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Windsurf CEO explains why traditional startup moats are mostly silly. Varun said even with 50-100 of the best MIT engineers, that's still just "hundreds of engineering years" in your product. Someone else can build something similar in the same space. He used Nvidia as an example. People think CUDA...

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Aish

4,055 subscribers

334,732 次观看 • 1 年前 •via X (Twitter)

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10 条评论

Austin Scholar 的头像
Austin Scholar2 年前

AI apps are the future of education. But I’ve already been using them for 12 years. Want to know which are the best ones? Read this:

Jenny Xiao 🌌 的头像
Jenny Xiao 🌌1 年前

@HarryStebbings Moats are mostly a simplistic way for non-technical investors to understand what they are investing in.

Joe Blau 的头像
Joe Blau1 年前

Harry was struggling. You could tell by the angle of his neck.

Dan Gray 的头像
Dan Gray1 年前

In a pure software context he’s broadly right. Speed, initially, and unit economics over time. Obviously this is less true for hardware, logistics, infrastructure etc.

Akshat Bahety 的头像
Akshat Bahety1 年前

Execution is the only thing that matters There is no secret sauce

Culttture 的头像
Culttture1 年前

It’s crazy how the windsurf CEO wants to be a VC more than a CEO and is propped up by Indian accounts on Twitter. He loves doing podcasts and talking about moats. He’s never created a moat. 😂 Is OpenAI going to audit windsurf’s users? See how many are real? @sama

Subba Reddy 的头像
Subba Reddy1 年前

>People think CUDA is their real moat, but that's not accurate >If CUDA didn't exist,AI Cos find a way to write assembly make GPUs work >People use CUDA coz Nvidia made it really capable at low floating-point math, great interconnect,and fast computers. Not coz they're locked in

Sam Tayyari 的头像
Sam Tayyari1 年前

People forget that moat doesn’t mean impenetrable. It just makes it harder to beat. This is an all stakes game where anything can happen at any moment. The teams job is just to shift the odds ever in their favour.

Brian Sowards (he/they) 🇺🇸🇮🇱🇮🇳 的头像
Brian Sowards (he/they) 🇺🇸🇮🇱🇮🇳1 年前

finally someone talking sense

Andrew 💥♻️ 的头像
Andrew 💥♻️1 年前

That’s an excellent point about CUDA. That moat is measured in months.

相关视频

Google just launched a direct attack on Nvidia's most valuable asset. Not their chips. Their SOFTWARE. And if this works, Nvidia's $4 trillion empire collapses. Here's what just leaked: Google is building "TorchTPU" - a secret project that makes PyTorch seamlessly run on Google's TPU chips instead of Nvidia GPUs. Why does this matter? PyTorch is the MOST USED AI framework on Earth. Every AI developer uses it. And PyTorch was built around Nvidia's CUDA software. Wall Street analysts call CUDA "Nvidia's strongest defensive wall." It's the reason companies can't easily switch away from Nvidia even when alternatives exist. You don't just buy Nvidia chips. You buy into their entire ecosystem. Switching costs MILLIONS in engineering work. Months of rewrites. Performance drops. So companies stay locked in. Even when Nvidia raises prices. Even when supply runs short. That's not a hardware moat. That's a SOFTWARE prison. And Google just found the escape route. Here's the problem Nvidia created for itself: Google's TPU chips are actually GOOD. Competitive performance. Better availability. Lower cost. But developers won't use them because Google's chips run JAX (Google's internal framework), not PyTorch. That means if you want to use Google TPUs, you have to rewrite your entire codebase. Nobody wants to do that. So Google TPUs sit unused while developers fight over Nvidia chips. Until now. TorchTPU makes PyTorch run natively on Google hardware. No rewrites. No performance loss. No months of engineering. You just... switch. And Google is partnering with META (who built PyTorch) to make it happen. They're even considering OPEN-SOURCING parts of it to speed adoption. Translation: Google is willing to give this away for free just to break Nvidia's lock. The implications are insane: Every company currently paying Nvidia's premium prices suddenly has a way out. Oracle, Microsoft, OpenAI - all locked into Nvidia's ecosystem - can switch to Google. Nvidia's pricing power evaporates overnight. And the timing is perfect: Nvidia is already facing heat. Semiconductor index dropped 3% today. Oracle just lost their biggest investor over AI spending concerns. Companies are realizing AI infrastructure costs are unsustainable. Now Google hands them an alternative. Same performance. Lower cost. Better availability. Jensen Huang knows exactly what this means. CUDA has been Nvidia's untouchable advantage for YEARS. It's why Nvidia trades at 50x earnings while AMD trades at 25x. The software moat justified the premium. But if Google removes that switching cost? Nvidia becomes just another chip company. And chip companies compete on price, not ecosystem lock-in. Here's what happens next: Google needs 12-18 months to make TorchTPU production-ready. If it works, cloud providers will adopt it instantly. They WANT an alternative to Nvidia's monopoly pricing. Amazon already building their own Trainium chips. Microsoft making Maia. They're all trying to escape Nvidia. Google just gave them the software bridge. Nvidia's response options are limited: They can't buy Google. Can't kill PyTorch (Meta owns it). Can't stop open source. Their only play is to keep improving CUDA faster than Google can catch up. But that's a race, not a moat. The market isn't pricing this in yet. Nvidia down 2% today. Google down 2%. Investors think this is just "another competitor." They don't understand this is an attack on the FOUNDATION of Nvidia's valuation. Hardware is replaceable. Software lock-in is what made Nvidia worth $4 trillion. Google is attacking the lock-in. Watch what happens in 2026 when TorchTPU goes live and companies realize they can actually leave Nvidia. The "Nvidia is unstoppable" narrative dies. And a $4 trillion valuation built on software moats gets repriced.
1:10

Google just launched a direct attack on Nvidia's most valuable asset. Not their chips. Their SOFTWARE. And if this works, Nvidia's $4 trillion empire collapses. Here's what just leaked: Google is building "TorchTPU" - a secret project that makes PyTorch seamlessly run on Google's TPU chips instead of Nvidia GPUs. Why does this matter? PyTorch is the MOST USED AI framework on Earth. Every AI developer uses it. And PyTorch was built around Nvidia's CUDA software. Wall Street analysts call CUDA "Nvidia's strongest defensive wall." It's the reason companies can't easily switch away from Nvidia even when alternatives exist. You don't just buy Nvidia chips. You buy into their entire ecosystem. Switching costs MILLIONS in engineering work. Months of rewrites. Performance drops. So companies stay locked in. Even when Nvidia raises prices. Even when supply runs short. That's not a hardware moat. That's a SOFTWARE prison. And Google just found the escape route. Here's the problem Nvidia created for itself: Google's TPU chips are actually GOOD. Competitive performance. Better availability. Lower cost. But developers won't use them because Google's chips run JAX (Google's internal framework), not PyTorch. That means if you want to use Google TPUs, you have to rewrite your entire codebase. Nobody wants to do that. So Google TPUs sit unused while developers fight over Nvidia chips. Until now. TorchTPU makes PyTorch run natively on Google hardware. No rewrites. No performance loss. No months of engineering. You just... switch. And Google is partnering with META (who built PyTorch) to make it happen. They're even considering OPEN-SOURCING parts of it to speed adoption. Translation: Google is willing to give this away for free just to break Nvidia's lock. The implications are insane: Every company currently paying Nvidia's premium prices suddenly has a way out. Oracle, Microsoft, OpenAI - all locked into Nvidia's ecosystem - can switch to Google. Nvidia's pricing power evaporates overnight. And the timing is perfect: Nvidia is already facing heat. Semiconductor index dropped 3% today. Oracle just lost their biggest investor over AI spending concerns. Companies are realizing AI infrastructure costs are unsustainable. Now Google hands them an alternative. Same performance. Lower cost. Better availability. Jensen Huang knows exactly what this means. CUDA has been Nvidia's untouchable advantage for YEARS. It's why Nvidia trades at 50x earnings while AMD trades at 25x. The software moat justified the premium. But if Google removes that switching cost? Nvidia becomes just another chip company. And chip companies compete on price, not ecosystem lock-in. Here's what happens next: Google needs 12-18 months to make TorchTPU production-ready. If it works, cloud providers will adopt it instantly. They WANT an alternative to Nvidia's monopoly pricing. Amazon already building their own Trainium chips. Microsoft making Maia. They're all trying to escape Nvidia. Google just gave them the software bridge. Nvidia's response options are limited: They can't buy Google. Can't kill PyTorch (Meta owns it). Can't stop open source. Their only play is to keep improving CUDA faster than Google can catch up. But that's a race, not a moat. The market isn't pricing this in yet. Nvidia down 2% today. Google down 2%. Investors think this is just "another competitor." They don't understand this is an attack on the FOUNDATION of Nvidia's valuation. Hardware is replaceable. Software lock-in is what made Nvidia worth $4 trillion. Google is attacking the lock-in. Watch what happens in 2026 when TorchTPU goes live and companies realize they can actually leave Nvidia. The "Nvidia is unstoppable" narrative dies. And a $4 trillion valuation built on software moats gets repriced.

Ricardo

1,616,417 次观看 • 7 个月前

Jensen Huang was asked what NVIDIA's single biggest moat is. The most valuable company in the world. He didn't point to the chips. He said a competitor could clone CUDA exactly and it wouldn't matter. "if somebody came up with a GUDA or TUDA it wouldn't make any difference at all." That is the reframe. And it changes what NVIDIA is actually defending. The conventional story is that NVIDIA wins on silicon. Faster GPU, better transistors, more FLOPS. Which means the day someone ships a faster chip, the game is over. Every competitor is racing on that assumption. Jensen is defending something else entirely. He said it wasn't three people who made CUDA win. It was 43,000 people and several million developers who bet their software on it. The moat isn't the hardware. It's the install base. Now here's where it gets interesting. Put yourself in a developer's seat. Target CUDA and you reach a few hundred million machines: every cloud, every computer maker, every industry, every country. And the platform gets roughly 10x better every six months, for free, while you wait. A rival could ship a chip that is genuinely faster and still lose, because no rational developer ports a mountain of software off a platform that already owns the install base and improves itself every two quarters. He is not selling the best chip. He is renting out the largest install base in computing. The open question is whether better silicon can ever beat that, or whether the only way past a moat like this is to make the whole category obsolete.
5:27

Jensen Huang was asked what NVIDIA's single biggest moat is. The most valuable company in the world. He didn't point to the chips. He said a competitor could clone CUDA exactly and it wouldn't matter. "if somebody came up with a GUDA or TUDA it wouldn't make any difference at all." That is the reframe. And it changes what NVIDIA is actually defending. The conventional story is that NVIDIA wins on silicon. Faster GPU, better transistors, more FLOPS. Which means the day someone ships a faster chip, the game is over. Every competitor is racing on that assumption. Jensen is defending something else entirely. He said it wasn't three people who made CUDA win. It was 43,000 people and several million developers who bet their software on it. The moat isn't the hardware. It's the install base. Now here's where it gets interesting. Put yourself in a developer's seat. Target CUDA and you reach a few hundred million machines: every cloud, every computer maker, every industry, every country. And the platform gets roughly 10x better every six months, for free, while you wait. A rival could ship a chip that is genuinely faster and still lose, because no rational developer ports a mountain of software off a platform that already owns the install base and improves itself every two quarters. He is not selling the best chip. He is renting out the largest install base in computing. The open question is whether better silicon can ever beat that, or whether the only way past a moat like this is to make the whole category obsolete.

Vikram M

367,768 次观看 • 17 天前

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA
1:48

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA

Karl Mehta

14,976 次观看 • 22 天前

Rick Rubin: "Make what you love, not what you think people will like" "If you want to live in a creative way, which will benefit everything in your life, be a better person in your family, do a better job starting a new business, it's all the same. I don't really know anything about music. It's more a way of looking at the world and wanting it to be the best it could possibly be. And doing whatever it takes to be the best it could possibly be." Rubin shares how his career happened: "From the beginning, I never thought any of the things I'm doing were possible or realistic. I just did things out of the love of them, thinking I would have real jobs. That my passion would be my hobby, and I'd have a job to support my hobby. And it just magically turned out different than that without me knowing it was possible." On why some things connect and others don't: "The stars line up at certain times for certain things to happen. Sometimes you can make something great, and it doesn't connect for whatever reason. Sometimes you make two things you think are the two best things you've ever made. One of them connects with the world. One of them doesn't. And it might not have anything to do with what's in the art. It might be that it came out the same day as something else. Or there was a bigger story at the time. There's so much to it that we don't understand." He continues: "All we can do is make something good and put it out and hope for the best. That's all there is. We never know why things work. Even if you make a piece of art and it works, you may not know why." On talent versus work ethic: "There are a lot of talented people who never make it because they don't have the work ethic. It's not just talent, talent's a piece. And you could argue for some people, the work ethic trumps the talent." Rubin explains what real collaboration is: "Having worked with a lot of bands, I see there's often this friction where people are trying to get their idea in. That's not a collaboration. A real collaboration is when everyone who's there is working together towards whatever is the best thing for the whole. Whether it's your idea or someone else's idea, it doesn't matter. If you're invested in the collaboration, you want the best idea to win. You don't want your idea to win." On what makes art great: "What makes it great is the personal. With all of its imperfections. With all of its quirkiness. That's what makes it great. How you see the world that's different from how everyone else sees the world. That's why you're an artist. That's your purpose in sharing your work with the world." He warns against being derivative: "There are these derivative voices where they're finding what they think other people want to hear, and they start saying it because they've heard other people say similar things that are now successful. Even if they have some short-term success doing that, it's not revolutionary. It doesn't change the world. It doesn't last. The people who you first see and you might not like that you come to like because you don't understand them at first, those are the ones that change the world. Those are the ones you dedicate your fandom to for life." Rubin shares his philosophy on taste: "You can't second-guess your own taste for what someone else is going to like. We're not smart enough to know what someone else is going to like. To make something thinking, 'Well, I don't really like it, but I think this group of people will like it,' it's a bad way to play the game of music or art. You have to do what's personal to you. Take it as far as you can go. Really push the boundaries. And people will resonate with it if they're supposed to resonate with it." He describes creativity as catching waves: "We're really talking about magic. The universe conspiring on our behalf if we let it. Being in this flow of catching these waves that anyone can catch. If you're trying to catch it, you're open to it, you see it coming, you take off on every chance you get. And sometimes the ride happens. It's remarkable how it happens. It doesn't come from preconception. It's not an idea. It's through the doing." Rubin explains how ideas exist in the universe: "Have you ever had that experience where you have an idea for something, you don't do it, and then six months later you see someone else has done it? It's not because they took your idea. It's that it's time for that, and you can act on it or not. The best artists are the ones who have the best antenna for this material that's available. It's coming through. The best comedians see the best jokes. They see them coming. We all live in the same world; the way you see it, you have the best joke because you see it best." He closes with how to stay open: "If we listen to what's going on around us, you can overhear a conversation in a coffee shop, and it is the setup for an idea you're working on. You hear a phrase you don't commonly use. My experience is: when you are open and looking for these clues in the world, they're happening all the time. And they're happening often right when you need them."
8:29

Rick Rubin: "Make what you love, not what you think people will like" "If you want to live in a creative way, which will benefit everything in your life, be a better person in your family, do a better job starting a new business, it's all the same. I don't really know anything about music. It's more a way of looking at the world and wanting it to be the best it could possibly be. And doing whatever it takes to be the best it could possibly be." Rubin shares how his career happened: "From the beginning, I never thought any of the things I'm doing were possible or realistic. I just did things out of the love of them, thinking I would have real jobs. That my passion would be my hobby, and I'd have a job to support my hobby. And it just magically turned out different than that without me knowing it was possible." On why some things connect and others don't: "The stars line up at certain times for certain things to happen. Sometimes you can make something great, and it doesn't connect for whatever reason. Sometimes you make two things you think are the two best things you've ever made. One of them connects with the world. One of them doesn't. And it might not have anything to do with what's in the art. It might be that it came out the same day as something else. Or there was a bigger story at the time. There's so much to it that we don't understand." He continues: "All we can do is make something good and put it out and hope for the best. That's all there is. We never know why things work. Even if you make a piece of art and it works, you may not know why." On talent versus work ethic: "There are a lot of talented people who never make it because they don't have the work ethic. It's not just talent, talent's a piece. And you could argue for some people, the work ethic trumps the talent." Rubin explains what real collaboration is: "Having worked with a lot of bands, I see there's often this friction where people are trying to get their idea in. That's not a collaboration. A real collaboration is when everyone who's there is working together towards whatever is the best thing for the whole. Whether it's your idea or someone else's idea, it doesn't matter. If you're invested in the collaboration, you want the best idea to win. You don't want your idea to win." On what makes art great: "What makes it great is the personal. With all of its imperfections. With all of its quirkiness. That's what makes it great. How you see the world that's different from how everyone else sees the world. That's why you're an artist. That's your purpose in sharing your work with the world." He warns against being derivative: "There are these derivative voices where they're finding what they think other people want to hear, and they start saying it because they've heard other people say similar things that are now successful. Even if they have some short-term success doing that, it's not revolutionary. It doesn't change the world. It doesn't last. The people who you first see and you might not like that you come to like because you don't understand them at first, those are the ones that change the world. Those are the ones you dedicate your fandom to for life." Rubin shares his philosophy on taste: "You can't second-guess your own taste for what someone else is going to like. We're not smart enough to know what someone else is going to like. To make something thinking, 'Well, I don't really like it, but I think this group of people will like it,' it's a bad way to play the game of music or art. You have to do what's personal to you. Take it as far as you can go. Really push the boundaries. And people will resonate with it if they're supposed to resonate with it." He describes creativity as catching waves: "We're really talking about magic. The universe conspiring on our behalf if we let it. Being in this flow of catching these waves that anyone can catch. If you're trying to catch it, you're open to it, you see it coming, you take off on every chance you get. And sometimes the ride happens. It's remarkable how it happens. It doesn't come from preconception. It's not an idea. It's through the doing." Rubin explains how ideas exist in the universe: "Have you ever had that experience where you have an idea for something, you don't do it, and then six months later you see someone else has done it? It's not because they took your idea. It's that it's time for that, and you can act on it or not. The best artists are the ones who have the best antenna for this material that's available. It's coming through. The best comedians see the best jokes. They see them coming. We all live in the same world; the way you see it, you have the best joke because you see it best." He closes with how to stay open: "If we listen to what's going on around us, you can overhear a conversation in a coffee shop, and it is the setup for an idea you're working on. You hear a phrase you don't commonly use. My experience is: when you are open and looking for these clues in the world, they're happening all the time. And they're happening often right when you need them."

Jaynit

109,107 次观看 • 3 个月前

The founders of Stripe and Pinterest on how to convince people to join your startup Stripe CEO Patrick Collison argues that part of the reason startups resonate so much is because the outcome is not guaranteed: "If it were guaranteed, it would be boring... Whether or not you're the best person in the world at what you do, you're probably not going to alter Google's trajectory. But if you really want to benchmark yourself and see how much of a contribution and impact you can make--which is a really compelling prospect for a lot of the best people--a startup is a much better place to test that." Pinterest founder Ben Silbermann emphasized this as well: "No smart person that you're hiring is under the illusion that you have a crystal ball into the future and that joining is a guaranteed thing. In fact, if you're telling them that and they select in, you shouldn't hire them because they didn't pass a basic intelligence test. I think it's important to tell them what's exciting and where you think the company can go. But also tell them where it will be hard and chart your best plan. And then tell them why their role can be instrumental--because it will be... What I would discourage doing is whitewashing all of that. If people are joining your company because they want all of the certainty and safety of working at Google but also the perks of working at a small startup with lots of responsibility and transparency, that's a really negative sign." Apparently in the early days of PayPal, Peter Thiel and Max Levchin would tell people after they interviewed all the reasons that the company would fail: "Visa and MasterCard want to kill us. We also might be doing something that's illegal. But if we succeed, we'll redefine payments." Don't whitewash the risks. Instead tell them how your startup will change the world if you succeed and how their role will be instrumental in affecting that change. Video source: Y Combinator (2014)
3:25

The founders of Stripe and Pinterest on how to convince people to join your startup Stripe CEO Patrick Collison argues that part of the reason startups resonate so much is because the outcome is not guaranteed: "If it were guaranteed, it would be boring... Whether or not you're the best person in the world at what you do, you're probably not going to alter Google's trajectory. But if you really want to benchmark yourself and see how much of a contribution and impact you can make--which is a really compelling prospect for a lot of the best people--a startup is a much better place to test that." Pinterest founder Ben Silbermann emphasized this as well: "No smart person that you're hiring is under the illusion that you have a crystal ball into the future and that joining is a guaranteed thing. In fact, if you're telling them that and they select in, you shouldn't hire them because they didn't pass a basic intelligence test. I think it's important to tell them what's exciting and where you think the company can go. But also tell them where it will be hard and chart your best plan. And then tell them why their role can be instrumental--because it will be... What I would discourage doing is whitewashing all of that. If people are joining your company because they want all of the certainty and safety of working at Google but also the perks of working at a small startup with lots of responsibility and transparency, that's a really negative sign." Apparently in the early days of PayPal, Peter Thiel and Max Levchin would tell people after they interviewed all the reasons that the company would fail: "Visa and MasterCard want to kill us. We also might be doing something that's illegal. But if we succeed, we'll redefine payments." Don't whitewash the risks. Instead tell them how your startup will change the world if you succeed and how their role will be instrumental in affecting that change. Video source: Y Combinator (2014)

Startup Archive

11,811 次观看 • 8 个月前

Cerebras just had the biggest IPO of the year. Founder Andrew Feldman says the 3 most important things he had to convince investors of while doing the roadshow were that demand for inference is going to 1,000,000x, the GPU isn't the only way to do compute, and that the CUDA moat is overstated. What he said: "Jensen said some time ago on Brad Gerstner's podcast that the demand for inference will grow by a 1,000,000x, and nobody believed him. And at the same time, you saw Sam Altman displaying real vision and going out and trying to lock up huge amounts of compute, memory, data centers, and power, because he saw it too." "[We tried] to share what that means — what exponential demand means. And that we're still so early, and yet the demand for AI compute is overwhelming." "The other thing is that there are lots of ways to do this. The GPU isn't the only way. You've got TPUs, Trainium, and us. There are lots of different ways to build a solution here." "And finally — the notion that CUDA is this grand lock-in is overplayed. Gemini 3, which is an excellent model, was trained on TPUs with no CUDA. The Anthropic models were trained on Trainium with no CUDA. Some of the best models, some of the most interesting things are being done without CUDA. And that lock-in might be overplayed." $CBRS
1:46

Cerebras just had the biggest IPO of the year. Founder Andrew Feldman says the 3 most important things he had to convince investors of while doing the roadshow were that demand for inference is going to 1,000,000x, the GPU isn't the only way to do compute, and that the CUDA moat is overstated. What he said: "Jensen said some time ago on Brad Gerstner's podcast that the demand for inference will grow by a 1,000,000x, and nobody believed him. And at the same time, you saw Sam Altman displaying real vision and going out and trying to lock up huge amounts of compute, memory, data centers, and power, because he saw it too." "[We tried] to share what that means — what exponential demand means. And that we're still so early, and yet the demand for AI compute is overwhelming." "The other thing is that there are lots of ways to do this. The GPU isn't the only way. You've got TPUs, Trainium, and us. There are lots of different ways to build a solution here." "And finally — the notion that CUDA is this grand lock-in is overplayed. Gemini 3, which is an excellent model, was trained on TPUs with no CUDA. The Anthropic models were trained on Trainium with no CUDA. Some of the best models, some of the most interesting things are being done without CUDA. And that lock-in might be overplayed." $CBRS

TBPN

36,474 次观看 • 2 个月前

MEET THE NVIDIA KILLER: OpenAI bet $10 BILLION on this company that makes chips 20x faster than Nvidia's. If this plays out as expected, it’s over for Nvidia. Cerebras Systems just locked in 750 megawatts of computing power to OpenAI through 2028. For reference: that's equivalent to the annual power consumption of 600,000 US homes. The deal? Over $10 billion. Here's what nobody understands: Cerebras doesn't make normal chips. Nvidia sells you thousands of tiny chips that you connect together. Cerebras makes ONE chip. A single wafer-scale processor the size of a dinner plate. 900,000 AI cores. 4 trillion transistors. All on one piece of silicon. The result? When OpenAI tested it, Cerebras ran inference 20X FASTER than Nvidia GPUs. That's not incremental improvement. That's a different category of performance. But here's where the story gets wild: Four months ago, Cerebras was a struggling company. Their IPO filing revealed that 87% of their revenue came from ONE customer: G42, a UAE-based AI firm. The US government launched a national security review. G42 had ties to Huawei. Ties to China. The IPO collapsed. Investors panicked. Cerebras withdrew their filing in October 2025. Most startups would've been dead. Instead, Cerebras did the opposite. They raised $1.1 billion at an $8.1 billion valuation. Kicked G42 out of the cap table entirely. Got CFIUS clearance. Then landed the OpenAI deal. Now they're raising ANOTHER $1 billion at a $22 billion valuation. They more than DOUBLED their valuation in 4 months. From near-death to $22 billion. While getting rid of their biggest customer. Why OpenAI chose them: ChatGPT has 900 million weekly users. Sam Altman keeps saying they have a "severe shortage" of compute. They need SPEED, not just power. When you ask ChatGPT a question, there's a loop happening: You send request → model thinks → sends response back Nvidia chips are fast at training models. Cerebras chips are built specifically for inference. For real-time responses. For the exact bottleneck OpenAI is trying to solve. Sachin Katti from OpenAI said it best: "Cerebras adds a dedicated low-latency inference solution to our platform. That means faster responses, more natural interactions, and a stronger foundation to scale real-time AI to many more people." In other words: "We need this to scale ChatGPT." The competitive landscape just shifted: Nvidia announced a $100 billion deal with OpenAI in September. But it's still not finalized. Meanwhile, Cerebras closed their deal before Thanksgiving. And it's ALREADY being deployed. Here's the part that should terrify Nvidia: In December, Nvidia bought Groq for $20 billion. Groq makes fast inference chips. Just like Cerebras. So why would Nvidia spend $20 billion buying a competitor to something they supposedly already dominate? Because they know what's coming. Inference is the new battleground. And Cerebras is winning it. The IPO is coming Q2 2026. After this OpenAI deal, Cerebras now has: ✓ IBM contracts ✓ Department of Energy contracts ✓ OpenAI locked in for 3 years ✓ $22 billion valuation ✓ CFIUS clearance ✓ Zero customer concentration risk They went from 87% revenue dependency on one customer to the most diversified chip company outside Nvidia. In four months. The lesson? Smart money doesn't follow headlines. It follows where the AI leaders are actually spending. OpenAI didn't announce this deal for publicity. They need Cerebras hardware to scale ChatGPT. That's a $10 billion vote of confidence. While everyone's watching Nvidia stock, the real war is happening in inference. And the company with ONE giant chip just beat the company with thousands of tiny ones. What do you think happens when Cerebras IPOs?
1:03

MEET THE NVIDIA KILLER: OpenAI bet $10 BILLION on this company that makes chips 20x faster than Nvidia's. If this plays out as expected, it’s over for Nvidia. Cerebras Systems just locked in 750 megawatts of computing power to OpenAI through 2028. For reference: that's equivalent to the annual power consumption of 600,000 US homes. The deal? Over $10 billion. Here's what nobody understands: Cerebras doesn't make normal chips. Nvidia sells you thousands of tiny chips that you connect together. Cerebras makes ONE chip. A single wafer-scale processor the size of a dinner plate. 900,000 AI cores. 4 trillion transistors. All on one piece of silicon. The result? When OpenAI tested it, Cerebras ran inference 20X FASTER than Nvidia GPUs. That's not incremental improvement. That's a different category of performance. But here's where the story gets wild: Four months ago, Cerebras was a struggling company. Their IPO filing revealed that 87% of their revenue came from ONE customer: G42, a UAE-based AI firm. The US government launched a national security review. G42 had ties to Huawei. Ties to China. The IPO collapsed. Investors panicked. Cerebras withdrew their filing in October 2025. Most startups would've been dead. Instead, Cerebras did the opposite. They raised $1.1 billion at an $8.1 billion valuation. Kicked G42 out of the cap table entirely. Got CFIUS clearance. Then landed the OpenAI deal. Now they're raising ANOTHER $1 billion at a $22 billion valuation. They more than DOUBLED their valuation in 4 months. From near-death to $22 billion. While getting rid of their biggest customer. Why OpenAI chose them: ChatGPT has 900 million weekly users. Sam Altman keeps saying they have a "severe shortage" of compute. They need SPEED, not just power. When you ask ChatGPT a question, there's a loop happening: You send request → model thinks → sends response back Nvidia chips are fast at training models. Cerebras chips are built specifically for inference. For real-time responses. For the exact bottleneck OpenAI is trying to solve. Sachin Katti from OpenAI said it best: "Cerebras adds a dedicated low-latency inference solution to our platform. That means faster responses, more natural interactions, and a stronger foundation to scale real-time AI to many more people." In other words: "We need this to scale ChatGPT." The competitive landscape just shifted: Nvidia announced a $100 billion deal with OpenAI in September. But it's still not finalized. Meanwhile, Cerebras closed their deal before Thanksgiving. And it's ALREADY being deployed. Here's the part that should terrify Nvidia: In December, Nvidia bought Groq for $20 billion. Groq makes fast inference chips. Just like Cerebras. So why would Nvidia spend $20 billion buying a competitor to something they supposedly already dominate? Because they know what's coming. Inference is the new battleground. And Cerebras is winning it. The IPO is coming Q2 2026. After this OpenAI deal, Cerebras now has: ✓ IBM contracts ✓ Department of Energy contracts ✓ OpenAI locked in for 3 years ✓ $22 billion valuation ✓ CFIUS clearance ✓ Zero customer concentration risk They went from 87% revenue dependency on one customer to the most diversified chip company outside Nvidia. In four months. The lesson? Smart money doesn't follow headlines. It follows where the AI leaders are actually spending. OpenAI didn't announce this deal for publicity. They need Cerebras hardware to scale ChatGPT. That's a $10 billion vote of confidence. While everyone's watching Nvidia stock, the real war is happening in inference. And the company with ONE giant chip just beat the company with thousands of tiny ones. What do you think happens when Cerebras IPOs?

Ricardo

28,088 次观看 • 6 个月前

Nvidia just made its biggest acquisition ever... A small startup. On Christmas Eve. While everyone was distracted. The startup is Groq. They make AI chips that run faster than Nvidia's. In September, Groq raised $750 million at a $6.9 billion valuation. Investors included BlackRock, Samsung, Cisco, and Donald Trump Jr.'s fund 1789 Capital. Yesterday, Nvidia paid $20 billion for them. That's a 3x markup in 90 days. Trump Jr. just made a fortune overnight. But the money isn't even the craziest part... Nvidia dominates AI chips. They have 90%+ market share. All of big tech depends on them. So why would they pay 3X for a tiny competitor? Let me explain: Groq was building inference chips that threatened Nvidia's monopoly. Faster processing. Lower costs. Better architecture. If Groq succeeded, they'd crack open the market. So Nvidia did what monopolies always do: bought them before they became a threat. They're buying silence - not innovation. And this isn't a one-off. In September, Nvidia spent $900 million on Enfabrica, another AI chip startup. Same playbook. They committed $100 billion to OpenAI with a requirement that OpenAI deploy 10 gigawatts of Nvidia products. Now $20 billion for Groq. Nvidia isn't competing anymore. They're consolidating. They're using their cash pile to swallow every potential rival before they grow. The founder and CEO of Groq, Jonathan Ross, is joining Nvidia. So is the president and the entire leadership team. Groq's cloud business will keep running independently. But the tech, the IP, the competitive advantage? All Nvidia's now. This is the largest acquisition Nvidia has EVER made. Their previous record was $7 billion for Mellanox in 2019. They just tripled that. And nobody's questioning why. Everyone's celebrating "innovation" and "consolidation" and "strategic partnerships." But what actually happened is this: Nvidia looked at the one company that could challenge their monopoly and paid whatever it took to kill them. $20 billion is cheap insurance when you're worth trillions. The only question left is who's next.
0:35

Nvidia just made its biggest acquisition ever... A small startup. On Christmas Eve. While everyone was distracted. The startup is Groq. They make AI chips that run faster than Nvidia's. In September, Groq raised $750 million at a $6.9 billion valuation. Investors included BlackRock, Samsung, Cisco, and Donald Trump Jr.'s fund 1789 Capital. Yesterday, Nvidia paid $20 billion for them. That's a 3x markup in 90 days. Trump Jr. just made a fortune overnight. But the money isn't even the craziest part... Nvidia dominates AI chips. They have 90%+ market share. All of big tech depends on them. So why would they pay 3X for a tiny competitor? Let me explain: Groq was building inference chips that threatened Nvidia's monopoly. Faster processing. Lower costs. Better architecture. If Groq succeeded, they'd crack open the market. So Nvidia did what monopolies always do: bought them before they became a threat. They're buying silence - not innovation. And this isn't a one-off. In September, Nvidia spent $900 million on Enfabrica, another AI chip startup. Same playbook. They committed $100 billion to OpenAI with a requirement that OpenAI deploy 10 gigawatts of Nvidia products. Now $20 billion for Groq. Nvidia isn't competing anymore. They're consolidating. They're using their cash pile to swallow every potential rival before they grow. The founder and CEO of Groq, Jonathan Ross, is joining Nvidia. So is the president and the entire leadership team. Groq's cloud business will keep running independently. But the tech, the IP, the competitive advantage? All Nvidia's now. This is the largest acquisition Nvidia has EVER made. Their previous record was $7 billion for Mellanox in 2019. They just tripled that. And nobody's questioning why. Everyone's celebrating "innovation" and "consolidation" and "strategic partnerships." But what actually happened is this: Nvidia looked at the one company that could challenge their monopoly and paid whatever it took to kill them. $20 billion is cheap insurance when you're worth trillions. The only question left is who's next.

Ricardo

224,264 次观看 • 7 个月前

Q: What's the secret to building a great product that grows really fast? Paul Graham explains that the secret to growing really fast is to: "start with a small, intense fire." He uses Apple as an example. They started by selling just 500 Apple I computers. Today Apple is the largest company in the world. It's impossible to make something that a large number of people really want when you're just starting out. So you have to find people who want what you're building A LOT. And that's necessarily going to be a small number at first. But that's ok because that's how almost every giant company gets started. PG continues: "You have to know who those first users are and how you're going to get them. Then you're going to sit down and just have a party with those first few users and focus entirely on them and making them super super happy." Another example he draws upon is a startup in a Y Combinator batch making a new mobile email client. Their beta group had one user: Sam Altman. This startup's goal was to just make Sam happy. Sam uses email a lot on the go, knows all of the other email client options, and is super demanding. So they know that if they build a product that makes Sam happy, odds are it will make lots of other people happy too. "One of the things we tell startups in these extreme cases where they can make just one user happy is to act like a consultant. Act like Sam has hired you to make an email app just for him. All you have to do is make Sam happy--it can say 'Sam Altman' at the top of the screen. That's ok! Just so long as Sam would feel bummed if you stopped working on it. That's the test." Ultimately the secret to building a great product that grows really fast is to build something a small group of people love so much that they'd be really disappointed if you stopped working on it. There's lots of important steps to get right after this, but this is the foundation for growth. It's somewhat counterintuitive, but most of the world's largest companies (e.g. Apple, Facebook, etc.) started by building a product that made a small group of people really happy.
2:29

Q: What's the secret to building a great product that grows really fast? Paul Graham explains that the secret to growing really fast is to: "start with a small, intense fire." He uses Apple as an example. They started by selling just 500 Apple I computers. Today Apple is the largest company in the world. It's impossible to make something that a large number of people really want when you're just starting out. So you have to find people who want what you're building A LOT. And that's necessarily going to be a small number at first. But that's ok because that's how almost every giant company gets started. PG continues: "You have to know who those first users are and how you're going to get them. Then you're going to sit down and just have a party with those first few users and focus entirely on them and making them super super happy." Another example he draws upon is a startup in a Y Combinator batch making a new mobile email client. Their beta group had one user: Sam Altman. This startup's goal was to just make Sam happy. Sam uses email a lot on the go, knows all of the other email client options, and is super demanding. So they know that if they build a product that makes Sam happy, odds are it will make lots of other people happy too. "One of the things we tell startups in these extreme cases where they can make just one user happy is to act like a consultant. Act like Sam has hired you to make an email app just for him. All you have to do is make Sam happy--it can say 'Sam Altman' at the top of the screen. That's ok! Just so long as Sam would feel bummed if you stopped working on it. That's the test." Ultimately the secret to building a great product that grows really fast is to build something a small group of people love so much that they'd be really disappointed if you stopped working on it. There's lots of important steps to get right after this, but this is the foundation for growth. It's somewhat counterintuitive, but most of the world's largest companies (e.g. Apple, Facebook, etc.) started by building a product that made a small group of people really happy.

Michael McGuiness

890,425 次观看 • 3 年前

"Every former Nvidia employee that goes to a large tech company like Google and MSFT says it's extremely difficult to adjust to the culture, Nvidia is faster but the work ethic is on a different level" 3dfx was the No 1 graphics company in the mid-to-late 90s, their main competitor Nvidia beat them and essentially destroyed them - acquired their assets and hired 100 of their engineers. The 3dfx engineers kept looking for Nvidia's secret or magic trick, but it turned out the only secret was relentless execution & working crazy hard. This culture obviously stems from the CEO, Jensen - who loves to work on Sunday nights & finds it relaxing. Jensen is constantly focused on cultivating talent - he rewards highly performing engineers by doubling or tripling their stock compensation. To avoid the internal politics that plague large organizations (where projects get stuck in quicksand needing multiple approvals), Jensen made the organization flat. Every time they need to make decisions, he brings together top 10-15 people, including lower-level employees, to hash out the main problems in an intellectually honest way and execute quickly - what they call "speed of light" at Nvidia.
2:38

"Every former Nvidia employee that goes to a large tech company like Google and MSFT says it's extremely difficult to adjust to the culture, Nvidia is faster but the work ethic is on a different level" 3dfx was the No 1 graphics company in the mid-to-late 90s, their main competitor Nvidia beat them and essentially destroyed them - acquired their assets and hired 100 of their engineers. The 3dfx engineers kept looking for Nvidia's secret or magic trick, but it turned out the only secret was relentless execution & working crazy hard. This culture obviously stems from the CEO, Jensen - who loves to work on Sunday nights & finds it relaxing. Jensen is constantly focused on cultivating talent - he rewards highly performing engineers by doubling or tripling their stock compensation. To avoid the internal politics that plague large organizations (where projects get stuck in quicksand needing multiple approvals), Jensen made the organization flat. Every time they need to make decisions, he brings together top 10-15 people, including lower-level employees, to hash out the main problems in an intellectually honest way and execute quickly - what they call "speed of light" at Nvidia.

Aish

692,715 次观看 • 1 年前

Amplitude CEO Spenser Skates says the SaaSpocalypse is real, and your old moat is dead. The only moat now is speed of innovation: "You have to be pushing the bleeding edge of what capabilities are. If you create a company that can do that, that's what customers will buy." "What the SaaSpocalypse has gotten right is - if you look at the median SaaS company, their innovation has actually slowed to a standstill." "It's crazy how little they ship in terms of net new products." "Speed of using the bleeding edge of these model capabilities is all that matters. You're even seeing it in the foundational model companies. Opus was the hottest thing a week ago, then it Codex literally launched the same day, saying, 'We're even better, and we're faster and we're on Cerebras chips.' I think all that matters is the rate of improvement." "It's like sushi. Buyers are always going to want the best thing. So if you're keeping up with innovating the best thing, you will be able to charge a premium. It's fine that the 7/11 gas station now sells sushi. It's not going to put Jiro in Japan out of business." "The lesson is - there is no moat anymore from what we've built. There's only a moat if we're able to deliver the most bleeding edge capability."
2:07

Amplitude CEO Spenser Skates says the SaaSpocalypse is real, and your old moat is dead. The only moat now is speed of innovation: "You have to be pushing the bleeding edge of what capabilities are. If you create a company that can do that, that's what customers will buy." "What the SaaSpocalypse has gotten right is - if you look at the median SaaS company, their innovation has actually slowed to a standstill." "It's crazy how little they ship in terms of net new products." "Speed of using the bleeding edge of these model capabilities is all that matters. You're even seeing it in the foundational model companies. Opus was the hottest thing a week ago, then it Codex literally launched the same day, saying, 'We're even better, and we're faster and we're on Cerebras chips.' I think all that matters is the rate of improvement." "It's like sushi. Buyers are always going to want the best thing. So if you're keeping up with innovating the best thing, you will be able to charge a premium. It's fine that the 7/11 gas station now sells sushi. It's not going to put Jiro in Japan out of business." "The lesson is - there is no moat anymore from what we've built. There's only a moat if we're able to deliver the most bleeding edge capability."

TBPN

95,450 次观看 • 5 个月前

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.
1:01

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.

Ricardo

159,113 次观看 • 2 个月前

J-Cal: Nvidia is taking the gloves off with its open source model. They will own the whole stack. “You will not be able to tell the difference between Jensen Huang's open source LLM and Claude for 95% of your searches, I guarantee you. Now, why has Nvidia and Jensen downplayed their open source model until this moment? Why would he do that? Why would he never bring it up in the All-In interview, never bring it up? Because his top customers (OpenAI, Anthropic, etc.) were very concerned, from what I understand, about the fact that Nvidia had made so much progress on their open source model. But suddenly, after OpenAI announced their Jalapeno chips, after Anthropic started making chips, after AMD did successful projects with both of these companies, after Elon said he's going to do his own fab, Nvidia's taking the gloves off. They are going to own the whole stack. You get the hardware from them, and you're going to get a model that's competitive with OpenAI's for free.”
0:54

J-Cal: Nvidia is taking the gloves off with its open source model. They will own the whole stack. “You will not be able to tell the difference between Jensen Huang's open source LLM and Claude for 95% of your searches, I guarantee you. Now, why has Nvidia and Jensen downplayed their open source model until this moment? Why would he do that? Why would he never bring it up in the All-In interview, never bring it up? Because his top customers (OpenAI, Anthropic, etc.) were very concerned, from what I understand, about the fact that Nvidia had made so much progress on their open source model. But suddenly, after OpenAI announced their Jalapeno chips, after Anthropic started making chips, after AMD did successful projects with both of these companies, after Elon said he's going to do his own fab, Nvidia's taking the gloves off. They are going to own the whole stack. You get the hardware from them, and you're going to get a model that's competitive with OpenAI's for free.”

The All-In Podcast

226,773 次观看 • 22 天前

Chamath: US AI Startups Can Learn A Lot from DeepSeek "This is a case where necessity was the mother of invention." On E213, Chamath Palihapitiya explained how, even if the $6M number is inaccurate, DeepSeek still had some impressive breakthroughs: GRPO > PPO for reinforcement learning "These guys were like, 'Well, how am I going to do this reinforcement learning thing?' They invented a totally different algorithm." "It uses a lot less computer memory and it's highly performant." PTX > CUDA to build the model "And then the second thing that was crazy is everybody is used to building models and compiling through CUDA, which is NVIDIA's proprietary language." "And these guys worked totally around CUDA and they did something called PTX, which goes right to the bare metal." What US AI startups can learn from this: "We, meaning the West, with all the money that we've had, didn't come up with these ideas." "And I think part of why we didn't come up is not that we're not smart enough to do it, but we weren't forced to because the constraints didn't exist." "And so I just wonder how we make sure we learn this principle, meaning, when the AI company wakes up and rolls out of bed and some VC gives them $200M, maybe that's not the right answer for a Series A or a Seed." "And maybe the right answer is $2M so that they do these DeepSeek-like innovations."
0:55

Chamath: US AI Startups Can Learn A Lot from DeepSeek "This is a case where necessity was the mother of invention." On E213, Chamath Palihapitiya explained how, even if the $6M number is inaccurate, DeepSeek still had some impressive breakthroughs: GRPO > PPO for reinforcement learning "These guys were like, 'Well, how am I going to do this reinforcement learning thing?' They invented a totally different algorithm." "It uses a lot less computer memory and it's highly performant." PTX > CUDA to build the model "And then the second thing that was crazy is everybody is used to building models and compiling through CUDA, which is NVIDIA's proprietary language." "And these guys worked totally around CUDA and they did something called PTX, which goes right to the bare metal." What US AI startups can learn from this: "We, meaning the West, with all the money that we've had, didn't come up with these ideas." "And I think part of why we didn't come up is not that we're not smart enough to do it, but we weren't forced to because the constraints didn't exist." "And so I just wonder how we make sure we learn this principle, meaning, when the AI company wakes up and rolls out of bed and some VC gives them $200M, maybe that's not the right answer for a Series A or a Seed." "And maybe the right answer is $2M so that they do these DeepSeek-like innovations."

The All-In Podcast

108,815 次观看 • 1 年前

Brian still spends over two hours a day on recruiting and personally hires the top 200 people at Airbnb. I loved this idea of being in the flow of talent to find the best people: "Don't do searches. Build pipelines. I try to map out all the best people in the Valley. So let's say I need to hire really good engineers. I don't do searches. I just informationally meet the best engineers in the world. Every meeting, the job is to get the next meeting, meet someone else. The mistake people make when they hire. They go, "I need to hire a blank." So they hire a search firm. They give you 50 profiles, and you pick the best one. That is the wrong way to do it. The best way to do it is pipeline recruiting. You're constantly recruiting, you're constantly meeting people. in advance of searches. And all of it is referral based. The two ways to find out if people are good – is to start with the results and work backwards to the people. Find an ad you like and figure out who made that ad. Start with the results. Work backwards to people. Don't start with the resume. The other thing to do is just keep asking people to build your Rolodex. The moment I find somebody that's really good, I ask them who all the best people they know are. And I build these little mafias and they tell you who the other good people are. I am the co-hiring manager for the top 200 people in the company. This is very radical. A lot of CEOs think it's their job to hire their executive team, and their executive team hires their team. I think that is fatal. You always want to be marrying up, hiring people of the future. It should be like we're reaching. If you can hire them without my help, we're not reaching far enough. You want to hire the very best person you can."
2:07

Brian still spends over two hours a day on recruiting and personally hires the top 200 people at Airbnb. I loved this idea of being in the flow of talent to find the best people: "Don't do searches. Build pipelines. I try to map out all the best people in the Valley. So let's say I need to hire really good engineers. I don't do searches. I just informationally meet the best engineers in the world. Every meeting, the job is to get the next meeting, meet someone else. The mistake people make when they hire. They go, "I need to hire a blank." So they hire a search firm. They give you 50 profiles, and you pick the best one. That is the wrong way to do it. The best way to do it is pipeline recruiting. You're constantly recruiting, you're constantly meeting people. in advance of searches. And all of it is referral based. The two ways to find out if people are good – is to start with the results and work backwards to the people. Find an ad you like and figure out who made that ad. Start with the results. Work backwards to people. Don't start with the resume. The other thing to do is just keep asking people to build your Rolodex. The moment I find somebody that's really good, I ask them who all the best people they know are. And I build these little mafias and they tell you who the other good people are. I am the co-hiring manager for the top 200 people in the company. This is very radical. A lot of CEOs think it's their job to hire their executive team, and their executive team hires their team. I think that is fatal. You always want to be marrying up, hiring people of the future. It should be like we're reaching. If you can hire them without my help, we're not reaching far enough. You want to hire the very best person you can."

Patrick OShaughnessy

316,842 次观看 • 2 个月前

🚨 Do you understand what you're looking at right now? $1,000,000,000,000. Count the zeros. Twelve. That's not a company's valuation. That's not a market cap... That's ONE MAN'S revenue prediction. For selling chips.. > Jensen Huang just said Nvidia will make $1 trillion from AI chips by 2027.. One trillion dollars. From one product. In one industry. That didn't exist 3 years ago.. > Every company fighting the AI war - OpenAI, Google, Meta, Amazon, xAI - is buying their weapons from the same arms dealer.. > Nvidia doesn't care who wins. They sell bullets to every side. > DeepSeek wiped $600B off Nvidia in January.. Jensen recovered in two weeks and just came back asking for a trillion.. This man doesn't flinch. The entire AI revolution has one chokepoint. One company. One man. One leather jacket. And he just named his price.
0:31

🚨 Do you understand what you're looking at right now? $1,000,000,000,000. Count the zeros. Twelve. That's not a company's valuation. That's not a market cap... That's ONE MAN'S revenue prediction. For selling chips.. > Jensen Huang just said Nvidia will make $1 trillion from AI chips by 2027.. One trillion dollars. From one product. In one industry. That didn't exist 3 years ago.. > Every company fighting the AI war - OpenAI, Google, Meta, Amazon, xAI - is buying their weapons from the same arms dealer.. > Nvidia doesn't care who wins. They sell bullets to every side. > DeepSeek wiped $600B off Nvidia in January.. Jensen recovered in two weeks and just came back asking for a trillion.. This man doesn't flinch. The entire AI revolution has one chokepoint. One company. One man. One leather jacket. And he just named his price.

Tuki

81,840 次观看 • 4 个月前

Rick Rubin: "I've met very few billionaires who are happy" "I don't look at the outside very much. I look inward. I try to focus on what do I feel, what am I seeing, in the hopes that by sharing what's going on in me, it resonates with someone else. I can't predict what someone else would like. And I don't think anybody can. So if I'm authentically true to myself, that's the best chance of someone else liking something." Rubin explains the paradox of acceptance: "People want to be accepted. And I'm suggesting that the best way to be accepted is to be yourself. It's not to change yourself to what someone else thinks. First of all, you don't really know what someone else thinks. And if you're not genuine to yourself, nothing is there. It's just a projection or a mask. It's not true." On what makes something interesting: "In a sea of information, the more yours is personal, the more it's not like hers or his or theirs, the more it's yours. If we're all thinking the same thing, it's boring. Why would we make anything if everyone thinks the same thing? What makes us interesting are the differences. Even the imperfections. The imperfections are what make us human." Rubin shares what captures his attention: "There's so much middle of the road, and it doesn't interest me. I want it because it's louder, quieter, softer, harder. It's pushing some boundary. That's why I take notice. It's not more of the same. It's the one that makes you stop and think: did I really hear that? Did I really see that? What's going on here?" On what success actually means: "If I like it, that doesn't mean anything. That's what people think. Just because I like it doesn't give it any value. But as an artist, if you like it, that's all of the value. That's the success. It comes when you say, 'I like this enough for other people to see it.' Not 'other people like it, so it's successful.' That doesn't mean anything. Because other people liking it is out of your control. All that's in your control is making the thing to the best of your ability." Rubin reframes what greatness means: "I came to realize recently, it's all an offering to God. And if you're making an offering to God, you're not thinking about the budget, or hoping this segment of the audience is going to like it. We don't think like that. It's a higher vibration. We're making the best we can make, to the best of our ability, out of love and devotion. That's what it is. There is no higher form." On criticism and reviews: "Most of the artists I work with don't read any criticism or reviews, good or bad. The ones who are the strongest in who they are can even read a terrible review and laugh at it. Because when someone gives you criticism, it's telling you as much about who they are as what you've made." Rubin explains the only real competition: "The idea of the Oscars or the Grammys, where we're saying which album is better than another, it doesn't make any sense to me. Because it's always apples and oranges. The only people we can honestly compete with is ourselves. Is this the best I can make today? Have I gone further than I've gone before? That's all we can do. That's the only competition that makes sense." On the obsession required for mastery: "Many of the artists that are great at what they do are great for one reason: they fall in love with this thing, and they just want to know everything they could possibly learn about it. I'm working on a documentary project with comedians now. One of the things they talk about is their commitment; when other people are going out on the weekend, they're going to perform every night they possibly can. For a period of 10 years. Having bad performances. Having people not like what they do. Banging their head against the wall. But that obsession with breaking through, and when I say breaking through, I don't mean to the audience. I mean with themselves." Rubin shares a hard truth about dreams and jobs: "Maybe your purpose in life isn't related to your job. Maybe your job is your job, and the job is the thing that supports you. And then the rest of your waking hours are devoted to your purpose. Don't let following your dreams undermine your ability to support yourself. If you decide 'I want to be a comedian and I'm putting all my eggs in the comedian basket', the pressure of having to support yourself will change you as a comedian. Not for the better. You want the stability of being able to take care of yourself in the world to be free to do whatever your passion is." He challenges the mythology of genius: "There's a mythology that the people who make things that we love are special people, the people on Mount Olympus, magic people who are geniuses. And then there's the rest of us. That's not the case. We're all just people. We're all doing our best. We're all good at some things, not good at other things. We're humans. And sometimes we find a way to make something beautiful." Rubin shares his most vulnerable moment: "The call came: 'How do you feel? You have the number one album in the country.' And I remember saying, 'I've never been more unhappy in my life.' We mistakenly think some kind of outward success is going to change something in us. And it does not. It may make life more comfortable. But it doesn't change who we are. Any hole in ourselves that we're hoping to fill does not get filled." He explains why successful people are often unhappy: "If you spend 20 years of your life working towards a goal that's going to solve everything, and then you finally achieve what you've been trying to do for 20 years, and nothing changes, that's when you get hopeless. It's not uncommon to see very successful artists who are very unhappy. I'm sure you've met many very successful business people. Billionaires. Very few of them are happy. Very few. They've accomplished their dreams and are unhappy. Because we don't know what we want. We're trying to fill something that maybe can't be filled through material or public success. It's something else. Some internal thing." Rubin closes with this: "Don't do things just because you think you're going to get something for it. That's not why we do things. Do what's interesting to you. Follow what's interesting. Don't worry about the outcome. We can never predict the outcome. Follow your own inner guide. It might not make sense to anyone else. It might not even make sense to us. And that's okay. The wisest thing we can do is know enough to know we don't know. Anytime you think 'I know how it is' your world just got a lot smaller."
12:19

Rick Rubin: "I've met very few billionaires who are happy" "I don't look at the outside very much. I look inward. I try to focus on what do I feel, what am I seeing, in the hopes that by sharing what's going on in me, it resonates with someone else. I can't predict what someone else would like. And I don't think anybody can. So if I'm authentically true to myself, that's the best chance of someone else liking something." Rubin explains the paradox of acceptance: "People want to be accepted. And I'm suggesting that the best way to be accepted is to be yourself. It's not to change yourself to what someone else thinks. First of all, you don't really know what someone else thinks. And if you're not genuine to yourself, nothing is there. It's just a projection or a mask. It's not true." On what makes something interesting: "In a sea of information, the more yours is personal, the more it's not like hers or his or theirs, the more it's yours. If we're all thinking the same thing, it's boring. Why would we make anything if everyone thinks the same thing? What makes us interesting are the differences. Even the imperfections. The imperfections are what make us human." Rubin shares what captures his attention: "There's so much middle of the road, and it doesn't interest me. I want it because it's louder, quieter, softer, harder. It's pushing some boundary. That's why I take notice. It's not more of the same. It's the one that makes you stop and think: did I really hear that? Did I really see that? What's going on here?" On what success actually means: "If I like it, that doesn't mean anything. That's what people think. Just because I like it doesn't give it any value. But as an artist, if you like it, that's all of the value. That's the success. It comes when you say, 'I like this enough for other people to see it.' Not 'other people like it, so it's successful.' That doesn't mean anything. Because other people liking it is out of your control. All that's in your control is making the thing to the best of your ability." Rubin reframes what greatness means: "I came to realize recently, it's all an offering to God. And if you're making an offering to God, you're not thinking about the budget, or hoping this segment of the audience is going to like it. We don't think like that. It's a higher vibration. We're making the best we can make, to the best of our ability, out of love and devotion. That's what it is. There is no higher form." On criticism and reviews: "Most of the artists I work with don't read any criticism or reviews, good or bad. The ones who are the strongest in who they are can even read a terrible review and laugh at it. Because when someone gives you criticism, it's telling you as much about who they are as what you've made." Rubin explains the only real competition: "The idea of the Oscars or the Grammys, where we're saying which album is better than another, it doesn't make any sense to me. Because it's always apples and oranges. The only people we can honestly compete with is ourselves. Is this the best I can make today? Have I gone further than I've gone before? That's all we can do. That's the only competition that makes sense." On the obsession required for mastery: "Many of the artists that are great at what they do are great for one reason: they fall in love with this thing, and they just want to know everything they could possibly learn about it. I'm working on a documentary project with comedians now. One of the things they talk about is their commitment; when other people are going out on the weekend, they're going to perform every night they possibly can. For a period of 10 years. Having bad performances. Having people not like what they do. Banging their head against the wall. But that obsession with breaking through, and when I say breaking through, I don't mean to the audience. I mean with themselves." Rubin shares a hard truth about dreams and jobs: "Maybe your purpose in life isn't related to your job. Maybe your job is your job, and the job is the thing that supports you. And then the rest of your waking hours are devoted to your purpose. Don't let following your dreams undermine your ability to support yourself. If you decide 'I want to be a comedian and I'm putting all my eggs in the comedian basket', the pressure of having to support yourself will change you as a comedian. Not for the better. You want the stability of being able to take care of yourself in the world to be free to do whatever your passion is." He challenges the mythology of genius: "There's a mythology that the people who make things that we love are special people, the people on Mount Olympus, magic people who are geniuses. And then there's the rest of us. That's not the case. We're all just people. We're all doing our best. We're all good at some things, not good at other things. We're humans. And sometimes we find a way to make something beautiful." Rubin shares his most vulnerable moment: "The call came: 'How do you feel? You have the number one album in the country.' And I remember saying, 'I've never been more unhappy in my life.' We mistakenly think some kind of outward success is going to change something in us. And it does not. It may make life more comfortable. But it doesn't change who we are. Any hole in ourselves that we're hoping to fill does not get filled." He explains why successful people are often unhappy: "If you spend 20 years of your life working towards a goal that's going to solve everything, and then you finally achieve what you've been trying to do for 20 years, and nothing changes, that's when you get hopeless. It's not uncommon to see very successful artists who are very unhappy. I'm sure you've met many very successful business people. Billionaires. Very few of them are happy. Very few. They've accomplished their dreams and are unhappy. Because we don't know what we want. We're trying to fill something that maybe can't be filled through material or public success. It's something else. Some internal thing." Rubin closes with this: "Don't do things just because you think you're going to get something for it. That's not why we do things. Do what's interesting to you. Follow what's interesting. Don't worry about the outcome. We can never predict the outcome. Follow your own inner guide. It might not make sense to anyone else. It might not even make sense to us. And that's okay. The wisest thing we can do is know enough to know we don't know. Anytime you think 'I know how it is' your world just got a lot smaller."

Jaynit

152,885 次观看 • 3 个月前

Google's recent Gemini 3 release has shocked the world with undeniable proof that the TPU is a powerhouse AI chip, leaving many to wonder what lays in store for companies like NVIDIA & xAI. Listen to Gavin Baker lay out the exact strategy that Jensen Huang & Elon Musk are going to roll out over the next 12 months to beat Google at AI. The world is in for a HUGE surprise. ---------- We'll see the first models trained on Blackwell in early 2026. I think the first Blackwell model will come from XAI. And the reason for that is just, according to Jensen, no one builds data centers faster than Elon. Jensen has said this on the record. ... So if you're Jensen or Nvidia, you need to get as many GPUs deployed in one data center as fast as possible in a coherent cluster so you can work out the bugs. And so this is what X AI effectively does for Nvidia because they build the data centers the fastest. They can deploy Blackwells that scale the fastest, and they can help work with Nvidia to work out the bugs for everyone else. So because they're the fastest, they will, they'll have the first Blackwell model. ... We know that these Blackwell models are gonna be really good. ... Then something even more important happens. So the GB 200 was really, really, it was really hard to get it going. The GB 300 is a great chip. It is drop in compatible in every way with those GB 200 racks. Now you're not gonna replace the GB 200s there. Just any data center that can handle those, you can slot in the GB 300s, and now everybody's good at making those racks and you know how to get the heat out. You know how to cool them. You're gonna put those GB 300s in and then the companies that use the GB 300s, they're going to be the low cost producer of tokens. Particularly if you're vertically integrated. If you're paying a margin to someone else to make those tokens, you're probably not gonna be. I think this has pretty profound implications because I think it has to change Google's strategic calculus. ---------- Listen to the full conversation between Gavin & Patrick OShaughnessy below 👇
6:23

Google's recent Gemini 3 release has shocked the world with undeniable proof that the TPU is a powerhouse AI chip, leaving many to wonder what lays in store for companies like NVIDIA & xAI. Listen to Gavin Baker lay out the exact strategy that Jensen Huang & Elon Musk are going to roll out over the next 12 months to beat Google at AI. The world is in for a HUGE surprise. ---------- We'll see the first models trained on Blackwell in early 2026. I think the first Blackwell model will come from XAI. And the reason for that is just, according to Jensen, no one builds data centers faster than Elon. Jensen has said this on the record. ... So if you're Jensen or Nvidia, you need to get as many GPUs deployed in one data center as fast as possible in a coherent cluster so you can work out the bugs. And so this is what X AI effectively does for Nvidia because they build the data centers the fastest. They can deploy Blackwells that scale the fastest, and they can help work with Nvidia to work out the bugs for everyone else. So because they're the fastest, they will, they'll have the first Blackwell model. ... We know that these Blackwell models are gonna be really good. ... Then something even more important happens. So the GB 200 was really, really, it was really hard to get it going. The GB 300 is a great chip. It is drop in compatible in every way with those GB 200 racks. Now you're not gonna replace the GB 200s there. Just any data center that can handle those, you can slot in the GB 300s, and now everybody's good at making those racks and you know how to get the heat out. You know how to cool them. You're gonna put those GB 300s in and then the companies that use the GB 300s, they're going to be the low cost producer of tokens. Particularly if you're vertically integrated. If you're paying a margin to someone else to make those tokens, you're probably not gonna be. I think this has pretty profound implications because I think it has to change Google's strategic calculus. ---------- Listen to the full conversation between Gavin & Patrick OShaughnessy below 👇

Hans C Nelson 🗽

5,010,626 次观看 • 7 个月前

Peter Thiel: "Competition is for losers" "Competition is for losers, which got people's attention, because we normally believe the opposite. We believe that the losers are the people who don't compete intensely enough. You're a loser if you're not competitive. But what if you're a loser because you're too obsessed with competing? If you're too focused on competing, maybe you're losing sight of what's really important." Thiel explains the distinction most people miss: "The most important distinction in business that people don't talk about enough is that there are two kinds of companies in this world. There are companies that are competitive, and there are companies that have monopolies. If you're a one-of-a-kind company, a happy company that's doing something different, you are a monopoly. It is the goal of every founder, every entrepreneur, it should be their goal to try to build a monopoly business." He frames this as an unconventional truth: "Most people believe that capitalism and competition are synonyms. I believe capitalism and competition are antonyms. A capitalist is someone who's in the business of accumulating capital. A world of perfect competition is a world where all the profits are competed away."
1:20

Peter Thiel: "Competition is for losers" "Competition is for losers, which got people's attention, because we normally believe the opposite. We believe that the losers are the people who don't compete intensely enough. You're a loser if you're not competitive. But what if you're a loser because you're too obsessed with competing? If you're too focused on competing, maybe you're losing sight of what's really important." Thiel explains the distinction most people miss: "The most important distinction in business that people don't talk about enough is that there are two kinds of companies in this world. There are companies that are competitive, and there are companies that have monopolies. If you're a one-of-a-kind company, a happy company that's doing something different, you are a monopoly. It is the goal of every founder, every entrepreneur, it should be their goal to try to build a monopoly business." He frames this as an unconventional truth: "Most people believe that capitalism and competition are synonyms. I believe capitalism and competition are antonyms. A capitalist is someone who's in the business of accumulating capital. A world of perfect competition is a world where all the profits are competed away."

Jaynit

55,180 次观看 • 3 个月前

Pedro Franceschi explains why Brex doesn’t hire “people managers” anymore One day Brex founder Pedro Franceschi made a list of all of the leaders at the company who worked and didn’t work. “I was trying to find what was predictive of leadership success,” he explains. “A lot of things are important, but they’re not predictive. For example, being customer obsessed is important, but there are people who were customer obsessed who were on both sides of the list.” The only trait that Pedro found to be predictive of leadership success at Brex was what he calls “the ability to operate at all levels” — someone who even at the highest levels of leadership has a deep understanding of the details of execution at the individual contributor level. What this means in practice is a CTO who is actually a great engineer. A Head of Design who can actually design amazing products. And a great Head of Sales who can actually go and close deals themselves if they need to. “It doesn’t mean that they’re going to do that all the time,” Pedro explains, “But it means that they know the nuances of what makes someone great at the craft… If you don’t know how to identify greatness because you don’t know what the bar is yourself, there’s no way to build a team that’s great.” He continues: “A lot of companies develop this role over time that people call a ‘people manager.’ They’re Director of Engineering but they can’t really code because they manage people now… And that concept is just something we eliminated. At the end of the day, there’s no way to manage people divorced from the work — you’re managing the work itself.” Pedro uses Jony Ive as an example: “Jony Ive wasn’t managing the team that designed the iPhone. He was designing the iPhone with a group of people. It’s simple, but it is a very profound change in how you orient your relationship with the work and what you put out there in the world. And I think you have to select for people who appreciate the actual output of the work and the work itself, not the process of doing the work… What matters is: Do you know what great looks like? Can you do it yourself? And can you bring people along with a really high bar for doing it at all level.” Video source: Kleiner Perkins (2025)
3:50

Pedro Franceschi explains why Brex doesn’t hire “people managers” anymore One day Brex founder Pedro Franceschi made a list of all of the leaders at the company who worked and didn’t work. “I was trying to find what was predictive of leadership success,” he explains. “A lot of things are important, but they’re not predictive. For example, being customer obsessed is important, but there are people who were customer obsessed who were on both sides of the list.” The only trait that Pedro found to be predictive of leadership success at Brex was what he calls “the ability to operate at all levels” — someone who even at the highest levels of leadership has a deep understanding of the details of execution at the individual contributor level. What this means in practice is a CTO who is actually a great engineer. A Head of Design who can actually design amazing products. And a great Head of Sales who can actually go and close deals themselves if they need to. “It doesn’t mean that they’re going to do that all the time,” Pedro explains, “But it means that they know the nuances of what makes someone great at the craft… If you don’t know how to identify greatness because you don’t know what the bar is yourself, there’s no way to build a team that’s great.” He continues: “A lot of companies develop this role over time that people call a ‘people manager.’ They’re Director of Engineering but they can’t really code because they manage people now… And that concept is just something we eliminated. At the end of the day, there’s no way to manage people divorced from the work — you’re managing the work itself.” Pedro uses Jony Ive as an example: “Jony Ive wasn’t managing the team that designed the iPhone. He was designing the iPhone with a group of people. It’s simple, but it is a very profound change in how you orient your relationship with the work and what you put out there in the world. And I think you have to select for people who appreciate the actual output of the work and the work itself, not the process of doing the work… What matters is: Do you know what great looks like? Can you do it yourself? And can you bring people along with a really high bar for doing it at all level.” Video source: Kleiner Perkins (2025)

Startup Archive

45,584 次观看 • 1 年前