The Truth About College Degrees In The AI Era - Vinod Khosla

But I want to just say, maybe I should touch upon your investment in OpenAI. In 2019, it was— you have been known for contrarian bets, but this was way out there contrarian.

We wrote a $50 million check, and when we wrote the check, we also sent an apology letter to our LPs saying, sorry, we're making this investment. It doesn't make any logical sense. It's a nonprofit, no product plan, no business plan. I love making those bets.

So freedom is the ultimate promise of AI and just people free to live life and that becomes a new normal.

Who wants to work on an assembly line for 8 hours a day for 40 years? That to me is slavery. It's servitude to survival because you need a job. Those are not jobs with human dignity.

But what does it mean for someone who is going to college now? Why go to college?

I think the only reason to go to college is Vinod Khosla, welcome to Sparks.

I've been waiting for this conversation for a long time. You may not recall, but I have been to this office a few times. I've met you in different contexts. Yes. Was, was good to see you at the AKI event as well. I want to start with the— I'm in Valley for last few days and I come here often once or twice a year, but the pace seems very different now. There's so much action and a lot of it seems to be concentrated in San Francisco. Is this— you've been in Valley for last 40-odd years. Does this feel different or?

It definitely feels different. There's a lot of activity. A lot of genuinely good startups, but also a lot of money. And that combination has resulted in velocities that are very, very high.

In one of your talks, you mentioned there, and I think it's fairly obvious also, there are only 3, 4 very deep model companies now in the US at least, and then maybe there are equal number in China. Do you think most of the innovation is concentrated inside this company and there's a delta between what the companies outside these companies are able to do?

No, I think there's a lot of innovation outside these companies, a lot going on, at least in this area. Like every day there's a new idea that's worth considering, if not funding. Result of which, you know, the best way to understand Silicon Valley today is of all the unicorns, 91% are in the Bay Area. The rest of the world combined accounts for 9%, which is pretty stunning. The second highest territory—

This is all unicorns, not AI unicorns.

I think it refers to AI unicorns, but— The second highest is New York with 2%. So it's even this number 2 is largely irrelevant. Yeah. And so the action is here. Almost all the innovation is here.

And see, if you look at any AI company today, the engine of all AI companies, obviously the inferencing, which is powered by one of these companies. What is the nature of innovation outside? But I want to just say, maybe I should I want to touch upon your investment in OpenAI in 2019. It was— you have been known for contrarian bets, but this was way out there contrarian. If you recall your thinking in the discussion, what convinced you? It was not even clear where OpenAI is going to be for-profit company, nonprofit, yet you wrote a pretty large check.

So I wrote a check that was twice the size of the largest initial check I'd ever written. Vinod Khosla, because I don't like writing huge checks. We like very small checks. So I'd never written in 40 years a check over $25 million initially. Later on, we'll add additional money. And we wrote a $50 million check. And when we wrote the check, we also sent an apology letter to our LPs saying, sorry, we're making this investment. It doesn't make any logical sense. No sense. It's a nonprofit, no product plans, no business plan. It's just a tech— technology effort. But the idea was very simple. So today that letter is sort of a funny thing. And I should probably tweet it. It was so funny nowadays in retrospect. But what was very clear to me is when you get AI, it'll be very consequential. So it wasn't when we would get AI. It was when we get it, whenever that is, whether it happens in 2 years or 10 years, didn't matter. It would be very consequential. So the bet was very much on the very large upside if you were successful. And that's our kind of bet. I love making those bets.

And then each bet has to be, I guess, two parts. One is you were convinced that AI, whenever it does happen, will be very consequential. But this particular company, because when you're dealing with so much uncertainty, almost no precedence and almost no clarity about timelines, picking a team versus the other also has to— there's probably some method behind that.

Well, absolutely. You judge the team. I thought this was a very good team. We were very confident in the team. But there weren't also a lot of companies around. It was Google. Mm-hmm. Yeah. OpenAI and Baidu, maybe, as a Chinese company. So there wasn't a lot of AI efforts. It's not like today.

And there's this whole thing about opportunity meeting a prepared mind. I know you've been talking about AI for a while, including, I think, 2012. You've been talking about AI doctors and so on. So is it almost a case of you were looking for something like this and you happen to eventually, you know, I assume you must have gotten to know—

I was absolutely looking for it. You know, there's some important areas of technology that I tend to like to identify and say we should, if we find a great startup, invest in it. By the way, same year— it was 2018 that we committed to OpenAI and closed in early 2019, uh, but same year we invested in fusion. Nobody was expecting fusion in the next 30 years, yet we placed that bet, and I think it looks pretty good today. So, uh, you know, I like unusual bets. We also placed a bet back here in public transit, which is also not considered a venture area. So, um, I think around then we also invested in a hypersonic aircraft. That was also unusual for a startup to be doing hypersonic aircraft. So we, we're not afraid to place large bets. We tend to be cautious about how we guide them so they don't run out of money because some of these areas become very difficult. But I'm always trying to say what will be hugely disruptive 10 years from now that people aren't expecting. If everybody's expecting it, then it's not interesting.

But it has to be at the sweet spot of people are not expecting it, but it should. At least on average, should become real in the next 10 years. Because if, let's say, OpenAI bet, if you were to place the same bet in 2009, the story would not look that great because there's a finite lifetime.

Look, this is the hard part of venture investing, is guessing when you will have breakthroughs, when will large changes happen. So I'm always looking, like everything I look at, is between 2030 and 2035 and say what can be consequential.

And this philosophy as a venture capitalist, or I guess you would like to call it a venture advisor, has been a work in progress. You know, you've kind of honed it over a period of time by seeing a lot of different patterns. Like, what is the backstory behind this way?

So I like to differentiate from people who are investors. You know, they have to run spreadsheets. We never run a spreadsheet on rates of return. So rate of return calculations are just mostly misleading in our business for what we do. Most other investment firms use it.

It's misleading because of the artificial mark-to-market that you—

Well, it's not artificial mark-to-market. Mark-to-market in private markets is always artificial. That's not the real issue. What the real issue is, you can't predict these things. You know, if I said to you OpenAI will have no revenue in January of '23, but January of '26 it'll have $20 billion, you'd say I'm crazy. So sometimes it's better to realize you can't forecast instead of trying to make a forecast. And then using it as a basis for calculation. You just say it's not possible to forecast.

See, today AI is obviously very impressive. It can do a lot of things. And one can also argue that we are not fully exploiting what's possible with AI even today. But a lot of the AI investment, there are now, I think, close to $1 trillion of CapEx which is being spent this year and perhaps next few years, every year. This also assuming some— this scaling to continue for next few years, is that you almost take it for granted. Now we have hit an inflection point. The scaling will continue because it can also stop. We start— the asymptote may play out and this may have implications for the whole journey.

And if you look at the 5-year journey, yeah, could you have 10 times the amount of inferencing? Absolutely. There's demand for that.

10 times more intelligent, like what's the metric?

10 times more inferences than we do today. Could you see 100 times? Possibly. Uh, depends on the price decline.

And you're not commenting on quantity of inference, not quality of inference?

No, just the number. Yeah, yeah, got it. Sort of measure it in tokens. Produced. Now, the intelligence of each token will also go up, which is the quality aspect. So I suspect we'll see continuing increasing increases in the number of tokens, almost exponential. Yeah, we'll keep seeing, um, large but more modest increase in intelligence per token, which is human intelligence delivered.

Yeah.

And we'll see pretty rapidly declining costs per token. And if the costs decline, the demand will be there. I'm pretty confident about that.

But is any of this contingent on newer breakthrough?

I don't think so. I think we look There's a set of breakthroughs we can forecast pretty easily because we know how to get there. If we scale X or Y, you know, we know scaling laws apply. We know certain cost curves of silicon and other things. You put all that together, I don't think any massive breakthroughs are needed. I consider things like memory in AI systems, continuous learning in AI systems as sort of routine things Again, a question of when it'll come along, not if.

Yeah.

And the bigger question is, when they come along, how good are they? How good is the continual learning? How good is memory? How, how well can it be utilized? So I, I think those are predictable. I also expect we'll see unusual phenomena in AI progress that we aren't planning on.

Unusual good, unusual bad, we can't say.

I think mostly unusual good. There will be some bad things for sure.

I want to bring the conversation to health. I think around 2016 you wrote this paper, I think it's called something like 20% Doctor, which was about the role of AI in medicine and ubiquitous, you know, world-class doctor available to everyone in their mobile phone. In fact, incidentally, Vinod 2016 was when I started my second company and it was a health company. We wanted to solve for holistic lifestyle across everything from fitness, food, and marrying to primary care. Most of those things didn't work out. Fitness worked out very well. So today it's a very large fitness company. But the dream of that AI doctor was at least that we could pursue. But fast forward 10 years from now, you think we are much closer to now that vision of where everyone have access to?

Yeah, there's no question. Even 5 years from now. You won't need a human doctor other than in interventional medicine. That means like surgery and heart surgery or things like that, or burn victims or broken bones. I think 5 years from now, the expertise involved in a doctor is almost completely already in systems. I no longer consult doctors. I fractured my wrist. Last week, got an X-ray, sent it to ChatGPT, and told me what to do. Now, I have had to have a real surgeon. I called the surgeon. He, you know, like any surgeon, he said, can you come in for a consult? I said, I don't think I need it. Here's what ChatGPT told me. I sent him the exact comments from ChatGPT. He said, this is exactly what I'd tell you, so you don't need to consult. Will go directly into— my first time I met him was in the surgical theater. And it worked out. And since then, I consulted on every question, like, can I do this, or can I do that, or when will the cast come off, or when can I put pressure, or— it's a much better, I would say, it's at least as good a doctor and a much more accessible doctor. I can ask it a question at midnight and I get an answer within 5 minutes. Yeah, as opposed to waiting multiple weeks for an appointment. That's possible for every person in India today. And I, I— one of my pet projects is to get that going and deliverable in India as a nonprofit effort within the next 2 years.

And why does it need to be a new effort? GPT already is available in India. They have, I think, pretty wide distribution for one of the largest user base for GPT as as you say, I also, you know, consult GPT, my first protocol for any health issue, and I'm pretty happy with the outcome we get. Why does it require separate effort at all?

I think this is misunderstood. The safety requirements for AI are much, much higher for some areas like health than in others. Yeah. So today, if you consult ChatGPT, The general triage error rate will be 20 to 30%. That means you get the wrong answer 20 to 30% of the time. Now humans are pretty bad at triage too. So you have to be careful. But when you add a health-specific system, and my son has a company that does that, but they use GPT-5. But layer on things on top, the triage error rate goes to zero, right? Much better than human beings. And so I think in all these areas, if you're talking about national defense or healthcare or financial trading, right, you want to use these large models. All of them will— are essential. They're necessary but not sufficient. You need additional things. Yeah, or various levels of insurance.

So this is not about making AI better with further scaling, it's about building enough guardrails and checks and balances and human—

those kinds of— every domain is a little bit different, you need different things and different guardrails. But yes, you know, we know AI systems hallucinate. Yeah, it's not been easy to reduce hallucination. If you're doing customer support and you hallucinate somebody's bank balance That's a problem. So there are special systems that'll ensure that the systems don't hallucinate and still use these systems, but with the extra guardrails and safety cells, whether it's financial or healthcare or other critical areas.

And these additional systems are more deterministic rules-based systems. They are not additional inference to kind of—

They're not rules-based systems. I think rules-based systems are too hard to do and manage. They're just better different techniques with different trade-offs.

Right. Got it. Got it. So maker-checker and probably multiple checks, but they're all inference-based systems that are layered together in some way.

So that's why there's opportunity in application areas too.

Right, right. And this is— I'm just thinking about now India healthcare, since you mentioned we have massive public healthcare system. There are, I think if I'm not mistaken, hundreds of thousands of doctors work there. So one possibility is to co-opt them in some ways to be the human layer.

Yes. You know, whether you need a human layer or not and for what is an important question. And I think each human being will make— every citizen in India will make their own decision. Obviously, if an AI is going to tell me I got cancer, I might prefer a human being to tell me that. Than get a text message. So, but different people may prefer different things. Others may say, hey, tell me as soon as possible, text is fine. I don't want to wait one week for a doctor's appointment to learn that. So different people will prefer different things, and I think human preference will become a big part of how we use AI systems.

Yeah. What does education look like in this? You know, it's both. Maybe I'm asking you a two-part question. For a grown-up person, you know, someone who's in their 30s, 40s, 50s, probably I assume people need to learn a lot of different things and perhaps unlearn. And then similar question for someone who is coming of age now. How should they think about education?

I spend most of my time today at age 71 learning. And learning new subjects. If I'm interested in fusion, I learn about fusion. If I'm interested in biology, I learn about biology, cancer drugs, whatever I need to learn, I can learn now. So the opportunity for 30 and 40-year-olds and 50 and 60 and 70-year-olds is huge as far as learning, and it's almost all free. So that's the big, big advantage.

And when you say learning now is mostly going to GPT and just finding out the right resources from there and then follow them?

Yep. That kind of thing. Yeah. I often have long dialogues with GPT on a subject. Yeah, even a typical, how do you design a much better drone motor? I've not designed a motor in 50 years, but I can still design one with GPT today. And say, I understand the basic scientific principles and I know how to apply them. And I'll do these exercises. I'll say, how would I design a cancer drug for this cancer? All those are available in Possible.

And this is something you said, this is something one can do or one should do.

Well, that's each person's choice.

To survive and thrive in this new world.

Survive and thrive. You have to do it, right? If you don't want to keep up, that's fine. But I'll give you the best example. You know, most people in the software business know GitLab as a company. He was one of our founders. We invested when there was 4 people, became a big company, public company, and then the founder got cancer. And if you Look at his history. He basically decided very quickly he wouldn't talk to doctors. He would essentially design his own cancer treatment.

Yeah.

And he got deep in. He learned everything from scratch as a software person and did his own cancer vaccines, cancer drugs, custom drugs for each stage of his cancer.

Yeah.

He wasn't given that long to live. He's alive and well and healthy now and doing even more drugs for what he might need as cancer drugs in the future. So if a software engineer can do that and you don't need a medical degree, that's the world we can live in. We can choose not to or choose to live there. I find it very, very inspiring.

Yeah, this is an incredible example. Does he talk about this publicly?

Oh, he talks about it. In fact, He's given a couple of talks called— it's called Going Founder Mode on Cancer. It's a beautiful talk.

I'll ask you for introduction, try to invite him on this, because this is ultimate example of what someone powered by AI and the right mindset with no knowledge can do, right?

Just general intelligence, right? And you know, you don't have to have a degree to have general intelligence.

But what does it mean for someone who is going to college now? Why go to college?

I think the only reason to go to college is to learn how to learn, to learn curiosity. Why do I work 80 hours a week? Because I have curiosity about so many things. You know, I asked ChatGPT, what do you think of all my searches over the last couple of years? It freaks out because it says, you've been all over the map. You're learning about cancer, you're learning about fusion, you're learning about designing motors, you're learning about, you know, various AI algorithms, just everything. Yeah. Even gardening. I learned so much from ChatGPT about gardening, my own garden. Yeah. So, you go because you learn how to learn. You go because you learn curiosity.

Yeah.

And by being active and online, and this may be the single most important thing, you get agency. You feel like you can do things. I think that's the difference between founders and non-founders. Founders have agency. Instead of looking at a problem and saying, they should do this, which everyone says, founders say, oh, there's a problem, I'll do it. I'll solve it. So that's founder mode.

Yeah.

And so there's no— it doesn't matter if I know about it or not, right? I'm just going to go start learning and attacking the problem. Yeah. So agency becomes very important to learn for both a 5-year-old and a 25-year-old.

So perhaps it has a huge implication for how schools and college cultivate this curiosity and agency, because a lot of it is about teaching you something what's in textbooks and being able to repeat it back in exams and so on. And that's how the whole system works and people become very good at it. But that's not exactly fostering curiosity and agency.

No. And I think universities need to change. I was at IIT Delhi in February. Myself and Sam gave a talk and then I was talking to the director and he was saying, we are going to expand the university. This is what we're going to do with classrooms.. And my answer was completely irrelevant. Do you think any of the students in our audience today will know more than the AI in their area of specialty? The answer is obviously not. Right. Right. So what should you do with IIT Delhi? I said open more dorm rooms to have more students. Yeah. Have more meeting rooms, not classrooms. Have places where people can gather and discuss things and debate things. And do the learning at home and come back and discuss topics. So there is a role for universities, but it's not the old role. It's not lecturing out of textbooks. Those can all be thrown away. They're all obsolete anyway because the world keeps changing, especially in technology areas like engineering. Every day you can say, how do I design a new magnet without rare earths?

Right.

You're not going to find it in a textbook. You're going to find it on ChatGPT and then pursue trails and build a little model and then experiment. We have people doing things like that. Yeah. You know, the country doesn't have rare earths. Can we not depend on China? Do our own.

Yeah.

The answer is probably a small group of people could solve that problem. That's called having agency if they choose to go do it.

Yeah, and I want to just underline that I have very often noticed that sometimes I stop myself from asking the question. But if I do ask a question and engage with any of the AI models, it leads to a totally new trail and you didn't realize it's possible. So then having that agency and somewhat courage to act on it, just, you know, like this, this is this founder you mentioned, you know, just trying to solve, figure out his own cancer situation with AI. It will not occur to most people to even attempt. And a lot of this promise of AI, Vinod Khosla, today everything is in some ways digital medium. That's all mostly text-based. Yes, can process some image, etc. But majority of both input and output is text with some translation. Where are you on the whole this physical aspect? You know, AI—

Well, physical AI is coming in the next couple of years. We'll have the ChatGPT moment of physical AI. I've tweeted a bunch about it. So I don't think there'll be an issue with robotics in 5 years from now.

Can you envision what does the moment ChatGPT moment can look like, or what are the possibilities where we say this is some— becomes relevant to all of us?

You know, it's— I think when you can put a robot in your home and can cook your meals, that's a pretty stunning point. Obviously there's lots of industrial applications, but a robot in your home.

And these look like humanoid robot, not specialized arm or what?

Most likely humanoid. I think there'll be multiple specialty form factors, but humanoids will be the largest form factor by a lot. And because they'll be the largest form factor, they'll have the most scaled manufacturing and they'll have the lowest cost.

Yeah.

So you'll need auto manufacturing-like facilities to make large-scale, very low-cost. You know, cars don't cost that much more than the cost of steel.

Right, right.

If you look at it, because the value-add is so automated and so scaled that it's very low overhead.

So, and if you play out this exponential growth and impact of AI, The world will be unrecognizable.

I think 15 years from now, the world will be unrecognizable. A 5-year-old kid today will grow up in a very different world by the time they're 20 or 25.

But it has also implications for social, political, economic structures also. They can't just hold up the current way because in some ways today, if Anthropic has gone from nothing to a trillion-dollar valuation in 4 years. And it seems, you know, Google is now $5 trillion, probably most likely going to a $10 trillion company in next few years. It seems like the benefits today are getting highly concentrated while there is some innovation outside, but most of the benefits seems to be flowing in a very, very small area.

Yeah, I disagree with that. I think the question to ask is, is 95% of the population better off? Not what's happening with the 5% who are making all the money. And that is happening. There's concentration of wealth. And technology has always resulted in a concentration of wealth. And there'll be more nonlinear. But if we stop worrying about the few percent and say, will 95% of the people be better off in 2040? Absolutely, no question.

They will be better off because they are making more income in their jobs or they will require some redistribution, very proactive.

No, because they have access to services. If they need education, it's free. If they need healthcare, doctor, it's free. If they need legal services, it's free. If they need more entertainment, it's near free. Hopefully even food and others will get cheaper because of robotics.

So I don't need to make $100,000. Even I make $50,000, I have dramatically better lifestyle possibly.

My bet is We'll have a very deflationary world before 2040, and prices will decline very dramatically for most goods.

Yeah.

A few things that aren't done by robotics or have other physical constraints will be more expensive. But we'll have— for today's measure of GDP, which is defined as a basket of goods and services that we measure today. Yeah, that basket will become much cheaper.

Yeah. And I think some of the forums, Vinod, you have argued for that it will at some point require some government ownership for—

I think there's many different systems possible. Each country will adapt its own.

Yeah.

You know, likely the US is very different than India, is very different than Germany.

Yeah.

Some people will resist AI, some countries will, and it depends on the politics in the country. So it's very important for a country like India to show the benefits of AI to people first. Yeah, free doctors, free teachers, free agronomists, so every small farmer can worry about it and, and the price of input. Yeah, goes down.

Yeah.

And so they see the benefit before they see the asymmetries. So there will be more asymmetry. Yeah.

And for India, I guess there's additional challenge of figuring out that this whole IT service industry and BPO industry, which is a huge source of foreign income for the country.

The AI business will be gone. There may be new opportunities in deploying AI to the planet because India has an advantage in learning how to deploy AI. Yeah, very few of the companies are doing it today. Yeah, but, uh, if they do, they'll be in good shape. If they don't, they'll be in very bad shape.

What are the examples of that? You know, what can India develop at scale which can employ millions of people and participate heavily in deployment of AI?

Yeah, it's, it's a complex area. Um, I, I, you know, I I've written a piece about it earlier this year for AI Specific to India. Yeah, so I'd refer you to that. It's about 20 pages long.

I'll go through it.

So it's a fairly detailed look at what we'll do. But, you know, the basic things people need— yeah, health, doctors, education, um, entertainment, food, those should become much, much cheaper. Housing is the one area that's troubling because that needs to scale and still mostly depend on materials cost. Yeah, not so much labor, right?

Yeah, I guess if you have physical AI and really cheap humanoid, so probably the—

yeah, but cement will still cost like cement costs. Hopefully we can do something about those, scaling those things.

Yes. Vinod Khosla, I guess, is mostly energy costs in some level. So if energy becomes cheaper, then I guess you can, you'll have more options. And where in this whole, the, you know, in the quest for solving for energy for an AI space has become a factor now. And you have, I think you've been investing in space as well with the Rocket Lab way back, I think 2012, '13. And so on. Have you— are you convinced that space has a role to play as photo in, in this data centers to support massive compute infrastructure?

Look, I would say data centers in space don't make sense today, but there's certain cost parameters like transport cost to space for a kilogram of weight. Things like that that could make it more cost-effective. You know, are factors of 10 possible in cost reduction? Yes. And if that happens, then the equation might change. But with today's increase in— today's costs and even normal declines in costs, data centers in space haven't seemed to make sense. But I don't rule out larger increases in— decreases in cost. And if that happens, then assumptions will change around data centers in space.

If you apply your framework of what will be feasible by 2035, which side of bet today you will take? The space-based data centers, a big part of our life, or unlikely?

I would say unlikely only because the cost on Earth will decline very rapidly. Got it. Once you have fusion, you don't have a power generation problem, for example, by 2035. So if power is dirt cheap on the planet, then why go up in space? Why get the inflexibility of fixed infrastructure that you can't change quite as easily as walking into a data center and changing a GPU that failed.

Right.

You know, suddenly GPUs will have to be pretty different because this radiation is not healthy for semiconductors. Power generation in space is hard. Cooling in space is hard. Now there's possible solutions to each of these problems. But if we— and if you're lucky enough to get the improvement in all those dimensions much faster than cost decline on Earth, then space centers may make sense. Today I'd bet that data centers on Earth make more sense.

Got it. And I think we'll start—

and they will decline rapidly in cost, and power will not be an issue.

Yeah. And hopefully, I guess, we'll start to get some data back as well in next few years with all these plans of various companies to have at least some experiments going on. So maybe 2, 3 years we'll have some more evidence start to pile up as well. And what is the process of looking at it? And maybe we can discuss in the context of fusion, because fusion, even today, most people don't believe is going to be realistic, the net gain from fusion over next 5 years. I think this is an area I tried to study last couple of years. In fact, I was looking for a possible investment in India. We have few fusion startups. But, and maybe I'm guilty of, you know, falling, looking for consensus and not outlier belief, but pretty much anyone you will talk to even today, they think it's not happening.

And that's the key. I don't talk to experts. You know, experts are experts in a previous version of the world, not the one you're trying to create. Like, that's the key to remember. If I get 3 teams to look at fusion, and all three agree, then it's probably not an unusual bet. It's consensus.

Yeah.

If teams disagree, then it becomes more interesting. So it's— look, it's hard to explain this process. I think we do a pretty good job of judging where technology is going. Yeah. It's probably 60-70% accuracy. And then we make a lot of mistakes, but we are not afraid of those mistakes. So we've made our fair share and never afraid to be mistaken. But, you know, when you're mistaken and you make the wrong bet, you lose 1 times your money. But when you make the right bet, you make 100 times your money, then it's worth, back worth placing, right? And that's our paradigm. You know, if OpenAI was successful, we should make more than 100 times, which we will. But that's always been my approach. Most people are afraid to fail. I like to say my willingness to fail is what gives me the ability to succeed. I'm not embarrassed when I fail. Yeah. And so I don't worry about it. If you write every investment off the day you make it, then you only have upside. Same is true of fusion. There's a trillion-dollar company in fusion to be had. Most people, you say, don't agree it's feasible. I'm very— I think at this point there's greater than an 80% probability in 5 years nobody will be debating fusion works and fusion works economically. My bet is in 2 years, people will say fusion works. In 5 years, people will say fusion works economically because you have to pass through both gates. And once it's economic, it's the source of energy for the whole planet. By the way, there's other sources. Super hot geothermal is another one I'm very excited about. I think it can be cheaper than natural gas and oil as a source of energy. Both fusion and super hot geothermal.

Okay.

That means geothermal above 400 degrees centigrade.

Let's talk about both, but I want to double-click on fusion. Just, I'm trying to get to, you know, your process and way of thinking. Let's take fusion. There are two ways one can look at, you know, one is macro. We obviously know fusion works. We can look at the sun and know it works. But there's so many competing platforms and to really get into nitty-gritty of fusion, you know, different technology and so on, you need to fairly technical in nature. Do you at Khosla Venture employ consultants, or maybe, you know, it goes against, you know, the philosophy of consulting experts? Is it like a macro bet, or is it like looking at technology has now reached these many gates and readiness, therefore it might be realistic in 5 years?

No, I think we look at fairly detailed look. Yeah, uh, obviously we employ experts from time to time, but most of our gut gut call is ourselves. We are pretty technical. We can make these calls. So more expert diligence is confirmation rather than decision. The question you have to ask in something like fusion is, why now? In 2018, what has changed that would say it's not possible before, but now it might be possible? And that was high-temperature superconductors. And that dramatically changes both the experiments you can run and the rate at which you can run them.

Yeah.

And also the economics. You know, if you can use high-temperature superconductors, which was the big risk to build in 2018, to build a 20-tesla magnet. You know, if the magnet is 4 times more powerful than what was possible before, your reactor is going to be 1/50th the size.

Right.

It suddenly becomes much more feasible to experiment, try things, build things. It doesn't take 30 years to build. It takes 3 years to build. And so everything becomes faster. And that was the bet we placed. And that's the kind of thing we look for. You know, every time there's something on the horizon that others don't believe, that we have to believe, and then find the right team. Finding the right team is very key. When I met Bob Mumgaard, he was a senior fellow at the MIT Plasma Fusion Lab. I was just visiting because I like techie geeky places to visit. And he showed me this reactor where before I stepped on it, the temperature was a couple of hundred million degrees, like 30 seconds before. And now you can step on it. Pretty cool. And so I like geeky things. And we got talking. And the more we talked, the better I liked him and what he was thinking and said, let's build a plant. So that's how that came to be.

Got it. Got it. So a lot of, I guess in this case, probably bet on the person as well.

Bet on the person for sure. Bet on the technology direction. What is feasible? What's not? That's a risk assessment. Mostly I will do my own risk assessments and other people in our firm are very good at it too.

Right.

So together as a group, We can do that.

Yeah, one of the things when I, you know, when I try to study fusion, one thing keeps coming up that what about fission? We have not really exploited full power. We have so much uranium, thorium, and so on, small modular reactors. Do you also look at this, that we need, world need a lot of nuclear energy? It'll be great to have a lot of our energy, especially now with the power energy that AI needs to come from nuclear process one way or other. Do you think about fission as well, or fusion is something that once it's solved is obviously We have infinite energy.

Once fusion is solved, there's no need for fission. Yeah. And fission has a different problem, at least in the West. Nobody wants a fission plant in their neighborhood. So fission technology is not hard.

Yeah.

It's possible to do fission technologies and even like the third thorium reactor India has been working on, which is a very good idea. But my view is very simple. If after you decide to build a plant and have the technology, you're going to have 10 years of lawsuits, nothing's ever going to pencil out. So you have to spend a lot of money before you know somebody will let you build in that neighborhood. And if you're building 5,000 plants for the United States, it just doesn't become feasible.

Right.

So you have to look at the world holistically and say the politics will not allow fission to have 5,000 reactors in the US or 5,000 in India. India will need more than 5,000.

And is there a risk that same politics will also try to at least create some hurdles for these massive data centers, which are going to be energy guzzlers and which are absolutely essential for this?

Yes and no, but there's solutions. A number of the data center providers are saying for everybody in the neighborhood of a data center will pay free electricity for residential purposes. It's a small tax on their energy consumption. You know, if they're doing a gigawatt and they give 50 megawatts of free electricity to neighborhoods, people are fine. So there are solutions. You can also develop your own reactors, whether they're super hot geothermal or fusion or nuclear, you can do your own. So you're not tapping into the grid. So there are solutions, but it is a political problem.

Yeah.

Mostly because people haven't worried about the politics.

And given the current conventional source of energy that are available, next 4 or 5 years of AI acceleration, is energy likely to be bottleneck or it's where we're okay?

I think energy is likely to be a bottleneck the next 4 or 5 years. Why? Because 4 or 5 years ago, we weren't thinking about the problem.

Yeah.

And nobody thought it was a big problem. Nobody believed AI would be a large consumer of electricity. Nobody forecast that. And so nobody prepared for it. I think there's a lot of preparation for it now. And so I think 5 years from now it'll become less of a problem. But it takes 5 years to build a power plant, maybe longer. And so in the early 2030s, enough power will come online, enough capacity, enough turbines, enough alternative sources of energy. I think it's a short-term problem. It's a 5-year problem.

Got it. Got it. I want to bring the conversation back to AI and what's possible with AI. And that's the agency, I guess.

This is the agency idea, right?

Uh, Vinod Khosla, I think we're nearly out of time. On the just closing note, I want to really zoom out and the big picture question about how all of this pans out in the longer term. You know, one scenario is with this whole, let's say, the entire promise of AI is fulfilled, there is, you know, abundance. Uh, where are you on this whole so-called notion of singularity that Ray Kurzweil— and I think you've been to one of the Peter's, you know, I take a practical view.

If I look into the 2040s or 2050, it is possible, in fact, very likely, if we have the right government policy, that the need to work to survive for a living will go away. People will still work, but work on things they want to work. Not things they have to work on because it's the only job they have.

Vinod Khosla.

You know, who wants to work in a field doing farm work in 40, 50-degree heat? Who wants to work on an assembly line for 8 hours a day for 40 years? That to me is slavery. It's servitude to survival because you need a job. Those are not jobs with human dignity. I think those jobs can disappear and people can work on what they want to work on as they want to work or get good at singing, artists, you name it, sports, competing. So many things to do.

So freedom is the ultimate promise of AI and just people free to live life and that becomes a new normal. And hopefully whatever next for humanity space or beyond, I guess, will play out.

Let me say, and I say this in a piece I wrote 2 years ago, I wrote a piece, Will AI Lead to Dystopia or Utopia? India, that was on AI in the Western world. I wrote a piece earlier this year for India. I believe AI will ultimately free humanity to be human beings, not servitude to survival. Survival has been the goal of every species till now.

That's an incredible message and something to really look forward to. Vinod Khosla, thank you for taking the time for this podcast, as well as the incredible career and impact in the world through all your investment and also inspiring so many VCs as well as entrepreneurs. And I think you've had a very different way of doing things, but, you know, this track record speaks for itself. So I think, you know, talking to you is very inspiring. I'm pretty sure our audience will be inspired and hopefully it will foster more agency and more people to really embrace, you know, the promise.

I hope so. I was inspired myself learning about a Hungarian immigrant coming to Silicon Valley to start Intel. That inspired me and got me on the entrepreneurial track. So I hope more people get inspired. Thank you, Vinod Khosla. Thank you.

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