. It's a Human amplifier. Well, let me not just kind of talk the talk, let me walk the walk or write the right, as the case may be. I could do a book that could be interesting on this and you and the whole team's perspectives on various things and AI know kind of led me to do this. And so I coincident it with the release of GPT4 because we didn't want to pre show the game. And it's a little bit of the AI is amplification intelligence or augmentation intelligence versus artificial intelligence or an aha moment, you know, amplifying human ability. Say a little bit about your view about this kind of amplification and augmentation.

I'm curious and I've been waiting for this to ask you. I realize it's not a perfect example because you're writing about GPT4 itself in so many ways, but how much of an amplifier did it feel like? Did it make it like 50% easier to write the book? 5 times? Easier to write the book?

At least 2 times and it might be more. Let me work through an answer. So one part of it was huge issue across all professions thing is solving the blank page problem. You know, you're writing a product resource document, marketing copy, legal brief, term sheet, medical analysis, commencement speech. You know, you go, okay, go into a prompt, type something and it generates something, right? And then all of a sudden you have something, a foil. It's like that's the collaborator, the co pilot to work on. And that was huge because for example, what I would do is say, okay, well how could AI really help education? Okay, what would be the critics of how, what AI would do in education? And you get both and you go, okay, let me think about them and let me put them. And that's all done in two, two minutes, right? So maybe it's 2x easier and like 10x the speed, you know, like something in the, in the dimensions. You also have this thing where something occurs to you like, huh, you know, Wittgenstein has this theory of language. Theory of language is following the rule. Well, maybe GPT4 would say something interesting about it. Especially when mixed with something else. Like you say you just read something about Chomsky and linguistics or something else and it gives you something interesting to kind of say about it. And all of that I think was really helpful. And so it, it limbered it up and it helped a whole bunch of way. Now you still. It wasn't just like press button, get book, right?

Yeah. One of the things that's been most gratifying to see is the success people have had using this as a creative tool to get past that blank page problem, to get unstuck on something, to generate a bunch of new ideas. Clearly it is not a replacement for creative work in any way, but as a new arrow in the quiver. I think people have had surprising success in many different ways and it's been very fun to watch the breadth of human creativity in finding out what to do with this.

Part of the thing that OpenAI is committed to is a lot of safety and so does tons of testing, alpha testers, beta testers, human factor stuff, hiring people to do it. Has there been any particular pieces of the creativity that have particularly surprised or.

Delighted One of the things that I hear a lot is parents of small kids talking about how every night their kids just want to make up stories with GPT4. And there seems to be like unending appetite for this from some kids and at least like, you know, hearing parents report back, some children are able to far outweigh what some adults are able to do with coming up with really creative stories and just being fluent quickly with a new way to use this, this technology. So that's been interesting because I've heard the same thing.

It's like we tell a new story every night and we kind of say, what do you want a story on? And why? I'd like to have a dragon and a teddy bear and an astronaut on a ballad. And you're like, okay, right? And I know even with GPT3, let alone GBD4, people have written children's stories illustrating sometimes through dall E and to publish those. So you know, while mine by navigation at timing, maybe the first co authorship with GPT4, there were already books being published with GPT3, with Dolly and so forth. You know, so we get to kids, we've always had a storm of education commentary, most of which I find to be having a real profound lack of imagination.

I totally get why this technology is causing a lot of change and some problems for extremely overworked teachers. That's all very natural and the adaptation is going to take some time. But on the upside, I think what's happening is remarkable and exciting. There's like a bunch of sort of boring use cases of GPT4 that I really love. Translation, summarization, there's, you know, information access. I've come to rely on it for many categories. But I think the deepest thing that I have found so far with it is the ability to learn new things better than Wikipedia, which was my current you know, leading way of learning something new fast. And I and many other people love the style of sort of interactive chat with a sort of AI tutor light to learn something new. And I am hopeful that this will be a great and new education tool.

It's good for you to have that balanced perspective, given that you guys are driving the. The creation. I am certain. And it's not just different. Students learn at different paces. Having a AI tutor who might be able to tie it to your interest if it's polar bears or your interest if it's climate change or your interest if it's Greek goddesses or whichever. But also, you know, kind of going at your pacing, being able to do stuff. But there's other things too. Like, for example, teachers go, well, wait a minute. Or writes the essay to cognitive, you know, lack. And there's one thing is like, say, look, look. It's really easy. I want to do an essay on Jane Austen and colonialism. I use GBD4. I generate eight essays. I hand those essays out as high school, probably maybe college. And I say, this is a D plus, do better. They can use that as a basis to get better. And then, and this is the real pitch to the teachers. You can now use GBD4 to help you grade. So as opposed to spending 60 hours on grading, you can spend 3 hours on grading and the other 57 hours with the students helping them. And you know, that kind of thing is just like it's there now.

Yeah, I think there's probably some concerns with using these systems for grading, but I also think we'll find ways to make it okay and work in many ways. And that idea that you can free up whatever that comes out to 95% of your time for something, I think that's a concept we hear again and again with use of GPT4 in the.

Speed of writing the book we got the first chapter is education to try to understand how we can help elevate all of us because we're all, you know, ideally ongoing through education, but of course, especially children and all the rest. And also reskilling when you get to work. But also medicine. Say a little bit about the kind of line of sight to an AI tutor and an AI doctor on every cell phone, every smartphone.

Yeah, Certainly an exciting world to get to through this lens of human amplification. The idea that we can have doctors that can provide a higher quality of care and care to many more people using these tools to automate parts of it, but keep humans in the loop. There's a Lot of companies now working in that direction. I think it's rightfully going to be a long time before most people want a full on AI doctor, but this hybrid approach where this is a tool to make our doctors much better and we can have super high quality, affordable medical care available to a lot more people, seems tremendous. On the education front, it's obviously going to get so much better, but we're sort of already there. People are now used to their phones being able to tutor them on things that they need, which is amazing.

And you know, part of the thing that I think is great about the API framework and learning. Are you seeing people doing this medical and education stuff already? What are you seeing that that already in development?

We are, yeah. One of the most fun parts of the job is getting to meet with developers and hear about what they're already doing and what they're planning to do. And certainly medical advice and tutoring are frequent and extremely exciting areas.

Did you have any reflections on the impromptu book? Things that I should have worked more on or themes I should have developed more on or things that were worth people especially paying attention to?

Well, I had a very interesting response to it and I'm not sure if it'll be what other the same way that other people respond to it, but I thought it was great. I think it raises a lot of issues. It was this weird sort of like study of someone else studying something that I had been so close to for so long. And I was like, oh man, it's like looking through fresh eyes at something that I have seen. All of the parts that don't work, all of the problems, all of the kind of limitations. And you did a great job of still highlighting those and you know, to some embarrassment in some cases. But, but it was a very strange experience, I think for me and for others who work at OpenAI in a way that's maybe different for people who didn't watch it. Like the process of creation.

Yeah. No. And look, I, I, I, I saw the, I saw the process of creation from a more of a remote. Right. Kind of helping. I will seek your feedback on how to continue to improve, to help because I think what the team is doing is amazing. Let's go to the work section. Like, I know that one of the things you guys are super directed on is how do you have a very positive impact on the world of work? Like take the analogy of what happens when you 10x every person, every function in a company. Do you have fewer salespeople? Nope. You like more sales? Do you have fewer marketing people? Well, probably not, but you probably have different because like the one that put in all the form entry and the advertising, that's probably less. But you really care about your marketing still. Product and engineering, same thing, probably. Finance is probably the same. Legal, you wish you'd had fewer, but you probably still end up with the same customer service. You probably have a huge, you know, decrease in. Because it's a cost thing. So there's some work transformation. What are you currently thinking about what this amplification means for the next 10 years? Ish. Five years? Ish. Because all this, the impacts on work will take time on what's going on. And how should people think about amplification as a path for themselves and a path for their companies?

I always try to be honest and say in the very long term, I don't know what's going to happen here and no one does. And I like, I'd like to at least acknowledge that in the short term it certainly seems like there was a huge overhang of the amount of output the world wanted. And if people are way more effective, they're just doing way more. We've seen this first with coding and people that got early access to Copilot reported this and now that the tools are much better, people report it even more.

Yep.

But we're now in the sort of GPT4 era. Seen it in all sorts of other jobs as, as well, where you give people better tools and they just do more stuff. Better stuff and amplifying your ability. I'm trying to remember where I heard this from. I think it was maybe from Paul Graham. Yeah, I think. I'm pretty sure it was from Paul Graham. There's a huge cost premium on work that has to be split across two people. There's the communication overhead, there's the miscommunication, there's everything else. And if you can make one person twice as productive, you don't do as much as two people could do. Maybe you do as much as three and a half or four people could do for many kinds of tasks. I think one of the things that we are seeing with this GPT4 application is that.

Yep. And also, I mean that's like the earlier book thing. You got a blank page problem, you have a lot more rote work amplification. So it's kind of like how do you slot in to be more effective? And when people say, well, but wait, that really changes. It's like, well, you know, mathematical intelligence used to be like, how much calculation can you do when A calculator changed that, but that's fine. We don't do the calculator or memory. You know, intelligence used to be memory, and now you can use search in the Internet in order to do it. So I have confidence that our intelligences can tune to where does. Where is the creative ad versus anything else, even for us. Speaking more for myself than you older.

Folk, I'm old enough now. It's a. You notice that. You notice it when it comes to, like, you get in these, like, crazy work periods and the late nights get a little bit harder. Early signs.

Yeah, indeed. And it doesn't get easier from a generation ahead of you in the work topic. Part of the reason for writing the book was to say, look, there's. There's so many amazing things we can get to. We can get to an AI tutor for every person, every child, an AI doctor for people who can't afford medicine or people who don't have access to. Or companionship with the doctor, you know, et cetera, et cetera. But everyone worries about it because they worry about what. What happens with my job. And part of what I wanted to kind of show is like, look, here's. Here's an instance of using it with, you know, smart, knowledgeable person using it for actual work. And the work is writing this book, right?

Yeah. I love that you did it. I think it's so tangible and it, like, it made me want to write one too.

I look forward to it. I will be one of your dialogue participants. What do you think about the use of GPT4 for the kind of. The information problem? And, you know, I actually don't think we've specifically talked about this. I mean, obviously there's a lot of criticism saying, look, it's a generative, AI, is very good at generating generation, is not necessarily truthful. It can be targeted in any direction, which includes misinformation. Hence we have an amplification of the social media and another kind of things problem, and therefore, oh, my God, this is an assault on journalism. I don't agree with this point of view, and although I do think one has to work to make it good. What are your kind of working thoughts about how to navigate this in a way that's like collective learning positive. Collective truth positive. We facilitate.

One of the areas that we most need to figure out is how to get these models to be super reliable while not losing the creativity that people like or, you know, giving settings for when you want one or the other. We don't have the answer here yet. We Have a bunch of ideas and we're able to make week over week improvement in the problem. But, you know, telling you when we're going to be able to really get to a system that is accurate to what you as the user want, I carefully use that instead of saying a system that is true because that's really hard. You know, I think we're, we don't have an answer. We're making progress, we need some new ideas and it'll get better.

I mean, one of the things that's contained in your answer, I think is really important is the dynamics of learning. So, like, if you said, well, we have an agreement about what a kind of social model of truth or facts is that we update and so forth, let's make it easy and say, well, it has to do with science and facts and you know, the kinds of things versus even, you know, grounding in, you know, some kind of truth process, which is usually collaborative human study. Well, you know, easy enough to take to train an agent like that. Put it in the browser and then, you know, that kind of the, hey, I'm like this thing like you, you hear, you know, the earth is actually flat or the moon is made out of blue cheese and it says, no, no, no, you should look over here for good information.

Look, those things I think we can get, we can get right? The following example that I'm going to give. I don't even know if it's true or not, which illustrates how hard this problem is. Maybe I just heard it repeated by people so often I now believe it's true. But I think that there was a time where some of the social media platforms were banning people for saying that Covid may have leaked from a lab and that, you know, you can't say that. It's, it's xenophobic, it's racist, it's hateful, it's, it's inaccurate, it's, it's fake news, whatever. And I think people were just having like, posts about that deleted. And then all of a sudden the kind of elite opinion on that changed. I remember there was one article that came out that seemed to really change it and, and like, you know, you see this big backtrack there, but, but you literally weren't able to discuss it in, in like the channels that are the de facto important channels now. And that's the kind of thing where if you let someone dictate truth, I think you do something dangerous. But there's lots of easy examples like, you know, the earth is not flat, the Holocaust did happen. I think we can make a system where we're willing to make editorial calls on those two. But there's a lot of other stuff where I think all of the trickiness comes in.

I chose easy examples. I noticed you didn't dispute the moon is made out of blue cheese. Maybe you haven't.

I'll agree that the moon is not made out of blue cheese too. I haven't personally been there, but it seems like a safe bet.

Yes, but actually I think how you can train these models, as you say, well, it doesn't have to yield an opinion on everything, doesn't have to yield an opinion on controversial topics or places where humans like for example, a one training answer is oh, on this topic, there's a lot of human dispute and.

We give those answers a lot. And we're now experimenting with more steerability of the models where a user can say a lot more about how they want the model to behave in different ways. And so if you want a high degree of careful calibration, the model can do that. And if you want something else, the model can do that too. And if you want the model in a very creative mode where it tells you a story about astronauts going to the moon and finding that it was made of blue cheese, there could be good reasons for that. That could be a fun sci fi story. One size fits all. I think people are finding more and more it doesn't quite work. Things they think they want a model to do or not do or never do doesn't always apply and it's uncomfortable. But giving the user a lot more control is something we think is important. And if you want that story about the astronaut going to the moon and being sure it was made out of blue cheese in some context, that's totally fine. But it's telling you something that is clearly not a fact in some other sense. Can I tell a quick story related to anything, but I just think it's this most beautiful story. There was this astronaut who talked to reporter, a reporter, years decades after going to the moon and they kind of asked him what it was like and he said, you know, I kind of forget about it. And then sometimes I'm out at my backyard at night looking at how beautiful the moon is and I just remember like, oh man, all these years ago I went there and walked around on it and now I forget. And I think that's just like an amazing story. But I also think when we kind of look back at this age of creating the first AI systems, we're all going to have our own version. All of us that have been involved in are going to have our own version of that.

Yeah, no, I completely agree. The, basically the last chapter in the impromptu book was my very strongly held belief, but also argument is that we evolve our humanity through our technologies. We evolve our humanity through the clothes we wear.

Yeah, yeah.

Chairs, we sit on the podcast mics, we talk to each other, you know, across, you know, video conferencing, you know, all of this stuff. There's a number of major scale problems facing the world. Climate change, economic transformation and elevation of humanity, people adapting to the new world, whether it's education, skills, et cetera, social justice of various forms. I know one of the ones you and I talk a lot about is criminal justice and having fairness across the society. Are there any that you think that AI is not a particularly good fit for? And then after that, what's a surprisingly good fit where people just had probably hadn't occurred to them.

So I think technology is the fundamental ingredient in making the world better in all of these ways. But technology on its own doesn't, always, doesn't usually do it. You need society, you need the participation of people, you need the kind of contributions of all of our institutions and what has made this, you know, from the enlightenment until now era so impressive, coming together with technology and also to enable the discovery of and creation and distribution of such technology to make this work. So if AI can start churning out new scientific discoveries, that'll be wonderful. And that's personally one of the things I'm most excited about. But even to kind of get those into the hands of people and to do it in a rapid and just way, you need all of the rest of society to play its role too. And so I don't view this as like, AI is just going to come along and wave magic wand and fix everything. It's like AI is this new meta tool that humanity has to enable us, along with all of our people, institutions, whatever, to go to greater and greater heights.

Like, for example, is it climate change? Is it the opposite of poverty?

If we can build AI systems that help us cure many disease, figure out the cure to many diseases, that's like a pretty big triumph. And this is not my field of expertise by far, but the people that are in it seem so excited about what this is about to unlock.

Yep, I completely agree because, you know, by the way, you know, diseases are broadly pretty indiscriminatory across rich, poor, gender, race, etc. You know, what do you see as kind of how AI Is a platform like you just recently did, you know, kind of like chat. GPT is a. As an API with some announced partners and other kinds of things. How should people think about the platform as, as they are navigating their lives?

I think the greatest platforms people pretty quickly forget are platforms. So there was like a while after the first smartphones and app stores launched and all these companies were saying, I'm a mobile company. And that was like a big deal because they were on the mobile platform and. And today it'd be ridiculous to say you're a mobile company because every company has a mobile part of its strategy. And we're going through a moment right now where everyone's talking about AI. AI is talking about the future. Probably true, all these AI companies, whatever. My hope is that 10 years from now, intelligence is expected in every product and service and it's so ubiquitous we forget it's a platform. It's just part of everything we do.

And what do you think the probability that in addition to the kind of large language models scaling, refining them, that there is another amazing major component that will be discovered and, or deployed in the next three to five years?

Well, discovered high, you know, may take longer. But my belief is we need at least one more really big idea we have.

Journalism is a chapter because we want to kind of show the actual positive impact on crafting perspective and news for people. We as human beings share things with each other. It's part of the reason we value journalists, though, even though, you know, some people like their flavor of journalists better than other people's. How would you tell a journalist to use GPT4 today? Like, this is how it helps you.

I talked to a few journalists since the GPT4 launch and I would ask this question because always curious to know more. Not useful at all, at least in the ways people have found so far for the reporting process, but very useful for the drafting, writing, synthesizing part of the process and the ability to like, put a bunch of notes in there, ask questions about it later, help kind of find themes between things. People have found a lot of use there.

That's interesting. And you referenced Wikipedia before, but it's like, it's like a mini. It's like a research assistant that gives you a mini brief right away. Not always 100% accurate, especially when you get to like very specific details on very specific questions. Like when I asked it, did Reid Hoffman make a knockoff of Settlers at Catan? And if so, what was it? It said, yes, he did, which is true, you know, I made a game called Startup Silicon Valley which I only give to my friends who've already bought settlers. You know, you have a copy at least one. But then it said and what the game was, was Secret Hitler, which is actually in fact a board game made by the cards against humanity people. I've heard it's quite funny, but not a game that I even crack the box on yet, let alone co design. And so you know, I, I would say, you know, look, cross check this stuff, but the quick research assistant briefing that's done immediately in like you know, 30 seconds is I think actually part of it. It is not a, you know, tell me what I should say about Sam Altman or what question I should say that makes sense and that's part of the, you know, use some imagination. I mean a little bit of the. Again, part of the reason why, you know, the impromptu was kind of this travelogue across, you know, that's a great phrase for it.

That is what it felt like to read.

Yes, exactly. Across these domains of human existence and say just like when you start encountering search, when you play with ChatGPT or GPT4, just try something like and, and literally think to yourself, how do I try something that may be different than I've ever thought about trying before? You know, like the one that, that kind of may seem pedestrian, that surprised me was the well, I got these seven ingredients in my refrigerator. What should I make for dinner? And it would just what occurred to me to ask that question, like you certainly wouldn't put it in, put it in the, you know, search engine. You would put it into Bing or Google or whatever. And here it's like, well, you could do this, you could do this, you could do this. Or with those seven agreements, you move for Thai or you're in the mood for, you know, Mexican, like oh, all right. One of the things that I think is too often not said about the transformation of work that AI and making intelligent tools going to be is by moving it out of more of the rote stuff you can also not just make it into more creative stuff. And so with which some people are fearful of, but also the more joyful parts of work.

Yeah.

You know, and I think that that transformation of joy is again amplifying human beings.

I deeply believe this. It's a little too early to declare victory on it, but it certainly seems like people stay in the flow state much more, stay in the parts of the job they enjoy much more. AI is like good at doing the repetitive stuff that most of us Just find a little bit monotonous. So anecdotally, we hear reports of this a lot.

Yeah, well, and actually I did that because, like, for example, part of, like, usually in writing books, having done it before, you know, you get to periods where you're just slogging through and getting it done. And I'd say, well, I have a break. I kind of do a prompt to discover something kind of fun and interesting. I think, hey, let me take this section of the essay that I'm doing and, and let me ask you before, make it into a sonnet or make a, a ballad about this. And I look at it and sometimes I go, okay, that was cool. I put it aside. Sometimes I keep a copy, Sometimes I go, oh, that was kind of interesting. And that, like, keeping me limber and fresh versus the. I just have to figure out the next sentence. Everybody has been sweating blood in order to make it available for people. Is there anything that you use GPT for that to your delight?

I mean, I mentioned this before, but it is still so delightful. To learn something new and feel like I just got a cheat code is very delightful. Another one is we just released this very early preview of plugins and I think the fact that GPT4 can now, with a lot of limits, write and execute code is so cool that, that just as like a citizen of humanity, I feel delight every time, even if it's just like doing something very simple.

One thing I think it's probably important that we haven't gotten to that I just can't, I don't think can be said often enough is what you guys are learning about how to align these systems with human interests and human values as they scale.

It's nice of you to say. I think we have made real progress relative to what people thought this was going to look like. But we do not know and probably aren't even close to knowing how to align a superintelligence and RLHF is very cool for what we use it for today. But thinking that the alignment problem is now solved would be a very grave mistake indeed. I am hopeful that we're going to make better and better tools that are going to help us come up with better and better alignment ideas.

I think that that answer is exactly right because staying deeply focused, deeply concerned as the dynamic thing proceeds is the way to maximize safety.

Well, I think it's worth being very precise here. What we do is we know how to make GPT4 safe, safe in the ways we know about so far. And again, like, big surprise Big, big success, but very, a lot more work in front of us and thankfully we now have a new tool to help us.

Yeah, I think people should take heart and positive energy out of the. That's the right way. You should be responding. You should be, oh no, no, it's no problem. You know, we're just cruising down the roads, no problem. This is, no, no, we're paying a lot of attention. It's the problem will require more work to improve the solutions we have. The tools we have can continue to improve it. And by the way, so far as we scale, we are learning better ways to use the tool to help us align better. Right. Even though there's a, a lot of open questions and a lot of, of journey we're going ahead. And this is part of the thing is when people look at a dynamic and future with change, they always tend to go, oh, what about the Boris case? You're like, okay, well what about the best case?

Right. One thing that I think is great about people using GPT4 and ChatGPT is they see, they feel the upside in a way that if you only hear about it, you, you discount and you really feel the downside. Now the downside is still really there, but using it I think adds some healthy caution to people too. But, but it really does let people taste the upside and figure out how to participate in this new world we're all going to create together. And I think that's great.

Yeah. The parallel that I see is that when you ask someone who's part of the creative industry, writing, painting, photography, whatever, and they haven't had access, they haven't tried these tools, they're always like, oh my God, is it going to take my job away? Is it now going to be the journalist, the author, the novelist, the, the painter, et cetera? Then when they play with it, they realize, oh my gosh, this could be a tool that really amplifies what I'm doing and they begin to see the upsides. And that's precisely why like I created Impromptu also with the pun in the name, I am prompting you as, yes, as part of this is to say, try it. Right. You know, it's a little bit like if someone described a car to you and you weren't familiar, it's like, well, it's a two ton death machine that can run over children. You know, causes 40,000 deaths per year in the continental United States. Wouldn't you like to get into one? Right? And then you go for a ride and you're like, whoa, this is Cool. Transform space. And I can do all these things. And it's that kind of thing of, you know, try it and realize what all the options are. And by the way, of course, you have to still be attentive to safety. You gotta go, all right, how do we make these things safer? You know, how do we put bumpers and automatic crash detection and, you know, other kinds of things in it, you know, lane change. And so in order to, you know, make them a lot safer, you know, decade after decade and Turing. And that's what I think the AI stuff is, too.

Sure.

You know, you've obviously been, you know, kind of over the last couple weeks, you know, kind of helping introduce the world to chat. GBT. GBT4Impromptu is an effort to try to. To kind of show why AI can be amazing for humanity and why I have actually belief and confidence that we really can get there just by intentionally, you know, metaphor driving. Driving it there. What would you say that you've learned in the last couple of weeks that you'd want to share with as, you know, a final thought? Share with listeners of a podcast about. Here's what we're trying to. Here's what we're trying to get to with AI in the next few years and the next decade.

You touched on at the very beginning. So it's a great thing to close with this idea that this is a tool of amplification and this is a tool that makes you do better at whatever you need to do better at. And it's. We can say that it's nothing like just trying it. So just go try it out. That's my advice. Um, and we. We really hope you love it. The feedback that we get from people is very helpful. As we think about future versions. People really have found new, incredible things, new places where it breaks. But. But, yeah, the ability to sort of, in whatever way you'd like to be amplified, use this tool to amplify yourself. I think that's the message that I'd love to end on.

Absolutely. And it's the reason why the book description for Impromptu is. It's not a read, it's the starting of a conversation. And so with that, Sam, thank you for this conversation and, you know, as always, look forward to talking to you soon.

Me too. Thanks, Reid.

That concludes this episode of Gray Matter. You can read a transcript of this conversation on our website, and you can find Reid's book on Amazon. Both are linked in the show notes. And if you aren't already a subscriber to Gray Matter, please sign up wherever you get your podcasts. I'm Heather Mack. Thanks for listening.