Reid Hoffman on OpenAI’s $7 trillion plan, Apple’s Vision Pro, and AI traps

27 Feb 2024 · 25 min

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Masters of Scale Podcast Episode Summary

Episode Title

Reid Hoffman on OpenAI’s $7 Trillion Plan, Apple’s Vision Pro, and AI Traps

Episode Overview In this episode, host Bob Safian engages with Reid Hoffman, co-founder of LinkedIn and a prominent venture capitalist, to discuss significant trends and events in the tech industry. Key topics include OpenAI's new text-to-video tool Sora, a $7 trillion fundraising plan by Sam Altman, the competitive dynamics of Meta and Apple, tech layoffs, and the implications of artificial intelligence on business operations.

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Key Points and Discussions

  1. OpenAI and the Future of AI
  2. Sora Tool: OpenAI recently launched Sora, a text-to-video generation tool, which Reid believes has the potential to revolutionize content creation.
  3. Fundraising Goals: Sam Altman's ambitious goal of raising $7 trillion for the chip industry is seen as a strategic move to achieve advancements in artificial general intelligence (AGI).
  4. Scale Over Algorithms: Reid emphasizes that the true advantage lies in scale computing rather than just algorithm improvements, suggesting that larger investments in AI computing power lead to more significant advancements.
  1. Tech Industry Dynamics
  2. Meta’s Resurgence: Discussion on Meta's recovery and stock price increase, partly attributed to a shift in focus towards AI and efficiencies achieved through restructuring.
  3. Apple Vision Pro: Reid expresses skepticism about whether Apple’s Vision Pro will become a widespread platform due to high costs and previous technology failures in this space.
  1. Tech Layoffs
  2. Reasons for Layoffs: Three primary theories discussed:
  3. Overhiring during the pandemic.
  4. Copycat layoffs driven by market trends.
  5. Increased efficiency due to AI reducing the need for a large workforce.
  6. Strategic Reshaping: Reid notes that layoffs may also allow companies to realign their focus and adjust to the anticipated productivity gains from AI without facing negative scrutiny.
  1. The Role of Startups and Large Companies
  2. Competition Dynamics: There is a recognition that both large companies and startups will benefit from AI advancements, challenging the notion that only one can thrive.
  3. Market Value Concentration: The concentration of wealth among top tech companies (Microsoft, NVIDIA, Apple, Amazon) raises questions about market health; however, Reid argues that competition among these firms can foster innovation and consumer benefits.
  1. Navigating Change and Opportunity
  2. Embracing Experimentation: Reid stresses the importance of not waiting for the perfect moment to engage with new technologies or challenges. Companies should actively experiment and adapt to the fast-changing landscape of AI and tech.
  3. Adapting to Technological Transformation: As AI integrates into various sectors, companies must rethink their strategies across all operations, beyond just IT.

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Key Takeaways

  • AI is a Compounding Force: AI acts as a catalyst that combines and enhances existing technologies, leading to significant transformations across industries.
  • Scale Matters: In AI development, having the necessary scale in computing resources is crucial for achieving breakthrough innovations.
  • Be Proactive, Not Reactive: Companies should avoid complacency in the face of uncertainty; active experimentation with new technologies is essential for sustaining growth and competitiveness.

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Closing Remarks Reid Hoffman provides a compelling perspective on the intersection of AI with business strategy, emphasizing that the future is not just about evolving technologies but also about how companies choose to engage with and adapt to these changes. His insights encourage leaders to proactively embrace innovation rather than waiting for clarity.

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Transcript

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1:22Hey, everyone. Bob Safian here. Every few months, I connect with Reid Hoffman to get his perspective on the key inflection points in the business world. Our most recent conversation, which we're sharing today, starts with OpenAI's new text-to-video tool, Sora, and why OpenAI CEO Sam Altman is trying to raise$7 trillion. That's trillion with a T. We also talk about Meta's dramatic resurgence, the Apple Vision Pro, three things driving tech layoffs, the AI trap that many businesses are falling into, and more. As always, Reid's insights both anchor me and get my wheels turning. I hope they do the same for you.

2:06Let's get to it.

2:28All right, we ready for this? Always with you, Bob. This past week, the new text-to-video tool that OpenAI released, Sora, which I don't know if you've played with at all yet. I played with it a little bit, and it does some amazing stuff. What people have been working on pretty intensely for the last year or two is these multimodal generative models. And it doesn't surprise me that OpenAI is the first to release the amazing new jump in capability. They just keep seeming to be ahead of everyone else, even though so many entities are racing to try to leapfrog them. Well, I think one of the key things that OpenAI has stayed true to, that relatively few of the other players are internalized to the degree to which OpenAI does it, which is a scale compute.

3:22So frequently, of course, people want to talk about the narrative of what's going on in AI as we've invented the new algorithm. And there are new discoveries and new algorithms, but really what we are is applying the scale compute lesson. We've got these news stories about Sam Altman going around for the trillion-dollar chip fund and all the rest because he and the organization has embraced the we are playing to scale. And by having played to scale, and there's a lot of kind of interesting academic results and other things that say, hey, scale is kind of trumping all. Yes, this algorithm is a little better.

4:01Yes, this algorithm is a little worse. Yes, this data set is a little better. Yes, this data set is a little worse. but it's the scale that is primarily driving it. It's what drove it in the large language models, hence large out of language models, and it's what's driving it in the multimodal as well. Once, though, you have that scale compute, it allows you to create these executions in a way that if you don't have that scale, it's not that you can't, but it's not going to be smooth the same way. It's just going to be that much harder or that much bumpier getting to those places. Yes, exactly.

4:33The SOAR work is amazing. I don't want to take anything away from the fact that it was smart, high-quality people working intensely in a team, but it's also creating these super expensive computers. That's a bold, risk-taking move from both OpenAI and from Microsoft. Now, you mentioned Sam Altman and his, I think it's$7 trillion he's trying to raise for the chip industry, which is a wild number, right? $7 trillion, especially at the same time that he is running this company. Is it about that we really need that number to get to the future of this industry? Or that's a target that pushes us in the right direction?

5:20What I would say is they've probably done some internal calculations about what scale gets them potentially to artificial general intelligence. There's several different definitions of artificial general intelligence. Obviously, the rough thought is something intelligent like we are, capable of having metacognition and strategic planning and one-shot learning and a bunch of other stuff, and that the scale approach of this will get there. So my guess is that's how the number got calculated, just from knowing the people. Now, that being said, part of the thing I think is amazing is whether or not you think AGI is high probability, medium probability, low probability, wherever you are in that spectrum, you will be creating really interesting increases in cognitive capability of these systems.

6:12Say they can't raise$7 trillion or not in one bold swoop or whatever else. You're still going to have amazing progress. So it kind of doesn't matter if it's set out as a, we need this to get to AGI or it's a target number with an aspirational focus. That continued investment to scale is going to be one of the things that's going to net a lot of the steam engine of the mind revolution and this amazing cognitive amplifiers for human work. that will come out of some portion of that, whatever portion of the goal plays out. Sometimes I feel like the story in technology development is like it's software, which feels like it's been more recently.

7:01But now with AI, of course it's software, but it sounds like it's the hardware also. These two things are being married or relying on each other to advance in a way that maybe we haven't had for a little while. Well, I think it's always been a combination of software and hardware. We were operating for decades on so-called Moore's Law, really kind of Moore's hypothesis or principle or something, which by doubling the number of transistors and getting the kind of compute better, we could continue that software progression. And there's some really compelling graphics that kind of show that the progress in this modern wave AI came about from when, as Moore's Law flattened, it just changed its shape of what the hardware loop was.

7:45As opposed to the hardware loop being we're also doing Moore's Law, it's the we're doing massive parallel configurations. By the way, what that means is that tends to go to certain kinds of algorithms. It requires a learning versus a programming. Artifact tends to be probabilistic computing. There's a stack of things that kind of go into how that scale plays. But the hardware-software combination continues. Sometimes sort of the valuations rise for one group and then the other group, right? They sort of seem to sometimes go in sequence, although right now with Microsoft on the one hand on OpenAI and with NVIDIA on the other end, they're both going.

8:30Valuations are actually, in fact, kind of a market prediction about where future value will lie. And you go, OK, the hardware like NVIDIA has got these great business with 80 percent margins. We have this fairly strong hardware edge that so far we have not had anyone catch us. And so people go, OK, there's a lot of value there. We'll bet on that. But on the other hand, people also know there's going to be a ton of value on the software side. Right. And so the short answer is the market saying we're betting on both the software and hardware on the AI side. And so place your bets. And who wins in the long run or who is the bigger winner?

9:11It's kind of hard to tell right now. I mean, right now we see open AI obviously winning, but I'm thinking of the earlier waves of social media, like Facebook was not necessarily considered to be the winner in the beginning, and yet they ended up being the winner. This happens in business and in technology in particular. A hundred percent. And also, it's a little bit reminiscent also of the question is, is this going to be a technological change, things that large companies win from or startups win from? And the answer that I've been given fairly consistently along this whole path is both, right?

9:44It isn't going to be the David and Goliath where David invents his new thing, AI, and it kind of resets the apple carts of the Goliaths that are appropriately bought into AI, which is intensely Microsoft and Google and some Amazon, definitely Facebook. They will be a massive increase for the large companies, but will also be very valuable across a whole set of startups. And so I think it's going to be a realization of the software revolution, that transformation of industries by software across the entire stack of size. And I think that's also true hardware and software. The concentration of wealth right now in the top tech names, Microsoft, NVIDIA, Apple, Amazon, It's like 25 % of the market value from the S &P 500.

10:32I mean, it's not been that way before. Is that troubling? Well, there's definitely places where scale can be not good. That's an odd statement to be making on the Masters of Scale podcast. But it's not what most people think. Most people think, oh, big is bad. Oh, look, it's continuing market dominance of the top tech companies. And you're like, well, actually, in fact, if we were five big U.S. tech companies or seven big U.S. tech companies heading to three, I'd be actually quite concerned. We're actually five to seven heading to 10 to 12. And the competition between these organizations is fierce.

11:12And it creates a lot of opportunities for startup. It creates a lot of services for consumers. It creates a lot of value within the American tech industry, which benefits America. Scale is concerning when it distorts it because it crushes competition. if tech company X were to going to get to scale and then lock out other players to the detriment of society, detriment of industries, detriment of consumers. But that's not an absolute scale number. That's a relative scale number to your competitors and other players. That's the mistake that lots of press and everyone else just mistakes. That's the reason why if it was five to seven going to three, well, if it's five to seven going to 10 to 12, then it's good.

11:56NVIDIA's inclusion in the trillion dollar club is part of the going from five to seven to 10 to 12, right? That's the instance of it. Like I've been saying this for years and it's like, look, here's an example proof. And you're like, well, you didn't say NVIDIA before. It's like, you don't know which ones, but you know that the competitive ground swell is coming. And by the way, One of the benefits that you have when you have this is all of these companies are investing massively in technological R &D. It's not what people frequently are saying, scale is bad. It's saying you have to watch for certain elements of scale, which I don't think we are actually triggering yet.

12:34So this is like qualitatively different than, say, regulators looking at the airline industry and saying JetBlue and Spirit shouldn't get together or the grocery industry and Kroger's and Albertson shouldn't get together. The tech industry is sort of qualitatively different. Well, if you were saying Microsoft and Google should combine into one company, I would definitely agree that would not be a good idea, right? But if you said, should large company X be able to buy small company Y, the answer is, sure, they should be able to. The competition between these organizations is ferocious. And by the way, as a venture capitalist, my primary identity, there's a lot of opportunity on the startup side.

13:14Back in the day, decades ago, when Microsoft was the one big tech company, that was a bigger challenge. It was good to limit it. But I think everyone was surprised by how quickly through the browser and through other things that new tech companies could emerge and challenge it. Now, the last point to your earlier question, these top tech companies are a quarter of the S &P. I think this is beginning to really show the realization that all companies are heading towards becoming tech companies, that you need that tech amplification in all of it. And that's what we need to be figuring out across all industries.

13:54And it's the thing that we need to be embracing for the future of our economies, the future of our prosperity as societies and individuals. The classic dialogue thing is we got to limit the big tech. And you're like, well, that's if you want to limit your economic future, right? It's like, no, what you want to do is say, how do we leverage the fact that we have some technological advantages to benefit society broadly? And that's where the intellectual work needs to be. Reid is such an impassioned advocate of technology, but that doesn't make him wrong. The future is coming faster than ever, and you want to be on the right side of it.

14:30After the break, we talk about Mark Zuckerberg and Meta, the Apple Vision Pro, tech layoffs, and more. Stick around. Real leaders don't back down when the stakes are high. They innovate, they push forward, and then they take the stage at the Masters of Scale Summit. Join us in San Francisco, October 7th to 9th, to hear from the CEO of the New York Times, scientists using cutting-edge technology to find cures, the leader of crypto powerhouse Coinbase, a retired four-star general, and many, many more. Apply now at mastersofscale.com slash apply25. That's mastersofscale.com slash apply25. If you're ready to take your startup from idea to impact, then AWS is your launchpad.

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16:09The National Association of PEOs says businesses can grow twice as fast if they use one. So if you're scaling, make it simple with Deal. Go to deel.com slash mos and get up to three months free. Before the break, Reid Hoffman shared his perspective on how AI is altering the game of scale. Now we talk about Mark Zuckerberg and Meta, the Apple Vision Pro, tech layoffs, and the trap that many business leaders are falling into in 2024. Let's jump back in. So I want to ask you about Mark Zuckerberg and Meta. Facebook was the quintessential social media company. And then it sort of seemed like they were ceding ground, particularly to TikTok, right, which sort of captured the cultural heat.

17:00Zuckerberg's talking about the metaverse and spending a lot of money, maybe not getting a lot for it. Apple Vision Pro is getting all the buzz more than Quest VR did. And Sheryl Sandberg steps aside as COO, and then she's leaving the board. And then on one day, Meta stock, bam, goes up like 20%. What happened? What did people sort of misappreciate or misunderstand? And I don't know whether it's about Meta or about the industry or about Mark. It didn't surprise me, although I'm not a public market trader, and I tend to be structuralist over years. What is the position over one year, three years, five years, 10 years?

17:41It's part of why doing early stage venture. Now, one, Mark is a bold innovator. We'll take bold bets. Some of the bold bets are pretty amazing. Like when he bought Instagram when it was really small, bought WhatsApp. Some of the bold bets I personally don't think work out as well. Oculus and Meta as they focus, but he's a constant infinite learner. And so I saw when the light bulbs came on of, oh my God, this AI thing is going to be really important and we should be doubling down on that. I don't think their agents and so forth are that good yet. But the notion of how do you tie the AI stuff into the advertising system and have an alternative, really compelling advertising system?

18:23How do you continue to do engagement with the feed and other kinds of things, which I think they do? Now, I think it didn't surprise me at all that they would have a vigorous recovery, given Mark, given a focus on AI, given a natural set of assets in aspects that are important in human life. I mean, he made the business more efficient, I think, than people expected. And I think the stickiness of the different parts of meta proved to be stronger than certainly the marketplace was anticipating. I mentioned that Quest and Apple Vision Pro, have you tried these things out? I know Microsoft has its HoloLens.

19:04Is this an area that you play with, that you dabble in, or is it not really your jam? Well, my very first product management job was in virtual worlds. Having gone into the promise of it and realized it was so under-delivered that I'm a little bit overly skeptical. I'm part of the reason why Greylock didn't invest in Magic Leap and other things because I go, look, this is really amazing technology, but I just don't see it coming together as the new tech platform yet. Now, I've had a couple of my trusted friends, David Z, other people say, I really need to play with Vision Pro. I need to see what it is.

19:41I have played with the Oculus. I have played with HoloLens. I have yet to think that any of these things are a new platform. I definitely think that the economic cost of the Vision Pro means it certainly won't be a platform yet. Now, will it be, as some people are speculating, is it a limited N number of iterations from here to there to make it work? Is it two or three? and I think that's part of the reason why David has been like, okay, you really need to go play with this. And so I've ordered one, right, to get a sense of it. The cautionary thing about how you get to platform. Here we are, you and I, talking, wearing glasses.

20:23Yes. Even these things, which are an amazing part of early technology, a number of human beings pay$5 ,000 to have a laser applied to their eyes so they don't have to wear these things. So that's what you have to clear in terms of the value proposition to get to a general platform. And if it isn't a double-digit percentage of humanity, then it's not going to be a general platform. Now, it may be a work platform. It may be like a doctors, nurses, police people, fire people, other kinds of things is part of why I think the HoloLens and Microsoft kind of realize better than the consumer folks for these things.

21:03But as a general platform, you have a very high hurdle to clear. The benefits really have to be powerful enough to make it worth the inconvenience of, much as we love that we have these spectacles they allow us to see, they're a pain. They're a pain. Yes, exactly. In the optimistic good times that the tech industry is having right now, there have also been a bunch of layoffs talked about at places like Amazon and Meta and Alphabet. And I've heard kind of three different theories about why these layoffs happen. One being overhiring from the pandemic, which is something that Zuckerberg has said at Meta.

21:47They sort of overhired some. Another argument is copycat layoffs, basically doing it for performative reasons to appease public market investors to make it look like you're being sort of sharper. And the third being that AI is making things more efficient and that these businesses just don't need people the same way. Now, obviously, there are many more reasons why layoffs could happen. I'm curious whether you have a theory about why this is happening. So the first one is certainly the case, the overhiring from the pandemic and kind of reconfiguration and so forth, because people overly generalize from, oh, during the pandemic, this is the new normal.

22:25It's like, well, no, it's not going to be the new normal. To some degree, it was almost like a collective mistake where everyone's saying everyone else is hiring, so we should be hiring too. Now, the copycat layoffs is actually a touch more sophisticated as a question, which is I don't think that any of the leaderships of any of these companies is so banal as to simply be, well, because the investors are demanding it for margins and other people doing it, I have to do it too. And so it doesn't say there isn't something there. But I think what actually, in fact, goes into this is when there is that zeitgeist, a time of layoffs, you can then kind of go, OK, I now have a permission to do some of the resetting in the business.

23:08Like I should be doing less of X, more of Y. Things I should be doing anyway, but suddenly I can do it and it's sort of part of the zeitgeist and I'm not going to pay as much of a price for it. Exactly. Because the price you usually pay, say you're the only person doing these kind of layoffs. Like, is it because you suck? You've made bad decisions. And so there's a pressure to not do it in bold stroke. If we do that and we're standing out there by ourselves, it causes a bunch of negative speculation. Whereas when we go, oh, shoot, we can now take opportunity, like the industry itself is doing layoffs, and we can do some reconfiguration.

23:46And I think that's much more of what you're happening. It's all kind of simplistic press stories. And what you should really do is look underneath. It's like, okay, what are they reshaping their businesses for? Now, they may be reshaping their businesses for an anticipated AI productivity. I think there will be a bunch of AI productivity. I don't think that much AI productivity is currently baked into the numbers and baked into the way that people are operating. So it's certainly not a post-fact thing. I think the other cards, the consideration are this gives us a way to reshuffle and that reshuffling, that reconfiguration is what you should be looking at at each of these tech companies.

24:22And I do feel like after, over the last four years between pandemic and supply chain and inflation and AI, that a lot of leaders that I'm talking to are sort of, they're not saying that they're resetting or they're like, let's not be too aggressive, but they're sort of reflecting a little bit right now. And I don't know, I wonder sometimes whether that's complacency or that's fatigue or that's wisdom. Hmm. Well, frequently with these choices, Bob, as you know, it's a combination of all of them, and it depends on the different leaders, right? To essentially go to what people should be, as part of the resetting, is should be saying, look, we are at another wave of technological transformation.

25:07We've had a bunch. We've had the internet. We've had the iPhone. We've had mobile computing. We've had cloud. Now AI is going to take all of those to another level. The reason why it's so big is it's a compounder of all of them together. And that's coming in a small n number of years. So if you're not plotting part of the technology strategy of your business to be doing this, and I don't mean IT strategy. You know, it's the technology underlying how your whole business operates, what your supply chain is, how your employees work together, how you sell and market, how you build and constitute your product, how you do innovations, how you do financial analysis.

25:51All of that is an evolution from essentially the steam engine of the mind and AI. And so the advice that I give everyone, they say, well, what should I do now? It's like, well, it's all in very dynamic flux. You can't just say it's only X right now and that's all you need to do. So what you need to do is start experimenting with it. So the one thing about the reflective thing where it's lazy is, no, no, you should be diving into the experimentation. Not necessarily committing fully to a particular path right now because you don't really know. But if you're not experimenting with some vigor, you're likely to be making a pretty dangerous mistake.

26:27And if you're sort of waiting for things to become, quote, clear, which is what a lot of leaders, I think, want to do, they're actually losing ground because they're not getting comfortable with how this new technology can change the way they operate. Exactly. You should not be waiting. You should be experimenting, possibly experimenting vigorously. Well, Reid, thanks for doing this. Always good to chat with you. Always great to talk with you, Bob. I look forward to the next.

26:56What I came away with most from this discussion with Reed is the potential trap of waiting for the right moment to engage with a new opportunity or a new challenge. If we're waiting for clarity to emerge in today's fast-changing world, then we're waiting too long. We have to jump in and experiment in the face of ambiguity. I'm Bob Safian. Thanks for listening.

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29:44Thank you.

From the publisher

Will OpenAI’s new text-to-video tool Sora revolutionize content creation? In this episode of Masters of Scale, Reid Hoffman joins Bob Safian to discuss Sam Altman’s fundraising, Meta’s dramatic resurgence, and three catalysts driving the recent tech layoffs. In this rapidly evolving world, Reid makes a case for how AI is redefining the game of scale, and why entrepreneurs shouldn’t buy into the myth of a “right moment” to engage with a new opportunity or challenge. 

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