Reid Hoffman (2:14)

What?

Scott Galloway (2:15)

For what?

Prof. G (Host) (2:16)

For a speaking gig.

Scott Galloway (2:17)

Hold the phone. Now we know why my speaking revenue has crashed. You're taking my gigs. Let me get this. Who's bringing you to Florence?

Prof. G (Host) (2:26)

Royal bank of Canada.

Scott Galloway (2:27)

RBC is bringing you to Florence.

Prof. G (Host) (2:29)

That's right. Florence, baby. I'll be there for one day, so I'll give that. Do that. Probably try to have some fun as much as I can. But we'll be recording at the same time. Coming back, then going to Texas.

Scott Galloway (2:41)

Oh, well, that should be easy. There's a ton of direct flights from Florence to Houston. Oh, my. You're literally living the life I had in the 20s and 30s, and let me tell you, it's exhausting. Look at me. You're going to look like this.

Prof. G (Host) (2:53)

I'm anxious about it for sure.

Scott Galloway (2:54)

So you are now getting my speaking gigs. And your memo to self undermine Ed's credibility. Begin slowly diminishing his professional standing. Kill the prince. Okay. Okay. That's great. Congratulations.

Prof. G (Host) (3:11)

Thank you. Yeah, I'm excited. It'll be. It'll be fun.

Scott Galloway (3:14)

That's really exciting. Have you been to Florence before?

Prof. G (Host) (3:16)

No, it's going to be my first time.

Scott Galloway (3:17)

It's. I love the tourist places, people, so. It's so touristy. Like Venice and Florence. I love highly touristy destinations. I think they're great. It's a beautiful little city.

Prof. G (Host) (3:28)

Why are you a fan of the tourist traps?

Scott Galloway (3:30)

I went to Florence right out of college with a backpack and a Eurail pass. Do young people do that anymore or do you just sit at home on their phones?

Prof. G (Host) (3:40)

Yeah, of course. Interrailing. That's what I did, too. Yeah, a little bit. I joined my friends for the latter half, so I was mostly in Eastern Europe. We were in, like, Slovenia, which was not that interesting. But Florence would have been fun if. I'll probably have, like an hour to. To myself if I had to see one thing in Florence. Do you have any recommendations?

Reid Hoffman (3:58)

The honest answers.

Scott Galloway (3:59)

Get fucked up. Eat a lot of good food. I don't. I don't have any, like, cultural landmarks or in. In the know. And Florence with Scott Galloway. I couldn't be less Stanley Tucci. I couldn't be. I'm like, where's the bar? Where's the bar? Yeah, that's not. That's not my gig, but I'm very happy for you. Should. Oh, we should get on our promo. Ed, how are ticket sales going? What's going on with our tour?

Prof. G (Host) (4:24)

I believe they're going quite well. I think we're close to sold out in San Francisco, to be honest. I haven't checked. So I'm sort of speaking out of my ass here.

Scott Galloway (4:34)

New York and San Francisco are almost sold out. We have. Very soon we're going to be announcing speakers in la. Miami, and I think. Are we close to New York? I think we're close. Very excited about that. We're doing kind of business of entertainment or business of nightlife. Miami. We're going to do business of money or business of Finance in New York. We're going to do business of media entertainment in la, business of tech in San Francisco. You know, that kind of stuff. But if you are interested in getting a ticket, please go to Prof. Marketstour

Prof. G (Host) (5:04)

Prof. G Markets Tour.

Scott Galloway (5:06)

Thank you Prof. Gmarketstour.com and we look to see you in either LA, San Francisco, Chicago, Miami or New York.

Prof. G (Host) (5:17)

Absolutely. And if you're watching us on YouTube and you like what you're hearing, hit subscribe. And if you're listening on Spotify or Apple podcasts, hit follow. And with that, shall we get into our conversation?

Scott Galloway (5:28)

Let's do it.

Prof. G (Host) (5:32)

Over the past month we have focused on the downsides of AI, from real world violence targeting industry leaders to growing political pushback against data center expansion. So this felt like the right moment to bring on someone who believes that AI can serve the public good. Our guest has spent years making the case that AI will improve our lives. He has also created, advised and invested in some of the largest and most successful technology companies in the world. Few individuals sit closer to what might turn out to be the most transformative technology of our time. And so we wanted to find out what is actually happening on the ground. Here is our conversation with Reid Hoffman, co founder of LinkedIn Inflection and Manus AI partner at Greylock and author of Super Agency, with what could possibly go right with our AI future. Reid, great to have you on the show. Thank you for joining us. I want to start with some specific news that we saw this week that is making investors a little bit anxious, and that is this APE OpenAI news, specifically that they missed their revenue target last year. They also missed their user target and they're obviously set to go public soon. It should be one of the most important IPOs ever. And suddenly investors are very anxious about this company and anxious that they're actually not growing in the way that they had expected. And you are in an interesting position because one, you're on the board of Microsoft and Microsoft is obviously one of the largest shareholders in OpenAI, one of the earliest investors. And also you are an early investor in OpenAI through your VC firm, Greylock. So let's just start with this. What do you make of this news and should investors be worried about OpenAI?

Reid Hoffman (7:19)

Well, ultimately, as an investor, I'm not worried. I mean, part of it is the company had very aggressive targets. And so when you have aggressive targets and you kind of go in a little below them, that's actually not the kind of thing that I worry about that much. And classically, the Reason why public companies, because most public investors tend to want reliability quarter to quarter, tend to do their best to be on target in terms of what they're saying because there's this kind of a reliability thing. Whereas I as a private investor tend to be the just established, the really, really strong basis. And so you know, for me the thing I wasn't tracking so much was, you know, last year's revenue, last year's user count, those are great in the making progress. Obviously we'll need to grow more too, but a lot more. But the, the real question that I was like very happy to see was, you know, the, the 5.5 release because you know, I think the thing that I'm most tracking is is OpenAI continuing to deliver some of the world's best, you know, kind of technology frontier models and so forth. And you know, that's, that's I think the precursor to everything else. And that from every source I've seen and multiple different benchmarks and multiple different engagements has been, you know, is the kind of the new world leader in quality model. So that, that's more of what I pay attention to because it' you know, with investing, it's downstream effects, it's, you know, what does next year look like? Is the most relevant question.

Prof. G (Host) (8:47)

Does that make you concerned? It's an interesting point. Like early stage investors, venture capitalists, they're more interested in the technology, they're more interested in what's going to happen 10, 15, 20 years down the line. Public markets investors are more interested in what's happening right now. I mean we're literally, we read quarterly earnings, we look at what happened last year, we look at what happened in the previous quarter. It's much more of a sort of backward looking practice which seems to be like it might be a big problem for OpenAI if they are to go public at the end of this year because suddenly they will be scrutinized for their financials. And so I wonder if that concerns you that suddenly the company is leaving an ecosystem of people and investors that are okay with financials that might not make sense right now, but then suddenly they're going and pitching the company to a group of investors who care a lot about that stuff. Are you worried that maybe they will get punished or that they will have a hard time in the public markets when that time comes?

Reid Hoffman (9:48)

Well, if they can't establish themselves, there is a small set of companies and it isn't just Tesla, which is probably the extreme example of this, which is kind of betting on the future But Amazon for a significant number of years and others that say, hey, I've got a foundational promise of which I'm going where investors go. We believe in that future and so we're buying in that future. And the fact that the, you know, the, the current, you know, you know, PE comparables, other kinds of things, you know, don't make sense on a quarter by quarter basis. Even factoring in a, you know, an interesting Keger or anything else. I think it'll be for all of the AI companies that are, you know, kind of, you know, prepping and considering going public. It'll be important to establish that basis because I think the first year or two will look a lot like, you know, kind of early.com companies, some of which were complete flame outs and some of which were enduring institutions. Amazon being an example.

Prof. G (Host) (10:49)

What do you make of the unit economics right now? This is something I've been thinking about. When we think about these companies like 10 years down the line where currently the unit economics don't really make sense. Like the cost to build these models is so incredibly high. And that is why OpenAI and Anthropic, any of the sort of foundation labs are burning a lot of money right now. And it almost seems as if the only way that this works out from the perspective of the business model is for these companies to become like essentially utility companies, like almost have these monopolies over compute. And Sam Altman has said this, he said that eventually he could see OpenAI becoming something like a utility company down the line, which to me is quite an interesting perspective because it's quite different from what we saw in the dot com boom where we've had, you know, a handful of companies, we might call it an oligopoly, but a handful of companies operating in the same space. I mean, where do you see the business model trending further down the line?

Reid Hoffman (11:57)

Obviously, you know, as you know, you have to distinguish between the training costs and the inference costs. And one of the things when you look at these numbers and the inference costs are actually in fact pretty good economics for inference. But obviously you have an exponentiating training category. And so the question is, is you're doing this exponentiating training. And I do think that at some point the training cost, even though there is a goal to get as strong as you can there, because then your quality of model, you know, kind of dominates through all of the different inferen units, essentially, you know, at some level of, of exponential that starts asymptoting just because it doesn't make sense within, you know, how many gigawatts do we have? What, what kind of economic cost do we get there? And I think a little bit of the, of the race is a race to that asymptote. Now where is exactly that asymptote is I think somewhat governed by availability of capital from investors believing and then the delivery of revenue. Now part of the delivery of revenue is not just the current services where you say, okay, you know, OpenAI is dominating the kind of chatbot and kind of what the consumer and kind of interaction with that service is. Anthropic is doing the coding side, you know, followed by OpenAI on the coding side in terms of how the API encoding works. But like this has got to be just the beginning. Part of how you're looking at these AI models is not just the provision of tokens, which obviously is interesting and across a number of things, but what is the output that comes from now that software engineering can be much more broadly spread and a whole bunch of areas which otherwise wouldn't have been able to afford software engineering can now do them. That can affect what their productivity of their areas. What happens there, what happens in services firms when a bunch of different services, you know, take legal or accounting or anything else can be done with intensive, you know, kind of amplification of this and that. It's not just the question of like, you know, paying seats in the software basis, but what is the delivery in terms of the margins of, of what the delivery of the service is and, and where all those economics play out is I think very early in tbd. And you'd say, well, should we wait to go public for those? I actually think one of the things when you, you know, you, you two know this better than I do, but I think one of the things that's been a bit of a kind of call it a social problem over the last few decades has been so much of the growth has been contained only to the private markets because of like, let's delay going public until it's, you know, extremely stable. Which means that a lot of folks who, who cannot participate in the private markets only get exposure to the public markets. And I think that's one of the benefits of having some of these AI companies. But I think it's early relative to what are the business model is going to be and then what is that revenue going to be and now utility. I think in terms of the fact that any task that you do with language or information, I think will have AI participation at some level of depth, whether it's complete automation, whether it's augmentation, whether it's assistance in various ways. And so the spread of that is I think a good measure on utility. I think one of the things that's good for society is the fact that we have multiple providers of these frontier models. So they're competing with each other in terms of, you know, pricing, in terms of availability to entrepreneurs, building other kinds of different services, in terms of being able to, you know, like the best governance mechanism is, you know, relative to the health of society for the cost of things, oligopoly, monopoly, et cetera, is to have competition which then brings the price down. And I think that's something that we are also seeing. So the utility question around, kind of around the, the like, should it run like utility? You know, I, I don't know how, you know how well utilities are thought of in the uk. In the US utilities are kind of a disaster. So you don't want it run like that.

Scott Galloway (16:03)

So I'd love to just get your, I mean granted you have a, you might have a bias because you're on the board of Microsoft, but and you're an investor in several AI platforms or LLMs. Can you give us a lay of the land in terms of the competitive set? You know, obviously OpenAI, anthropic, Google with Gemini and then the Chinese models and I'm sure there's a bunch of others. But give us what you think is the competitive landscape right now.

Reid Hoffman (16:28)

So I think, and this is to some degree a good news for startups and productive startups is I think the strongest positions are OpenAI and anthropic. I think in the traditional big companies Gemini is, is kind of next and I think we'll have a bunch of different efforts from Meta, you know, Microsoft on its own obviously uses a lot of OpenAI right now. You know, Amazon, who knows where Apple will play out and all this stuff since you know like they still don't seem to realize that Siri is like you know, 20 years old kind of in, in tech terms. Now for the Chinese models the interesting question will be like there's a lot of good open source models that pretty clearly have some roots in distillation from kind of the major western frontier models. And I think part of what we're going into is an area where that distillation will get a lot harder. Now that being said, the Chinese are building up compute, building up chips, have extraordinary amounts of talent, hard working great tech companies. Matter of fact the Sea Dance, you know, multimodal video Model is I think amongst the best in the world. So I think it's already, you know, that you already have stuff that's kind of playing there, but like, and then you get a kind of a jagged edge. Like you go, okay, let's go coding specific. So most developers will say Claude code. Part of the reason is because Claude code has got the best model, I think the best interaction thing for iterating through kind of the amplification of a software engineer. But then the in depth engineers that I know who play with them go OpenAI codecs because it spends. It's much more useful at like call it, you know, 20, 30, 50, 90 minute reasoning, long tasks that play to a harder engineering. And so they prefer that versus Claude code. And right now at the moment, that's it. When you get to like people who have exposure to it now some people then go, okay, I can't afford either of those, so I'll use Quen, you know, the, the Chinese open source model, which is quite credible. But when you think about the fact that you know, when you're looking for coding, just as one instance, you're actually looking for really part of the reason why you pay, you know, software engineers and all the rest, you're really looking for something that's quite good and quite reliable, that doesn't introduce bugs. Obviously we have mythos coming with questions around cybersecurity and what does this all mean there and that matters too. So you know, the. I tend to think a little bit on the coding side for your particular coding problem. It's a little bit like what we call in blitzscaling a Glengarry Glen Ross market which is, you know, first price Cadillac, second eyes steak knives, second price steak knives, third prize, you're fired. So roughly. But, but then it's different across, you know, like Images. Like the OpenAI Image Generator is I think now like, like I've been wanting to create graphic novels for eight years with AI and I now I think I can. So that's interesting. Anyway, so they just. We could go, we could spend the entire time on the, on the, on the different capabilities of these.

Scott Galloway (19:53)

So it's a good segue into talking about mythos. So Anthropic described mythos. It said that it turns every computer into a crime scene. And I'm trying to distinguish between what is responsible, warnings about their own product and catastrophizing as a means of fundraising. Because everyone's talking about mythos right now and there's sort of this and it's prevalent. I Think across a lot of AI that my technology is so amazing that it's going to reshape the world, both good and bad. Please invest in my series D at 100 times revenues. How much of this is responsible warnings from Dr. Frankenstein that Frank could be dangerous, and how much of it is just, quite frankly, is just fundraising?

Reid Hoffman (20:39)

1. I think the anthropic people are very earnest, principled, and honest. So I think there's a fundamental basis which is completely honest. And here's a simple way of making that the case, which is if you said the. The minimum that Mythos is is an ability to have an infinite number of quality cybersecurity engineers who are penetration testers. And it's not infinite, obviously, because there's a compute cost for running them, but you could take a thousand of them and run them in a direction you end up, you know, if it's just that you end up with a re. Changing of the cybersecurity landscape because we have billions of lines of code that essentially haven't been touched, and partially because there hasn't been either an economic model for the number of cybercriminals or the number of people employed by rogue states to go after any other than a certain set of systems. But it broadens the range by the ability to just kind of spin up many new penetration testing engineers, you know, with a kind of an AI mechanism. And that's the minimum that I think you could look at the. The discussion around Mythos and its cybersecurity issue is I think that it's actually somewhat better than that. And I don't mean that that's amazing what I just said, but I don't know yet how much more right. Like, is it. Is it. Oh, my gosh. You put a. A classic, you know, call it a, you know, top 10% cyber security engineer and put them against, you know, kind of a couple of Mythos agents. And do they outpace that person? You know, it's unclear to me. Does it think in ways that we haven't thought about before and generate new patterns? That's unclear to me, but you don't need those to have this be a massive, you know, kind of shift in how we think about cybersecurity. What are the kinds of things we need to do? And so I actually think that they're doing a responsible thing by saying there's an important change coming and we need to get at least the essential systems ready.

Scott Galloway (22:56)

We'll grant you more than a minute to answer this because it's a difficult or, you know, we're going to need a bigger boat. But Andrew Yang, who was on our podcast a few days ago, said, you know, he's having a moment, right, because he sort of in some ways predicted all the fears, the sum of all fears around capital destroying labor. And there's, you know, people would point there's already evidence around youth unemployment increasing, a lack of hiring, layoffs at some of the early adopters. We. I won't use we. I have taken the view that we have been to this movie before and some of the catastrophizing around the destruction in the labor market doesn't recognize the new opportunities and the new jobs that'll be created. So I would love to just get your thought and take whatever time you need to describe what you think the impact on the labor market is going to be of AI.

Reid Hoffman (23:53)

Every job that uses language or information will have an AI component that will range in certain cases from automation, in certain cases, much more AI work, in certain cases, kind of AI amplification or augmentation of human labor. And I think that will be true of all of those things. And so almost every industry, because if you think about like even like steel manufacturer, you still have meetings, financial analysis, you know, kind of capital, other kinds of things, you know, legal other kinds of things, all that play in it, you know, strategic planning. And so that means that AI will touch everything now. And I by the way, inherently also agree with you that one of the general problems when you get new technology, kind of put this in super agency is you go, well I can see if I take jobs as a fixed number that do not grow and do not change. And I can see that a bunch of them will be, you know, now will the horses then care? The buggies will go away and we'll have cars and like all the grooms people will go away and all the horse carrying jobs will go away and all the horse cleanup jobs will go. And I can tell that and you're like, well, but you didn't predict all the new car, the, the, the new jobs and drivers and d. And that, that particular thing. And you can predict the negative changes and you can't predict the positive ones. So now the, the rub in this is there's a couple of places where AI creates kind of multi industry very fast, much cheaper things. Like say for example, if you said, well, you know, like for example, one of the areas where I think you'll see a lot of automation is where human beings are following a script. The AI will follow a script much Better. So I think, I think like customer service jobs go completely away, but by the way, I think like sales jobs transfer a whole bunch too. And what does the new sales universe look like? Both of them are, are, are lots of body employers. And so you get, you get a, you get some pretty big transitions in terms of, of how this plays. And that's the thing is I actually think that the, the transition points will be like, more likely than not challenging to navigate. Now part of the reason, like I, I still tend to be a AI, like we just should, should accelerate as much as possible and use it. We can go into that and even though we're going to have this transition difficulties, but the thing we should be doing is saying, well, with AI, how do we help in these transition difficulties? Namely, how do we say, oh, if you're not long, if customer service jobs, they haven't really been decreasing yet. And so therefore a little bit of the, you know, kind of college people not being hired and so forth. It's much easier for companies to say we're doing layoffs because of AI than we mishired in the pandemic. There's global instability, we're not investing in the future at the moment because of global instability, etc. So no, no, we're strong because we're using AI. So there's a lot of discourse on that. But I actually think that, you know, things like the customer service jobs that will be the, as one of the kind of canaries in the coal mine of we have to have customer service and all of a sudden the jobs start going down because of Sierra Parloa or whatever, then I think that the, that you'll begin to see some of that now. I think you'll see it, it's just a question of speed, time, how, etc. And then we get to the transition, transformation transitions. And part of the transition is let's deploy AI for that. Let's deploy AI for, okay, I no longer have a customer service job. How do I, what other jobs could it like work with me? What other jobs could I do are being created. What are the things that, you know, like, you could help me learn. What are the things you could help me do? What, what are the jobs you can help me find? And when I think about this from a society point of view, because these kinds of workforce transformations, you know, the industrial age was really painful in terms of its trans. The like, we don't have any of the wonderful things we have without the industrial revolution. And I think the same thing is true of the cognitive industrial revolution with AI. But the transition is really being well how do we make the transition better? And I think the simplest thing is deploy AI for it.

Prof. G (Host) (28:26)

We'll be right back after the break and if you're enjoying the show so far, tune in on Sunday for our Founder series. We will be speaking with the co founder of the hot new legal AI startup Harvey.

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Reid Hoffman (30:26)

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Prof. G (Host) (30:46)

We're back with profg markets. I agree and Scott knows this, that eventually new opportunities will come as a result of AI transforming our economy. But the question is what happens in the interim? And the industrial Revolution I think is a great point. We're in a comfortable position now looking back 100 years ago saying oh it worked out. Look how wonderful the world is today. But I'm sure there are thousands, potentially millions of people who lived through that revolution, who did lose their jobs, who were not very happy about the situation. And we've talked to people who have talked about that too. Daron Acemoglu is someone who says, actually we didn't do a very good job of handling that transition. And it seems that this is going to be a similar thing, except even faster, because instead of putting vehicles on the ground or building factory equipment, you're literally just shipping software to companies. And we're already seeing it where employees are being laid off like thousands at a time in one go. I mean, this is what happened with Block, this is what happened with Amazon. They just literally send an email, they say, you're all fired. Sorry. Like, that's a new kind of system. And from a just purely like capitalist perspective here, one, I mean, from a human perspective, that's gotta be kind of shitty for a lot of people. And we're already seeing that. But also from a capitalist perspective, it seems as though one of the biggest obstacles for the AI buildout, if you are an AI optimist, technologist, one of the biggest obstacles is how unpopular it is now, largely because of this work being replaced dynamic, where AI is now less popular in the US than ice. So that seems to be a big issue and we're now seeing it in the political sphere. And so I guess my question is, like, how much of a problem is that? Is the popularity problem for AI a genuine concern among the technologists who you are close with in Silicon Valley who are actually building this technology?

Reid Hoffman (32:48)

You know, you'd have to be pretty blind not to be concerned about the popularity problem. And, you know, it's manifest and such, you know, things also is, you know, weird. Like we should have, we should ban data centers. And you're like, okay, you want the data centers built in Canada or somewhere else, you know, as opposed to here, you know, and, and most of the arguments against data centers are pretty spurious. I think the, the key question around the local economy is, say, hey, make it a good enough trade for us to bring it here, like bring in some economic prosperity. Sure. The construction jobs and the running jobs aren't a lot of jobs. Maybe there's some other things you can bring in. Like, you know, maybe you could bring in a plus 10% of your energy of your usage. You add 10%. That helps us in a structural way. I mean, there's all kinds of different ways you can do that. Now, that being said, you know, for example, you know, The UK didn't invent the Industrial revolution, but embraced it strongly and had, you know, centuries of global prosperity from it. And so I do think the transition is challenging, but I think the embrace is valuable. And, and I think that the, the question around, you know, what should we do? Is like, it's important from a economic. It's like, it is the driving force of what the future economies are, and it'll only work for future generations if we embrace the right economic things. But I think the key thing is to try to figure out what's the way we navigate better. Like, I think it's like, you know, anyone who says, oh, we navigated the Industrial revolution perfectly is out of their mind or a historical or anything else. It's like, look, what's the learnings? What are the things we can do now? The most often thing, the people who are not building within the, you know, kind of just call it competitive business world or competitive technology world, say, we'll just slow everything down, right? And you're like, okay, the problem is competition doesn't slow down. That's actually not, not the way that that kind of competition works. Like, if you just said, hey, everyone, wait for me to get my economy in order and then you can start shipping your export things, I mean, you know, take a look what, what's going to be happening within Europe with the spread of BYD cars from Hungary, for example. It's like, oh, no, no, wait for a decade for us to get our auto industry in place. That's not going to happen in terms of how this operates. So you have to be figuring it out how to make the adjustments and transformation at the speed that here we are in a markets podcast that the markets are bringing about, and that's the thing to do. So the idea is they give good ideas on the transformation that we can embrace to help make the transformation better. And that's part of the reason why, like I gesture at the speed and depth of AI also gives us tools to help with the transformation.

Prof. G (Host) (35:40)

How much genuine thought is being given to those kinds of ideas? Like, I think the trouble that a lot of people have is, on the one hand, there's the possibility that AI could be good for society and it could be a great thing and bring prosperity to many people potentially. But also, on the other hand, it could also make a small handful of individuals incredibly, incredibly wealthy. It could make wealth inequality even worse. It could concentrate power and wealth into the hands of a small few, which makes it, I think it makes people feel fairly and justifiably suspicious. And, you know, Dario Amadei could go on a, a show and say, AI is going to be, you know, wreck everything. And people would might say that that's not a lie, but exaggeration. He could also say, AI is going to be a great thing for everyone, everything's going to be fine. Everyone would say that's an exaggeration, that's a lie. He's just trying to get rich. So I guess the question is, like, when, when you interact with these people as someone who's kind of like in the eye of the storm, to what extent are people actually concerned and working on solutions to make this work for everyone versus just trying to kind of like, keep the message intact as they pursue the ultimate goal of wealth?

Reid Hoffman (37:08)

I don't think that's wrong to produce a goal of wealth. I think every networked system, cities, trade, everything else creates, you know, economic inequality and a. And economic inequality is part of the engine by which we, you know, fuel capitalism and competition and all the rest. So it's like, you know, just to be clear, I think that's a fine thing. I do think the question is, is how do you bring, you know, kind of the bulk of society along, eg, how do you have benefit that spreads, you know, throughout all society? And I'd say, like, for example, is one instance, you know, Sam Altman's gotten a bunch of bad press over the last, you know, X months, and yet in the very early days, he was funding, you know, universal basic income experiments, trying to figure out what kinds of things would work there and, you know, spending money directly himself in order to do that. So I'd say that there are people who actually, in fact, pay attention to the issue, care about the issue. It's one of the things I don't think Sam gets enough credit for is just one instance. Now, that being said, the question is to say, all right, are we putting in time and energy in order to help society? I think that a number of the different players, definitely Microsoft, Google, Anthropic, OpenAI and some others, are interested and willing to do that. They're not willing to do it if it's fruitless relative to its engagement and everything else, given that they also have an intense competition clock going. So if you wanted to say, like, one of the things that I've been telling, you know, governments for years is like, the kind of thing you should be asking for is I'd like to have a medical assistant that runs on every smartphone that can help people. I'd like to have a Legal assistant that runs on every smartphone that can help people. I'd like to have a tutor that runs on every smartphone and essentially make those the equivalent of free as part of the benefit for helping in transition. Like, I think you could do that and I think you could very easily cut the deals in which they would build it. And so where then the government could make sure it's there for everybody and to be getting some benefits in, you know, as we sort out the kind of melee of what's going. But like say, for example, they just say, okay, we'll go build the tutor that helps with like all things economic and jobs. Well, okay, we build it. Are we only going to use it? How's it going to get there? Do we have to spend energy and time on that too? So given that there's this focused competition about where the primary economics are and the establishment of platform and so forth, so this is kind of an area where I think they are legitimately concerned. Part of the reason why they in their own minds will, will say, you know, pretty, this is, you know, Scott was gesturing at, you know, kind of like the, oh, are you just fundraising by saying white color bloodbath in next year's, you know, you know, buy my Series D. And it's, I don't think that's a great way to try to sell the Series D. I think it's actually like, hey, shit's coming. Somebody should be helping do something here. And we're happy to help. We got our, that we're working on, but we're happy to put some energy into it. And I think that's what we need to be doing, you know, now unfortunately at the moment saying, well run government seems to be, you know, something on, kind of on the order of dinosaurs or dodo birds or anything else. And, and it's, it's difficult to figure out what to do. You know, I'm always happy whenever a, you know, any government of any western democracy style democracy calls me and says, hey, I'm trying to figure this out. What can I do to help? Like, I'm like, okay, here's some ideas. Here's things like, you know, the medical assistance one that I've been talking about since 2018, right? Because you want to say, hey, this AI transformation is challenging. Most people do not have immediate access to medical advice, right? The vast majority of the world does not have that. And so it's like, oh, could I get some? That's good. And that would be easy for governments to set up because it's changing the legal liability and then the, the mandate for how it's reached and then having a deal with whatever number of companies you want in order to, to go into that in terms of what you do. And then all of a sudden you're providing something.

Prof. G (Host) (41:30)

Part of me wonders if, I mean, you mentioned how like Sam Altman has been working on and talking about universal basic income ideas for a long time. And in fact OpenAI recently just published a proposal, they called it like this New Deal style proposal where they gave a bunch of ideas on how we might lessen the potentially harmful impacts of AI on our economy on things like wealth inequality. They suggested higher capital gains taxes. They suggested something akin to a UBI like, to their credit, they are thinking about this and proposing solutions and putting it out there. Part of me wonders, however, that this issue of comms and AIs PR is almost an impossible problem because of the reality, the fundamental reality of wealth inequality on the ground today. Where, and this is something Scott and I have talked about, where we look at the wealth inequality Gini coefficient, for example, which is 0.83 in the US right now. And during the French Revolution it was the same number. Things like that, where Americans hear this and they get very upset about it. And so anything that suggests that this could worsen that trend, AI being one of them, and it could like there's nothing, there's no amount of communications, there's no amount of PR or IR that you can do to make them feel better about that. That's what I've started to wonder about this AI revolution. And I wonder if, if you have any thoughts on that and if you agree or disagree, I tend to

Reid Hoffman (43:14)

not focus as much on the inequality question as much on, like if you say the kind of, the bulk of 80% of society, is their circumstances improving in some substantive way. And I tend to think that if they think, hey, I've got some reasonable opportunity playing the game, my circumstances can improve, they might be improving. Then I think you get more social stability. And I think it's when I, like, I don't know how to feed my children. I think, you know, my prospects over the next decade are just categorically worse, you know, et cetera, et cetera. I think when you hit it and it's not, you know, like the usual kind of thing that I tend to say is inequality tends to be more of a political topic because it's like, well, the CEO should only be paid 20 times as much as the bottom person. You're like, well, how do you get to that magic number, why isn't it two, why isn't it 5,000? You know, like you let markets sort those things out. And by the way, inequality comes with the economic system that we have built. Prosperity and capitalism and in competition and you know, cities generate higher wealth because of network density, trade generates higher wealth, you know, kind of the these kind of things. And it always has some disparate curve. It's not like it's evenly spread out like peanut butter across the whole system. Now that being said, it is absolutely mandatory for healthy societies to be saying, hey, I as a middle class family am like viewing myself as having better prospects as I'm going into it. I might have a rough year or two, I might have some way that I have to work hard or anything else, but like that kind of thing is an option. And I think that that needs a strong solution. And I think that part of the thing is right now I think people are like, look, times are hard. It's part of the reason why, you know, I think democracies around the world are tend to be 10, not 100, but tend to be, you know, kind of saying, hey, we want to elect someone who's going to take a wrecking ball to everything because we think maybe that's the only way that things could get better. That's almost always leads to things being worse. You know, cultural revolution, you know, French terror, et cetera, et cetera. Renovation is the important thing. But I get the frustration, the anger, the uncertainty that gets there. And I think it's beholden on all of us to try to say, hey, let's try to renovate these institutions together and let's try to make it work for the bulk of 80% and whatever it takes to get there. Because for example, if you said the simple problems, inequality is like, well then let's just simply institute a, you know, kind of like a 90 upper bound tax on stuff. And that should just simply solve everything. And I don't think that would actually in fact solve everything. I think, you know, like, I think someone did an estimate that if you took one of the super billionaires, you know, Elon or Bezos or whoever, and like simply redistributed their economics across the entire US country, it makes a difference. Everyone sent like, you know, small savings account gets a little bit bigger, but it doesn't fundamentally change anything there. So you want to be changing the actually economic system of what's happening.

Scott Galloway (46:26)

I would push back a little bit. Reid. I find that just because taxing billionaires are super Wealthy people wouldn't solve the problem. It does feel like once you get to kind of the 0.1%, your tax rate plummets. And just from an equity standpoint and being responsible, we do need to restore a progressive tax structure, including it should go up for the wealthiest, not down. And yeah, the defense that it's not going to solve our problem, I don't think is a, is a, a solid defense.

Reid Hoffman (46:56)

Oh, just to be clear, I'm for progressive taxation. This is an inequality point as being that like that's the problem of society and what we need to solve.

Scott Galloway (47:04)

You think there should be a floor.

Reid Hoffman (47:05)

How do we raise as much of the kind of call it 80 plus percent of people as we can and whatever that took in progressive taxation. That's awesome. From my point of view, I just, that progressive taxation itself I don't think is sufficient to the solution. Right. Like it's, it's. By the way, I completely agree the, the differential, like there's a reason why I think in, in most of the places where we've had strong growth in societies, we've had progressive taxation. The fact that the wealthy can hack it in ways that they're paying less tax than a middle class person as a percentage is essentially a misfunction of society. And that, that should be fixed. Right. But that's fixed for a different reason other than pure inequality questions.

Prof. G (Host) (47:50)

What would be that fix? Because right now a lot of people are just like, well, wealth tax, I mean it might be a crude and unnuanced perspective, but that's what is being proposed in California. Because they're like, well, we haven't seen anything else. Like what is the alternative in your view?

Reid Hoffman (48:08)

Well, so take the California one which is they go, okay, we have a budget shortfall because of, you know, things that Trump's, you know, quote unquote, big beautiful bill did. So we're going to pose a one off wealth tax for a particular, you know, kind of benefit of segment of California. I think all the optics in this are wrong. It's not fixing the systematic thing. It kind of you, you start with California, which other than Manhattan has the highest income tax rate in the country. From, from a way of doing this and no real, you know, understanding of this and no sense of what we're really trying to do is fix the overall system now. Like for example, I was supportive of the increase of, of, of the state income tax provision and the fact that you say, hey, we now charge this income tax now at, we added a new level at, you know, Higher levels like a million dollars of income and so forth. I think those are good things to do do. There's a. And by the way, some people against wealth taxes go, well wealth taxes. We never do wealth taxes. They're terrible. They're unproven. You're like, well actually property taxes are former wealth taxes. There's, there's ways to do it now there's a bunch of questions around what happens with private, you know, stock and so forth. I mean there's a bunch of unknowns and challenges and you want to compound in the growth. I'd say that the, you know, the reason why the wealth tax comes out in California is because it's more politically expedient. The easiest one is repeal Prop 13. But that's a third rail which is a, which is a fixed on property taxes, which is a wealth tax. But that's a third rail in California because the commercial real estate associations which benefit massively economic various slaughter any candidate who does that. So it's like, oh, let's go after billionaires versus versus, you know, real estate across the entire country.

Scott Galloway (49:58)

I'd love to get your take on the case that kicked off yesterday and that is Elon Musk's actions against or action against OpenAI.

Reid Hoffman (50:06)

I was around and basically Elon, I think is doing everything possible to throw anything he could possibly invent at OpenAI. And you know, among them was, you know, kind of claiming that they misled him. Like he wanted to identify himself as a co founder of creating it. But then it's oh, you misled me into, into a philanthropic donation with later plan to turn this into commercial. And having been around it, I know it's factually incorrect. We'll see what happens. It seems that it's like it's the kind of the definition of legal harassment and kind of trying anything possible to kind of say, no, I didn't make a huge mistake when I basically told OpenAI that it should become a company that I own. I, elon, should own 80% north of. And if you're not going to do it, I'm leaving. And oh look, the company, the organization did well. So I'm, I'm very, I'm hoping the truth and justice will prevail, which is basically it'll be a speedy trial which all of this stuff will get kicked out and maybe even an open AI countersuit for massive defamation and false suits might even work. But we'll, but we'll see.

Scott Galloway (51:21)

What do you think of the idea of creating sort of this Space Media AI conglomerate. And I mean they're talking about the SpaceX IPO. You're a markets guy, you're an investor at 95 times revenue. And Ed pulled some data. When Google went public it was growing 240% a year and trading at 10 times revenues. SpaceX is growing 20% or 24% a year and going out at 100 times revenues. And I'll say this about all the kind of upcoming IPOs. Doesn't it feel like the valuations have gotten way out over their skis here?

Reid Hoffman (52:01)

I certainly wouldn't buy in the SpaceX IPO. I think most of the people who are buying there are kind of in the. Hey, everyone thought Tesla was crazy for a long time and I made a bunch of money on Tesla and they did,

Prof. G (Host) (52:19)

I agree, but they did.

Reid Hoffman (52:21)

Yes, exactly. And so what the hell, give it a shot. As I think roughly what the investment thesis is there, which it's kind of like that strikes me as like a bitcoin charter. It's like well it went up so I should buy because it continue, it will go up again. Which is again not smart investing behavior. I also a friend of mine kind of said hey, I think what he thinks is going to happen is, is that the, and he's heard from other people, he thinks that SpaceX will go out and then they're going to merge it with Tesla because you know, Elon's comp package is apparently on market cap. So you know, gets a whole bunch of money if the, if it goes out and they merge. Oh, you know, I haven't cross checked this but you know, it strikes me as a possible, you know, set of considerations. But anyway, so I think it's, it's IPO should be made on a prospect of real growth. And so if you're not having that, I think, you know, the market should be more sane. Whether or not they will be sane is a different question.

Prof. G (Host) (53:33)

We'll be right back. And if you're enjoying the show, come join us on tour and hang out with us live. You can get your tickets@profgmarketstore.com the link is in the description. Zootopia 2 has come home to Disney Plus.

Reid Hoffman (53:54)

Let's go get ready for a new case.

Prof. G (Host) (53:56)

We're going to crack this case and

Reid Hoffman (53:57)

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Prof. G (Host) (54:04)

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Reid Hoffman (54:06)

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Prof. G (Host) (54:32)

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Reid Hoffman (54:33)

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Prof. G (Host) (55:28)

We're back with Prof. G Markets. We were talking earlier about that there is a lot of competition in AI, at least for the moment, and that might be a good thing, bringing prices down. One thing that I would also add is that it's also being subsidized right now by essentially the VC community, which is helping with prices. I feel like eventually prices are going to go up either way. One thing that we have been a little cautious of in the AI ecosystem is what we have described as corporate incest, which is where there is a lot of sharing of revenue that we're seeing. We saw this between Nvidia and OpenAI and then also we saw this trend of these kind of like pseudo acquihires or pseudo investments that turned out to be acquisitions. And one of the most prominent ones was a company that you founded, which is Inflection. And something that really struck me, I mean I remember reading the headline like Microsoft is Partnering with Inflection. And Inflection was this company that everyone was talking about. It was one of the hot AI startups. Microsoft is partnering with Inflection. They're going to pay them several hundred million dollars to partner with them. And then suddenly we also learned that half of the employee base has moved over to Microsoft. And then we also learned that the co founder who you started the company with, Mustafa Suleyman, also moves over to Microsoft and is now the CEO of Microsoft AI. At which point I started to think, well, this wasn't a partnership, this was an acquisition. And then we started to see it with other companies too. Meta goes and grabs Alexander Wang who started Scale AI, another big AI startup. We saw it with Google and character AI they kind of create this deal and then suddenly all the employees end up working for Google. It made me think that big tech is sort of taking over the AI ecosystem. You are sort of at the heart of this. What happened there with inflection and what do you make of that concept?

Reid Hoffman (57:24)

In my head whether it's an acquisition or not by actual point of view is does the business continue? Inflection continues. It has 70 employees, it has been doing a B2B business and so forth and pivoted. So I think the question is is the business continuing relative to the is it really an acquisition or not? Like so it's a partnership is a very generic world and it's a huge deal which a bunch of employees and a non exclusive ip right. And you know co founder went and that's happened in even more cases than you've mentioned. I think inflection we, we set the, the stage on and I think that the question is is I think part of what you've seen in the large tech companies is they would prefer to be buying companies versus doing these kind of, you know, kind of strange deals but feels that the regulatory environment is too hostile to, for them to do that especially earlier and so are looking for other ways to make it work. And so you say well what's a deal that you could make work that isn't an acquisition? It's like well you know get like a like kind of something that's not quite a BD deal but not quite a corp dev deal. Like it's kind of like halfway in between and the measurement is does the business continue, you know, with, with vigor and effectiveness afterwards. And I think that the you know, I think regulators, you know from having seen a bunch of commerce questions about this, you know, aren't fond of it because they're, they're like well we want to be, we're trying to regulate the corp dev side of things. I think part of the challenge is is I think that the theory just speaking of the U.S. although I, I know that the, the UK competitions market can be a little nutty, you know like view like we should not allow something if there's going to be future competition which is like kind of strange. I think that the question around acquisition should be not like are we increasing the amount of capability of competition? Like so let's take for example one of the big companies that has no play in AI right now, which is Apple. Like you shouldn't go get in the way of Apple buying an AI company, because that will actually increase their competitiveness with the other hyperscalers in terms of what they're doing. Even if it makes a big company bigger, you want to be increasing the competitive landscape of this and looking at where they currently are. And I think that's what you'd want to do on the corp dev side. Now this kind of thing I think is a deal innovation that's like BD plus in order to kind of navigate the universe and inflection got a bunch of capital and could pivot its business from doing frontier models to B2B and a bunch of other things in order to execute on this.

Prof. G (Host) (60:31)

I mean, it sounds like you acknowledge it is a way of getting around regulation essentially. And I guess people can do what they will with that fact, whether it's a good thing or a bad thing, whether it's innovation or kind of skirting around the law.

Reid Hoffman (60:52)

Well, I don't think it's skirting around the law because I think what happens is corp, the corp dev law doesn't cover it, right? So it's like, here's a way to make a deal transaction of a certain sort, a new center sort work, right? Because this doesn't cover it. So like skirting implies like, well, I'm going 80 miles an hour versus the 60 miles an hour. That's, that's, that's, that's posted on the highway. It's like, well, I'm going down a different road, right?

Prof. G (Host) (61:17)

It's almost like tax avoidance versus tax evasion. Like it's technically legal, but it's like in essence accomplishing kind of like the same thing. It's still following the law, but effectively like it is an acquisition in a lot of ways. So I guess the question would be like, is that of concern? Should startup founders. I mean, just as an observer, I looked at inflection, I looked at Mustafa Suleiman. I'm kind of thinking, you know, and you, and you co founded this company and I'm thinking this company could be the next Google, this company could be the next Microsoft. And that didn't happen because there was this moment where big tech had so much cash essentially that it could just kind of be like, hey, like, let's just partner, we'll, we'll pay you hundreds of millions of dollars and then that'll be the end of it.

Reid Hoffman (62:13)

Well, actually, I think you've got it exactly reversed.

Prof. G (Host) (62:15)

Okay?

Reid Hoffman (62:16)

No, I think you've got it exactly reversed because the question is, I think these deals are generally Terrible for investors. They're not like. What you really want to be able to do is command a really high price and say the only way you get anything here is that you buy the whole company. And if that's not available and you believe that your prospects on your current path aren't working, you will accept a suboptimal deal. So I think these deals are, are broadly much less good for investors.

Prof. G (Host) (62:46)

Fair enough, right.

Reid Hoffman (62:48)

And so investors don't want them. And by the way, then there's also the function of, you know, are they. Usually in these deals, it's on smaller numbers deals are better for investors. On larger numbers investors, employees are the same. But that also means that it's then suboptimal for employees as well. By the way, the reason why people will do this is because they go, oh, I see that the path we're on currently with this business is not going to work. So, for example, in the inflection cases, we're not going to be able to establish our agent with building frontier models in the way that we hoped. We need to pivot. So we're going to pivot to P2B. How do we get the capital? How do we make that happen? Will we do a deal where that enables that to happen? But that's a pivot deal, not a. Like it wasn't. Microsoft came along and kind of said, hey, a little bit of cash, you know, you completely upend your business was like, no, no, we've actually already decided that we need to change. And we're trying to figure out how to fund that change and make that change go through.

Prof. G (Host) (63:52)

But then the question becomes, why is inflection in a position where they feel that they can't compete in this space like inflection? From my understanding, you had some of the greatest minds assembled in all of technology, yourself included, to make this thing a success. And the fact that you guys decided that the better option would be to sort of slightly fold and pivot into Microsoft tells me that the landscape was too dominated by big tech, which is something that people have been concerned about, about this generation of technology versus say like the dot com boom.

Reid Hoffman (64:26)

So we figured that on a chatbot side, which thing we were focused on that going into scale building frontier models would be too expensive. And a year or two down the road, we'd be like in this really, really difficult position, because when you strategy, you're trying to, you try to pivot before you've, you've driven the bus off the cliff. Try to not. You try to go down A different road before. You're like off the cliff now. If we had had the idea which anthropic got into, which is let's go totally coding and APIs and just done that, maybe we would have been anthropic, right? We didn't have that idea. So we had a bunch of talent. But it's always about the engagement with the market, what you're showing to investors, even in crazy times, et cetera. And we looked at the thing we had and said we need to pivot to B2B. If instead we said hey, we could do coding, maybe things would have been different. But we didn't, you know, more fool us, we didn't have that idea. And you know, hooray for anthropics, you know, iteration.

Prof. G (Host) (65:24)

Do you believe that the monopolization or market power of big tech isn't a problem? Do you think that it isn't stifling innovation or having a negative impact on startups?

Reid Hoffman (65:39)

Well, the short answer is no for a couple reasons. One is it's a question of do you have growing number of competition? So like for example, if we were five hyperscalers heading to three, right? Then I'd say we have a problem. But I think we're five to seven hyperscalers heading to 10 to 15. You know, OpenAI anthropic, you know, Nvidia being some of the new ones with all competing with each other and in as a startup founder and as an investor, that surface gives me a lot of opportunity to maneuver. And by the way, the reason why you don't want to block out Corp dev is you say I want to create a company to complete with Hyperscaler X. Well, what happens when the company is not doing that? Well, I cannot raise substantial amounts of capital if I don't have an acquisition opportunity to get out. Right. And so if you say well we're going to block all acquisition opportunities for that, then I will never create the capital. And then by the way, me as a series AVC means that I'm not going to invest in a company that's trying to create a new kind of search experience because I can't get an acquisition out as one possibility if the IPO doesn't work. And by the way, my incentive is to create, you know, in modern parlance a trillion dollar company. That's what I want and I want to go long for that. So that's the reason why the, the regulatory structure is somewhat fubar in terms of the way it's currently conceptualized. And right now you can say, well you get pure capital determination about what the markets are and every VC is trying to spend as much money on AI companies as they possibly can in investing.

Scott Galloway (67:15)

What do you think of some of these tech companies going vertical and acquiring media companies?

Reid Hoffman (67:22)

Complicated question actually. And actually I'd be very curious to hear your answer to this too. Roughly speaking, I think the people have not quite generated the right like interesting generalizations from like Netflix originals and prime and Apple movies and so forth, like all these things which I actually think that part of what you should be doing in the modern age of the Internet is everyone has an ability to have a certain amount of expressiveness to the world at large, society, customers, industry. And so everyone should be running kind of like almost like some version of content marketing. And I don't mean that as pure like buy my product, but I mean it's kind of like this is who we are in the world. This is the kind of thing we're doing now. Some of it could be more pure like hey, we're just going to have a cool set of TV series, you know, whether or not we're, you know, Netflix, you know, Amazon or Apple. But it also could be other things and I actually think that's a good way for, for the companies to process. Now that's separate from we desperately need kind of objective civic news for democracy. And how do we solve that problem which has been crushed from multiple sides. And obviously I don't think the commercial is the tech companies. Other people buying these things isn't helpful, but I don't think it's the source of the harm.

Scott Galloway (68:51)

By the way, I'm a huge fan of big tech, vastly overpaying for independent podcast networks. I think it's a great

Prof. G (Host) (69:00)

one for us at Microsoft.

Scott Galloway (69:01)

Yeah, I think it's a great idea. Well, I mean it's funny. I mean there's definitely a tension, right? There's a tension between deep pocketed companies using what feels like or cosplaying independent journalism to do anything but independent journalism. That's the fear. And they crowd out true independent journalism which doesn't have the backing of deep pockets. But at the same time going vertical and having content or thought leadership. That's how I built my last company, analytics company. I started putting out media on YouTube so they should absolutely be allowed to do it. I'm a big fan. If you were asked by the administration, let's be real, you won't be asked by this administration. If you were asked by the next administration to help, loosely speaking, with a crude AI framework for regulation. As far as I can tell, the only regulation that's come down so far is meant to stop regulation at the state level. If you wanted some sort of safe and sane guardrails for AI right out of the gates, what are the two or three things you'd want to see happen?

Reid Hoffman (70:09)

Well, by the way, I thought what the Biden administration started doing was pretty smart, which is bring all the tech companies in, push them very hard on a set of things, get them to make some voluntary commitments, then to up it and kind of start enshrining it. And it's kind of like having red teaming on safety plans and so forth. I think the first and most important issue is what happens in like bioterrorism, what happens in cybersecurity, et cetera, how does that get provisioned? So, and I think there because you want to start, stop anything that could have a systematic damaging of the entire system and you want to make sure that's, that's kind of, you know, kind of well guard railed and that that would be one set of things you would do. I think another one you would do is say I want to generate like whatever your list of concerns are, like say if your concern is job replacement or your concern is, you know, I don't think the environmental impacts are actually, I think they're all more politicking than anything else. But it will say you had those then it's like I want to have you generate these kinds of reports could be for, you know, in a, you know, only for, you know, government consumption, but validated by your auditors, whatever the particular set of concerns are. And I want to, I want to have a trigger that if you, if some of these numbers are getting worse, you know, in a time frame that is quick. I want to have a trigger by which your auditors tell us quickly whether, so we can say what is something really happening and you know, jobs or something really happening and you know, et cetera, you know, misinformation on networks and we could get some sense of it so that we can start intervening on it. And then, you know, as part of that we also want to get previews about what's actually happening in the engagements with your products so we know how to steer and I think think that's a really good place to start versus all of the political melee, which is more about what I care about versus what I perceive the world to be versus actual data and information.

Prof. G (Host) (72:20)

Reid Hoffman is the co founder of LinkedIn inflection AI and Manus AI he's also a partner at Greylock and sits on the board of many companies, including Microsoft. He authored six bestsellers, including his latest, Super Agency. What Could Possibly Go Right With Our AI Future? Reid also co hosts two podcasts, Possible and Masters of Scale. And for more, you can check out his new substack, Theory of the Game. Reid, thank you for your time.

Reid Hoffman (72:46)

Pleasure.

Scott Galloway (72:56)

Ed, what do you think?

Prof. G (Host) (72:57)

I agree with him on something that I disagree with him on other things. I think what he kind of honestly acknowledged is that Big Tech is really dominating the AI landscape. And I don't think he convinced me otherwise, to be honest. So I think that's one thing I disagree with him on. I also kind of disagree with him on his views on the wealth inequality problem. Like, it sounds like he is pretty aggressively against a wealth tax, and that's fine, by the way. I don't think it would work either, but I think that there could have been more. I think there should be more attention paid to, okay, what is the alternative? It is getting to that point where we need to be very seriously advocating for different redistribution methods if you are going to also say that the one that other people have proposed is not the right path forward. So I guess that's where I would be in sort of disagreement with him on. He's also an incredible entrepreneur, incredible power player in the tech community. I mean, you can't deny his accomplishments. So I appreciate him for sharing his thoughts on all of these subjects with us.

Scott Galloway (74:09)

If you talk to anybody with the fingers and the pies he has, they're like, oh, no, regulation. Income inequality isn't a problem. Let our horses run. What if China gets out ahead of us? You know, it's constant excuse, excuse. There shouldn't be any regulation of AI. There's no problem here. Move along. Nothing to see. Reid is going to be as focused on preventing a tragedy of the commons as anyone in his position. You know, it's just, he can. And it's hard for him. He's on the board of Microsoft. He has to be very measured about what he says about OpenAI. He has to be very measured about what he says about Elon Musk. And he sort of calls it as he sees it. He says, look, this is. Calls it as what it was that Elon's having the biggest case of seller's regret in the history of business.

Prof. G (Host) (74:58)

Yeah, a lot of people just wouldn't give their opinion or give an answer to many of the questions that we asked him just then. And he did find me a VC

Scott Galloway (75:06)

or someone hugely invested in AI that has anything resembling the kind of moderate reason views of Reid. There just aren't very many of them.

Prof. G (Host) (75:17)

This episode was produced by Claire Miller and Alison Weiss and engineered by Benjamin Spencer. Our video editor is Jorge Carty, our research team is Dan Shalon, Isabella Kinsel, Kristen O' Donoghue and Mia Silverio. Jake McPherson is our social producer, Drew Burrows is our Technical Director and Catherine Dillon is our Executive Producer. Thank you for listening to Prof. G Markets from Profgy Media. If you liked what you heard, give us a follow and join us from for a fresh take on markets on Monday.

Mitch (Guest or Ad Voice) (75:57)

And kind

Scott Galloway (75:59)

reunion.

Prof. G (Host) (76:05)

Sam.