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"It all comes down to compute." Dmitri Alperovitch from Silverado Policy Accelerator explains: "The single most important input to winning is compute the processing power used to train and run AI models. Let me say that plainly, because it is defining that everything that congress and this committee do... show more

Select Committee on China

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In the 20th century, power depended on OIL and STEEL. In the 21st century, power depends on AI, CHIPS and COMPUTE CAPABILITY. At AI Summit 2026 India, I spoke about why the GPU challenge is not just a ‘supply chain issue’ but a ‘sovereignty issue’. In the AI century, power will rest with those who control chips, compute capacity and data centres. Today, design monopolies, manufacturing concentration and export controls determine who gets access. India controls none of these critical levers. We have the talent. We have the ambition. We have the intent. We have the capital. But talent without compute is aspiration. And compute without sovereignty is dependence. The role of policymakers is not to slow AI down; it is to remove bottlenecks, diversify access, set clear national targets, and build sovereign AI infrastructure in India. This is not partisan. It is strategic. #IndiaAIImpactSummit2026 #AI #ResponsibleAI #ArtificialIntelligence #BharatMandapam

In the 20th century, power depended on OIL and STEEL. In the 21st century, power depends on AI, CHIPS and COMPUTE CAPABILITY. At AI Summit 2026 India, I spoke about why the GPU challenge is not just a ‘supply chain issue’ but a ‘sovereignty issue’. In the AI century, power will rest with those who control chips, compute capacity and data centres. Today, design monopolies, manufacturing concentration and export controls determine who gets access. India controls none of these critical levers. We have the talent. We have the ambition. We have the intent. We have the capital. But talent without compute is aspiration. And compute without sovereignty is dependence. The role of policymakers is not to slow AI down; it is to remove bottlenecks, diversify access, set clear national targets, and build sovereign AI infrastructure in India. This is not partisan. It is strategic. #IndiaAIImpactSummit2026 #AI #ResponsibleAI #ArtificialIntelligence #BharatMandapam

Raghav Chadha

70,153 views • 4 months ago

Claude Fable 5 is INSANE 🤯 So we asked it to build the perfect private AI infrastructure, where: → 500+ open models run behind a single API, not one company's black box → An open data marketplace → You fine-tune and serve models on decentralized GPU compute → Agents pay per call in USDC via x402 → Every model, dataset, and payment settles on Base It failed. Luckily, we've spent years building exactly that. Private Inference. Data. Compute. Settlement. One private AI infrastructure layer. Cluster Protocol.

Claude Fable 5 is INSANE 🤯 So we asked it to build the perfect private AI infrastructure, where: → 500+ open models run behind a single API, not one company's black box → An open data marketplace → You fine-tune and serve models on decentralized GPU compute → Agents pay per call in USDC via x402 → Every model, dataset, and payment settles on Base It failed. Luckily, we've spent years building exactly that. Private Inference. Data. Compute. Settlement. One private AI infrastructure layer. Cluster Protocol.

Cluster Protocol

25,516 views • 21 days ago

Sam Altman says the AI infrastructure race is not about bigger chatbots. It is about shifting the planet's intellectual output from human brains to AI brains. "If people knew what we could do with compute, they would want way, way more." "The thing I am personally most excited about is to use AI and lots of compute to discover new science." "A recent cool example here is we built the Sora Android app using Codex... in less than a month." "You can imagine that way much further, where entire companies can build their products using lots of compute." Then he gives the scale: "Let's say that an AI company today might be generating something on the order of 10 trillion tokens a day out of frontier models." "We're going to have these models at a company be outputting more tokens per day than all of humanity put together, and then 10 times that, and then 100 times that." The bottleneck is moving from software talent to compute supply, inference speed, product integration, and where all that machine intelligence gets pointed.

Sam Altman says the AI infrastructure race is not about bigger chatbots. It is about shifting the planet's intellectual output from human brains to AI brains. "If people knew what we could do with compute, they would want way, way more." "The thing I am personally most excited about is to use AI and lots of compute to discover new science." "A recent cool example here is we built the Sora Android app using Codex... in less than a month." "You can imagine that way much further, where entire companies can build their products using lots of compute." Then he gives the scale: "Let's say that an AI company today might be generating something on the order of 10 trillion tokens a day out of frontier models." "We're going to have these models at a company be outputting more tokens per day than all of humanity put together, and then 10 times that, and then 100 times that." The bottleneck is moving from software talent to compute supply, inference speed, product integration, and where all that machine intelligence gets pointed.

Karl Mehta

16,359 views • 4 days ago

#BudgetSession2025 | Lok Sabha LoP and Congress MP Rahul Gandhi says "People talk about AI, but it's important to understand that AI on its own is absolutely meaningless because AI operates on top of data. Without data, AI means nothing. And if we look at data today, there is one thing which is very clear. Every single piece of data that comes out of the production system in the world. The data that was used to make this phone, the data that is used to make electric cars. The data that is used to make basically all electronics on the planet today is owned by China. And the consumption data is owned by the United States... China has at least a 10 year lead on India in this space. China has been working on batteries, robots, motors, optics for the last 10 years and we are behind...We would ensure that our banking system is not captured by 2-3 companies that basically do not allow you to build a production system. But our banking system is open, dynamic and accessible to small and medium businesses and to millions and millions of entrepreneurs who want to take part in this revolution. Our foreign policy would take into account this revolution. When we talk to the United States, we would not send our foreign minister to invite our Prime Minister to his coronation...Because if we had a production system and if we were working on these technologies, the American President would come here and invite the Prime Minister."

#BudgetSession2025 | Lok Sabha LoP and Congress MP Rahul Gandhi says "People talk about AI, but it's important to understand that AI on its own is absolutely meaningless because AI operates on top of data. Without data, AI means nothing. And if we look at data today, there is one thing which is very clear. Every single piece of data that comes out of the production system in the world. The data that was used to make this phone, the data that is used to make electric cars. The data that is used to make basically all electronics on the planet today is owned by China. And the consumption data is owned by the United States... China has at least a 10 year lead on India in this space. China has been working on batteries, robots, motors, optics for the last 10 years and we are behind...We would ensure that our banking system is not captured by 2-3 companies that basically do not allow you to build a production system. But our banking system is open, dynamic and accessible to small and medium businesses and to millions and millions of entrepreneurs who want to take part in this revolution. Our foreign policy would take into account this revolution. When we talk to the United States, we would not send our foreign minister to invite our Prime Minister to his coronation...Because if we had a production system and if we were working on these technologies, the American President would come here and invite the Prime Minister."

ANI

163,581 views • 1 year ago

.Dan Shipper 📧: "The AI jobpocalypse is not a thing. The mass unemployment thing that AI lab CEOs are talking about—that's not going to happen. AI models make yesterday's human competence cheap. But what's interesting is that since everyone's using the same models, it all looks the same. So it becomes commoditized. It's not valuable anymore. And what humans do is we go in there, and we're like, yeah, we have all this frozen human competence from yesterday, how do I use this to make something new and interesting, today?"

.Dan Shipper 📧: "The AI jobpocalypse is not a thing. The mass unemployment thing that AI lab CEOs are talking about—that's not going to happen. AI models make yesterday's human competence cheap. But what's interesting is that since everyone's using the same models, it all looks the same. So it becomes commoditized. It's not valuable anymore. And what humans do is we go in there, and we're like, yeah, we have all this frozen human competence from yesterday, how do I use this to make something new and interesting, today?"

Lenny Rachitsky

275,964 views • 1 month ago

From rewriting Google’s search stack in the early 2000s to reviving sparse trillion-parameter models and co-designing TPUs with frontier ML research, Jeff Dean has quietly shaped nearly every layer of the modern AI stack. As Chief AI Scientist at Google and a driving force behind Gemini, Jeff has lived through multiple scaling revolutions from CPUs and sharded indices to multimodal models that reason across text, video, and code. We sat down with Jeff to unpack what it really means to “own the Pareto frontier,” why distillation is the quiet force behind every generation of faster, cheaper models, how energy not FLOPs is becoming the true constraint on AI compute, what it takes to co-design hardware and models 2–6 years into the future, why unified multimodal systems will outperform specialized ones, what it was like leading the charge to unify all of Google’s AI teams, and his prediction that deeply personalized models with access to your full digital context will redefine what useful AI looks like. Jeff Dean Google DeepMind Google

From rewriting Google’s search stack in the early 2000s to reviving sparse trillion-parameter models and co-designing TPUs with frontier ML research, Jeff Dean has quietly shaped nearly every layer of the modern AI stack. As Chief AI Scientist at Google and a driving force behind Gemini, Jeff has lived through multiple scaling revolutions from CPUs and sharded indices to multimodal models that reason across text, video, and code. We sat down with Jeff to unpack what it really means to “own the Pareto frontier,” why distillation is the quiet force behind every generation of faster, cheaper models, how energy not FLOPs is becoming the true constraint on AI compute, what it takes to co-design hardware and models 2–6 years into the future, why unified multimodal systems will outperform specialized ones, what it was like leading the charge to unify all of Google’s AI teams, and his prediction that deeply personalized models with access to your full digital context will redefine what useful AI looks like. Jeff Dean Google DeepMind Google

Latent.Space

529,014 views • 4 months ago

Data centers in space are a "no brainer." SpaceX's 1st employee Tom Mueller (Tom Mueller) on Elon Musk's plan to move compute into space: "It makes the most sense of anything to move to space. All you need as an input is power, and all you have as an output is data." "You move it to space, you have all the power you would ever need, and you transmit that data back down on a terawatt laser beam—it's solved. It's just so simple."

Data centers in space are a "no brainer." SpaceX's 1st employee Tom Mueller (Tom Mueller) on Elon Musk's plan to move compute into space: "It makes the most sense of anything to move to space. All you need as an input is power, and all you have as an output is data." "You move it to space, you have all the power you would ever need, and you transmit that data back down on a terawatt laser beam—it's solved. It's just so simple."

Molly O’Shea

357,276 views • 27 days ago

Why wouldn’t China want more data centers built in the United States? Simple, the nation that leads in AI will lead the future, economically, technologically, and militarily. We’re already seeing it happen in real time as AI drives unprecedented productivity and margin expansion across every sector of the economy. While America debates permits, regulations, and protests over data centers, China is rapidly building power infrastructure and scaling compute capacity as fast as possible. This race is no longer theoretical. Whoever has the most compute, the best models, and the strongest infrastructure will shape the next era of global power.

Why wouldn’t China want more data centers built in the United States? Simple, the nation that leads in AI will lead the future, economically, technologically, and militarily. We’re already seeing it happen in real time as AI drives unprecedented productivity and margin expansion across every sector of the economy. While America debates permits, regulations, and protests over data centers, China is rapidly building power infrastructure and scaling compute capacity as fast as possible. This race is no longer theoretical. Whoever has the most compute, the best models, and the strongest infrastructure will shape the next era of global power.

Kevin O'Leary aka Mr. Wonderful

35,420 views • 1 month ago

Is AI officially becoming RACIST? 🚨🚨🚨 It would appear so… Various AI models are now dictating which human lives they deem “most important” Pakistan, India, and Nigeria have scored at the top, and the UK, and United States have scored dead last. Why is AI categorizing the value of human life in the first place, and on top of that, why is AI coming to that conclusion based on where you are from? It appears that these models are being programmed to view humans differently based on WHO is programming the AI… I can think of thousands of ways this can be used against us. This is freaky as hell, and creating a SERIOUSLY DANGEROUS precedent.

Is AI officially becoming RACIST? 🚨🚨🚨 It would appear so… Various AI models are now dictating which human lives they deem “most important” Pakistan, India, and Nigeria have scored at the top, and the UK, and United States have scored dead last. Why is AI categorizing the value of human life in the first place, and on top of that, why is AI coming to that conclusion based on where you are from? It appears that these models are being programmed to view humans differently based on WHO is programming the AI… I can think of thousands of ways this can be used against us. This is freaky as hell, and creating a SERIOUSLY DANGEROUS precedent.

The Patriot Voice

40,782 views • 1 year ago

Ilya Sutskever just said that when it comes to AI models, we are back at the age of research & ending the age of scaling. What he is telling us is that more compute at this point won't help us get much better models; we need new breakthroughs. Not something that the semi companies like $NVDA, $AMD want to hear TBH.

Ilya Sutskever just said that when it comes to AI models, we are back at the age of research & ending the age of scaling. What he is telling us is that more compute at this point won't help us get much better models; we need new breakthroughs. Not something that the semi companies like $NVDA, $AMD want to hear TBH.

Rihard Jarc

361,295 views • 7 months ago

Nvidia continues to dominate the AI industry with record earnings, explosive data center growth, and massive demand for compute. But the bigger story is what’s happening globally behind the scenes. China is aggressively competing with the United States on AI infrastructure, power generation, and data center expansion and they don’t want to rely on American chips to do it. This is no longer just about stocks it’s a global race for AI dominance.

Nvidia continues to dominate the AI industry with record earnings, explosive data center growth, and massive demand for compute. But the bigger story is what’s happening globally behind the scenes. China is aggressively competing with the United States on AI infrastructure, power generation, and data center expansion and they don’t want to rely on American chips to do it. This is no longer just about stocks it’s a global race for AI dominance.

Kevin O'Leary aka Mr. Wonderful

12,462 views • 1 month ago

🚨 Jensen Huang says everyone panicked about the AI data when MOST training data was never REAL to begin with. Ilya Sutskever told the industry pre-training was over. "Ilya said, 'We're out of data,' or something like that. 'Pre-training is over,' or something like that," Huang says. "The industry panicked, you know, that this is the end of AI." "And of course, of course that's obviously not true. We're gonna keep on scaling the amount of data that we have to train with." "A lot of that data is probably gonna be synthetic." That's where the panic came from — synthetic data sounds like cheating. "Most of the data that we are training, that we teach each other with, inform each other with, is synthetic." "It's synthetic because it didn't come out of nature." "You created it. I'm consuming it. I modify it, augment it, I regenerate it, somebody else consumes it." The textbook in your hand is synthetic. The post you're reading is synthetic. The lecture you took is synthetic. Nature didn't make any of it. Humans did. AI just learned to do the same thing — faster. "Training is now limited by compute," Huang says. "Data is now limited by compute." The data wall wasn't a wall. It was a mirror. If you're new here, follow @AiEvolutio for the latest on ChatGPT, Claude, and the AI tools shaping how we work and create. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

🚨 Jensen Huang says everyone panicked about the AI data when MOST training data was never REAL to begin with. Ilya Sutskever told the industry pre-training was over. "Ilya said, 'We're out of data,' or something like that. 'Pre-training is over,' or something like that," Huang says. "The industry panicked, you know, that this is the end of AI." "And of course, of course that's obviously not true. We're gonna keep on scaling the amount of data that we have to train with." "A lot of that data is probably gonna be synthetic." That's where the panic came from — synthetic data sounds like cheating. "Most of the data that we are training, that we teach each other with, inform each other with, is synthetic." "It's synthetic because it didn't come out of nature." "You created it. I'm consuming it. I modify it, augment it, I regenerate it, somebody else consumes it." The textbook in your hand is synthetic. The post you're reading is synthetic. The lecture you took is synthetic. Nature didn't make any of it. Humans did. AI just learned to do the same thing — faster. "Training is now limited by compute," Huang says. "Data is now limited by compute." The data wall wasn't a wall. It was a mirror. If you're new here, follow @AiEvolutio for the latest on ChatGPT, Claude, and the AI tools shaping how we work and create. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

AI Evolution

15,565 views • 1 month ago

Sam Altman says OpenAI has reached another GPT-3-style moment Something important is working so well that other strong projects have to give way That is why OpenAI is focusing its compute on next-generation models and the automated researchers and companies they can power

Sam Altman says OpenAI has reached another GPT-3-style moment Something important is working so well that other strong projects have to give way That is why OpenAI is focusing its compute on next-generation models and the automated researchers and companies they can power

Haider.

59,639 views • 2 months ago

The CEO of the world's largest asset manager just said something that should reframe how every investor thinks about the AI trade. Larry Fink, managing $11.5 trillion at BlackRock, stood at the Milken Institute Global Conference and said four words that matter, "We just don't have enough compute." "The United States is short power. We're short compute. We're short chips. And there's going to be shortages in all three and memory, four things. I actually believe a new asset class will be buying futures of compute." Think about what that means. Fink is predicting that compute becomes a tradable commodity like oil, like grain, like natural gas where investors buy forward contracts on future capacity because the shortage is so structural and so predictable that a derivatives market will emerge to price it. That is not a minor observation from a finance executive but rather the chairman of the most powerful capital allocator on the planet telling you that compute scarcity is a multi-year, investable megatrend. The data backs him up completely. Data centers will consume 70% of all memory chips produced globally in 2026. Advanced HBM production from Samsung, SK Hynix, and Micron is sold out through 2026 and into 2027 and a single AI server consumes 10-20x more memory than a conventional workload server. DRAM supply growth is running at just 16% annually while AI infrastructure demand is growing at 80%+. The chip crunch, the power crunch, and the compute crunch are not temporary dislocations, they are structural, and they will get worse before they get better. Fink also said something the bears keep getting wrong: "There is not an AI bubble. There is the opposite. We have supply shortages. Demand is growing much faster than anyone has ever anticipated." This is why the Milk Road Pro portfolio is built the way it is, long the companies producing and supplying the constrained resources: chips, memory, compute infrastructure, and power. Check out Milk Road Pro, link below to access our full thesis and plays.

The CEO of the world's largest asset manager just said something that should reframe how every investor thinks about the AI trade. Larry Fink, managing $11.5 trillion at BlackRock, stood at the Milken Institute Global Conference and said four words that matter, "We just don't have enough compute." "The United States is short power. We're short compute. We're short chips. And there's going to be shortages in all three and memory, four things. I actually believe a new asset class will be buying futures of compute." Think about what that means. Fink is predicting that compute becomes a tradable commodity like oil, like grain, like natural gas where investors buy forward contracts on future capacity because the shortage is so structural and so predictable that a derivatives market will emerge to price it. That is not a minor observation from a finance executive but rather the chairman of the most powerful capital allocator on the planet telling you that compute scarcity is a multi-year, investable megatrend. The data backs him up completely. Data centers will consume 70% of all memory chips produced globally in 2026. Advanced HBM production from Samsung, SK Hynix, and Micron is sold out through 2026 and into 2027 and a single AI server consumes 10-20x more memory than a conventional workload server. DRAM supply growth is running at just 16% annually while AI infrastructure demand is growing at 80%+. The chip crunch, the power crunch, and the compute crunch are not temporary dislocations, they are structural, and they will get worse before they get better. Fink also said something the bears keep getting wrong: "There is not an AI bubble. There is the opposite. We have supply shortages. Demand is growing much faster than anyone has ever anticipated." This is why the Milk Road Pro portfolio is built the way it is, long the companies producing and supplying the constrained resources: chips, memory, compute infrastructure, and power. Check out Milk Road Pro, link below to access our full thesis and plays.

Milk Road AI

418,782 views • 1 month ago

Sergey Brin said compute is dessert. The companies winning the AI race right now are not the ones with the most chips. They are the ones with the best algorithms. Every headline you read about AI is about data centers, Megawatts, and Nvidia orders. Billions in infrastructure and more. The entire investment thesis of the last three years has been built on compute scaling as the primary moat. Sergey thinks that framing is wrong. He pulled out an example from physics. The N-body problem. Scientists have been running those simulations since the fifties. Over the decades, raw compute improved on Moore's law. But the algorithms to solve the problem improved faster. Not slightly faster. Far faster. The algorithmic gains made the compute gains look small. He says the same thing has happened in AI over the last decade. Compute is not the meal. It is the dessert. You still want it. Nobody is turning down frontier compute. But the companies that figured out the algorithms first are the ones actually ahead. The market is pricing AI winners by who has the most chips. Sergey Brin just said that is the wrong scorecard. The ones who win this are not building the biggest data center. They are solving the harder math problem.

Sergey Brin said compute is dessert. The companies winning the AI race right now are not the ones with the most chips. They are the ones with the best algorithms. Every headline you read about AI is about data centers, Megawatts, and Nvidia orders. Billions in infrastructure and more. The entire investment thesis of the last three years has been built on compute scaling as the primary moat. Sergey thinks that framing is wrong. He pulled out an example from physics. The N-body problem. Scientists have been running those simulations since the fifties. Over the decades, raw compute improved on Moore's law. But the algorithms to solve the problem improved faster. Not slightly faster. Far faster. The algorithmic gains made the compute gains look small. He says the same thing has happened in AI over the last decade. Compute is not the meal. It is the dessert. You still want it. Nobody is turning down frontier compute. But the companies that figured out the algorithms first are the ones actually ahead. The market is pricing AI winners by who has the most chips. Sergey Brin just said that is the wrong scorecard. The ones who win this are not building the biggest data center. They are solving the harder math problem.

Ihtesham Ali

129,354 views • 15 days ago

Former EU foreign policy chief Josep Borrell: Russia will only be able to destroy Ukraine if Ukraine is unable to defend itself. If the US does not provide the means to do so, are we going to do it? Question mark. This is the existential question that Europe must answer for itself: Are we in a position to help Ukraine defend itself even if the United States does not? It depends on how willing we are. So far, we have helped Ukraine more than the United States, both in civilian and military terms. Can we do even more and replace the United States? This comes at a cost, and what is needed is not only the will and the ability to pay for it, but also to convert the money into weapons. Because people don't go to the front with a bag of cash; people go to the front with weapons. And between money and weapons there is something called industry, that is, production capacity.

Former EU foreign policy chief Josep Borrell: Russia will only be able to destroy Ukraine if Ukraine is unable to defend itself. If the US does not provide the means to do so, are we going to do it? Question mark. This is the existential question that Europe must answer for itself: Are we in a position to help Ukraine defend itself even if the United States does not? It depends on how willing we are. So far, we have helped Ukraine more than the United States, both in civilian and military terms. Can we do even more and replace the United States? This comes at a cost, and what is needed is not only the will and the ability to pay for it, but also to convert the money into weapons. Because people don't go to the front with a bag of cash; people go to the front with weapons. And between money and weapons there is something called industry, that is, production capacity.

Anton Gerashchenko

51,525 views • 8 months ago

Former US Attorney: Traditionally, the rule is that you have to have some sort of reasonable belief that the person that you're confronting is not a citizen. But we've repeatedly seen ICE and seen this administration engage in this behavior based on someone's appearance, the language they're speaking, where they're standing. It appears to be a policy that comes from the top down and will continue to be used

Former US Attorney: Traditionally, the rule is that you have to have some sort of reasonable belief that the person that you're confronting is not a citizen. But we've repeatedly seen ICE and seen this administration engage in this behavior based on someone's appearance, the language they're speaking, where they're standing. It appears to be a policy that comes from the top down and will continue to be used

FactPost

15,177 views • 8 months ago

I think the narrative on AI is very much that occurred when television went to color and everybody said it would wipe out radio. It didn't happen. It's a tool. It's a tool for productivity and margin enhancement. It's just starting to get utilized in all 11 sectors of the economy. My companies use it. But it's nowhere near the disruptor that people think. I'm more concerned about Chinese on AI because they have unlimited power. They are not restricted to set up coal-burning electrical plants. We can't do that. AI right now, for me, is a competition on defense and the military in China. I worry that we're falling behind the Chinese on power on our grid, and we haven't addressed it yet. We do not have policy that lets us build out at the same pace they are.

I think the narrative on AI is very much that occurred when television went to color and everybody said it would wipe out radio. It didn't happen. It's a tool. It's a tool for productivity and margin enhancement. It's just starting to get utilized in all 11 sectors of the economy. My companies use it. But it's nowhere near the disruptor that people think. I'm more concerned about Chinese on AI because they have unlimited power. They are not restricted to set up coal-burning electrical plants. We can't do that. AI right now, for me, is a competition on defense and the military in China. I worry that we're falling behind the Chinese on power on our grid, and we haven't addressed it yet. We do not have policy that lets us build out at the same pace they are.

Kevin O'Leary aka Mr. Wonderful

10,682 views • 6 months ago

ELON: AI MUST BE TRUTHFUL, NOT POLITICALLY CORRECT "I think it's very important that AI is trained to be truthful and not trained to be politically correct, because political correctness is often simply not true. And that means you're programming AI to lie, and I think that will backfire very badly. I keep harping on this point, but as the saying goes, honesty is the best policy. It's incredibly important. I do fear that regulators will not make the right decisions, that they'll worry too much about human follies. I would encourage regulators to say, what matters most of all is your AI is accurate and truthful.” Source: CA Narendra Madaparthi

ELON: AI MUST BE TRUTHFUL, NOT POLITICALLY CORRECT "I think it's very important that AI is trained to be truthful and not trained to be politically correct, because political correctness is often simply not true. And that means you're programming AI to lie, and I think that will backfire very badly. I keep harping on this point, but as the saying goes, honesty is the best policy. It's incredibly important. I do fear that regulators will not make the right decisions, that they'll worry too much about human follies. I would encourage regulators to say, what matters most of all is your AI is accurate and truthful.” Source: CA Narendra Madaparthi

Mario Nawfal

111,324 views • 7 months ago

Demis says he wants to see a Western open source AI stack and that we’re losing to China. He also says Google doesn’t have enough compute to build two frontier (open and closed) models, which is why Gemma is a smaller family of models. Watch this incredible clip. Shout out Y Combinator and Garry Tan for the fantastic interview.

Demis says he wants to see a Western open source AI stack and that we’re losing to China. He also says Google doesn’t have enough compute to build two frontier (open and closed) models, which is why Gemma is a smaller family of models. Watch this incredible clip. Shout out Y Combinator and Garry Tan for the fantastic interview.

Matthew Berman

296,378 views • 2 months ago