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Noam Brown (Noam Brown) posted something profound this week. Frontier models can solve most problems if you just let them run long enough. Nobody has ever run Mythos for a full year. We may never know how smart any given generation actually is. Gavin Baker's takeaway: however bullish he... show more

Altimeter Capital

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38,325 просмотров • 2 месяцев назад •via X (Twitter)

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If you hold $NVDA, here is the long-running agents argument that made Gavin Baker more bullish on compute. Fable 5 (Claude Opus 4.8) and ChatGPT 5.5 both demonstrated long-running agent capability - models that sustain deep reasoning over hours or days, not single queries. Baker's framing on BG2 Pod: imagine if Einstein had thought about fundamental physics 24 hours a day for a year. A model never gets distracted, never sleeps, never ages. The compute implication: more tokens per query, compounding inference revenue. Under 0.2% of people on Earth use AI agentically today. One such user runs 500 CPU cores and 5 GPUs, 24/7. Scale that to any meaningful population and the compute shortage persists indefinitely via Brad Gerstner: Source: BG2 Pod -

If you hold $NVDA, here is the long-running agents argument that made Gavin Baker more bullish on compute. Fable 5 (Claude Opus 4.8) and ChatGPT 5.5 both demonstrated long-running agent capability - models that sustain deep reasoning over hours or days, not single queries. Baker's framing on BG2 Pod: imagine if Einstein had thought about fundamental physics 24 hours a day for a year. A model never gets distracted, never sleeps, never ages. The compute implication: more tokens per query, compounding inference revenue. Under 0.2% of people on Earth use AI agentically today. One such user runs 500 CPU cores and 5 GPUs, 24/7. Scale that to any meaningful population and the compute shortage persists indefinitely via Brad Gerstner: Source: BG2 Pod -

Podcast Alpha

14,087 просмотров • 1 месяц назад

It's here: We just hit superhuman performance on AI kernel optimization! Real customer models & production settings. Not toy problems (what I typically see). This is the year that Claude writes its own kernels, Codex its own kernels, for every new GPU that it wants to run on -- something that takes months to port between GPU generations today. This has a massive impact to scaling intelligence. More compute means getting the next frontier model sooner.

It's here: We just hit superhuman performance on AI kernel optimization! Real customer models & production settings. Not toy problems (what I typically see). This is the year that Claude writes its own kernels, Codex its own kernels, for every new GPU that it wants to run on -- something that takes months to port between GPU generations today. This has a massive impact to scaling intelligence. More compute means getting the next frontier model sooner.

Sharon Zhou

241,935 просмотров • 5 месяцев назад

I'll let Noam Brown (OpenAI research) answer Yann's “told you so” again. There is nothing to add. There is no wall, there is no end in sight! "Now, we are in a world, like I said earlier, where the amount of compute that's going into pretraining for things large language models is very, very high. But the inference costs are very low. And there was a reasonable concern among various people that we were going to start seeing diminishing returns from AI progress because the costs and the amount of data that you need for pretraining would become so astronomical. And I think the really important takeaway from o1 is that that wall doesn't actually exist, that we can actually push this a lot further. Because, now, we can scale up inference compute. And there's so much room to scale up inference compute."

I'll let Noam Brown (OpenAI research) answer Yann's “told you so” again. There is nothing to add. There is no wall, there is no end in sight! "Now, we are in a world, like I said earlier, where the amount of compute that's going into pretraining for things large language models is very, very high. But the inference costs are very low. And there was a reasonable concern among various people that we were going to start seeing diminishing returns from AI progress because the costs and the amount of data that you need for pretraining would become so astronomical. And I think the really important takeaway from o1 is that that wall doesn't actually exist, that we can actually push this a lot further. Because, now, we can scale up inference compute. And there's so much room to scale up inference compute."

Chubby♨️

132,808 просмотров • 1 год назад

⚡ Gavin Baker on why Elon's data center strategy is printing money — and Brad Gerstner on why nobody saw it coming: "If you can borrow money at 6, 7, 8% and invest in something with a 55% ARR, I'm not the most sophisticated thinker, but that math maths... We do know from Jensen that Elon Musk brings data centers up faster than anyone, 122 days. Speed is literally cost." "This whole category of taking all of this compute, which he's uniquely good at standing up, and then reselling it in a way that's highly profitable was not in a lot of people's forecasts — now it's a major component of the forecast." — Gavin Baker & Brad Gerstner on Bg2 Pod / BGGB Pod As Jensen Huang said, “Elon is an N of 1.”

⚡ Gavin Baker on why Elon's data center strategy is printing money — and Brad Gerstner on why nobody saw it coming: "If you can borrow money at 6, 7, 8% and invest in something with a 55% ARR, I'm not the most sophisticated thinker, but that math maths... We do know from Jensen that Elon Musk brings data centers up faster than anyone, 122 days. Speed is literally cost." "This whole category of taking all of this compute, which he's uniquely good at standing up, and then reselling it in a way that's highly profitable was not in a lot of people's forecasts — now it's a major component of the forecast." — Gavin Baker & Brad Gerstner on Bg2 Pod / BGGB Pod As Jensen Huang said, “Elon is an N of 1.”

bg2clips

15,672 просмотров • 2 месяцев назад

“There's nobody better on planet Earth than Elon at converting electrons to tokens. He was building EWS all along.” - Brad Gerstner on how becoming a hyperscaler impacts SpaceX’s outlook Brad Gerstner on Elon Musk's cloud strategy: “It's a critically important evolution to the story. SpaceX has this five-layer cake: launch, connectivity, compute, hyperscalers, space datacenters, and then applications and models, and then other bets. And now we see the ace card that Elon's playing. He was building EWS all along, and so I estimate that this is going to generate, in this year, an incremental $4 to $5B of revenue on top of what analysts estimate is in the mid-20s. That's a material amount of incremental revenue to offset the cost of the investments that he's made here, and that will subsidize, to Chamath's point, all that he's investing to build the next generation of Grok. Remember, too, that he has three facilities, Colossus, Macro Hard, and Macro Harder. 1.2 gigawatts in Macro Hard and Macro Harder in Blackwell. So he's given the one that's kind of less connected, H100's great for inference, to Anthropic. He's monetizing it in a big way. It's terrific for Anthropic, and it solves what I think was the biggest question in the valuation story, which is what if he spends ahead of xAI's revenue? It takes the pressure off xAI delivering immediate revenue. Now he becomes an immediate competitor in the hyperscalers. I don't think this is the last announcement. And I would just say finally, everybody has talked about how we don't have enough power, how we don't have enough compute, how the revenues would not show up this year, but the chaos that is American capitalism somehow finds a way.”

“There's nobody better on planet Earth than Elon at converting electrons to tokens. He was building EWS all along.” - Brad Gerstner on how becoming a hyperscaler impacts SpaceX’s outlook Brad Gerstner on Elon Musk's cloud strategy: “It's a critically important evolution to the story. SpaceX has this five-layer cake: launch, connectivity, compute, hyperscalers, space datacenters, and then applications and models, and then other bets. And now we see the ace card that Elon's playing. He was building EWS all along, and so I estimate that this is going to generate, in this year, an incremental $4 to $5B of revenue on top of what analysts estimate is in the mid-20s. That's a material amount of incremental revenue to offset the cost of the investments that he's made here, and that will subsidize, to Chamath's point, all that he's investing to build the next generation of Grok. Remember, too, that he has three facilities, Colossus, Macro Hard, and Macro Harder. 1.2 gigawatts in Macro Hard and Macro Harder in Blackwell. So he's given the one that's kind of less connected, H100's great for inference, to Anthropic. He's monetizing it in a big way. It's terrific for Anthropic, and it solves what I think was the biggest question in the valuation story, which is what if he spends ahead of xAI's revenue? It takes the pressure off xAI delivering immediate revenue. Now he becomes an immediate competitor in the hyperscalers. I don't think this is the last announcement. And I would just say finally, everybody has talked about how we don't have enough power, how we don't have enough compute, how the revenues would not show up this year, but the chaos that is American capitalism somehow finds a way.”

The All-In Podcast

62,278 просмотров • 3 месяцев назад

It almost seems like magic right? Almost as if he had been preparing for this battle his whole life.. Just as he told us. It all just seemed to fall into place in hindsight.. Almost as if scripted. Almost as if there has been a plan to save the world long before we even knew. How is POTUS always 5-steps ahead? Who is helping POTUS? How is it he's been right about everything? Does POTUS know where the bodies are buried? Does POTUS have the goods on most bad actors? Was TRUMP asked to run for President? Hold on tight frens. We are getting to the good part. DECLAS

It almost seems like magic right? Almost as if he had been preparing for this battle his whole life.. Just as he told us. It all just seemed to fall into place in hindsight.. Almost as if scripted. Almost as if there has been a plan to save the world long before we even knew. How is POTUS always 5-steps ahead? Who is helping POTUS? How is it he's been right about everything? Does POTUS know where the bodies are buried? Does POTUS have the goods on most bad actors? Was TRUMP asked to run for President? Hold on tight frens. We are getting to the good part. DECLAS

Joe Rambo

96,937 просмотров • 1 год назад

🚨 JUST NOW — Tomi Lahren MIC DROPS Gavin Newsom: "Gavin's so smug, he doesn't know how to take a question...every time he's asked about the FAILURES of California, he repeats the same thing. '4th largest economy in the world!' Yeah, but that's not BECAUSE of your leadership!" "That's because California is a great state. You're doing everything you possibly can, Gavin, to KILL it!" "You and the Democrats who run that state. So the fact that he wants to run for president, we all know. And he can't take a simple question from a friendly, by the way, from Bill Maher. And he can't answer that!" "Boy, Gavin, Kamala might come knocking up on your back door there. She might actually be more powerful than you are, buddy." Tomi Lahren 🤣 The Big Weekend Show

🚨 JUST NOW — Tomi Lahren MIC DROPS Gavin Newsom: "Gavin's so smug, he doesn't know how to take a question...every time he's asked about the FAILURES of California, he repeats the same thing. '4th largest economy in the world!' Yeah, but that's not BECAUSE of your leadership!" "That's because California is a great state. You're doing everything you possibly can, Gavin, to KILL it!" "You and the Democrats who run that state. So the fact that he wants to run for president, we all know. And he can't take a simple question from a friendly, by the way, from Bill Maher. And he can't answer that!" "Boy, Gavin, Kamala might come knocking up on your back door there. She might actually be more powerful than you are, buddy." Tomi Lahren 🤣 The Big Weekend Show

Eric Daugherty

175,568 просмотров • 3 месяцев назад

David Stearns was asked how he approaches the Mets losing long-tenured, popular players: "That is something, broadly, that we talk about a lot. We have a lot of those conversations. We've had them throughout this offseason. We had them throughout last offseason, as well, when we were faced with some decisions. It is part of it. I've said this before, I can't tell you I know exactly how to weigh that. I think we do our best to weigh the full impact of any player on our team, on our organization, and we make the best decision we can."

David Stearns was asked how he approaches the Mets losing long-tenured, popular players: "That is something, broadly, that we talk about a lot. We have a lot of those conversations. We've had them throughout this offseason. We had them throughout last offseason, as well, when we were faced with some decisions. It is part of it. I've said this before, I can't tell you I know exactly how to weigh that. I think we do our best to weigh the full impact of any player on our team, on our organization, and we make the best decision we can."

SNY Mets

61,721 просмотров • 8 месяцев назад

Sell Drugs. Onchain. an indie game made by 1 dev went viral and crushed all the AAA games this year its Schedule 1 → 210k concurrent players week 1 → $125m revenue → everyone shared their drug business on tiktok/ig turns out people loves running a drug business in a simulated world so we thought what if you could run a drug empire and actually make money? (legally lol) welcome to Addicted a hyper speculative drug dealing sim game we basically rebuilt schedule 1 entirely on chain the game is fully onchain so its verifiable and unstoppable nobody has ever tried to build something like this on solana so took us 5+ months and 3 audits but ... finally its coming out soon you are not bullish enough

Sell Drugs. Onchain. an indie game made by 1 dev went viral and crushed all the AAA games this year its Schedule 1 → 210k concurrent players week 1 → $125m revenue → everyone shared their drug business on tiktok/ig turns out people loves running a drug business in a simulated world so we thought what if you could run a drug empire and actually make money? (legally lol) welcome to Addicted a hyper speculative drug dealing sim game we basically rebuilt schedule 1 entirely on chain the game is fully onchain so its verifiable and unstoppable nobody has ever tried to build something like this on solana so took us 5+ months and 3 audits but ... finally its coming out soon you are not bullish enough

Addicted

293,399 просмотров • 11 месяцев назад

Subnet 64 Chutes just confirmed in their latest interview with Jesus Martinez that they have the capability to run 1 trillion parameter models. let's put that into perspective for a second: templar was making waves for running 72b models and rightfully so, that was genuinely impressive. but Chamath Palihapitiya, when he brought up templar in a recent interview with Jensen Huang from NVIDIA, thought they were running 4b models. not 72b. 4b. and he was still bullish on it. now imagine when he finds out what chutes confirmed they can do.. 1 trillion parameters. on a decentralised subnet. no AWS. no Google Cloud. no centralised infrastructure pulling the strings. just Bittensor doing what it was always supposed to do - incentivising the best compute in the world to show up and compete. Jensen Huang talks about whoever is pushing the frontier of compute. that's the conversation chutes just walked into. this is the kind of milestone that doesn't stay quiet for long. when people outside of crypto start connecting the dots that a bittensor subnet is running inference at a scale that rivals or exceeds what the top AI labs are deploying, the narrative around $TAO changes completely. Chamath gets it wrong on the model size and is still impressed. Jensen sees who's actually moving compute forward. and chutes just put a number on the table that neither of them can ignore. the noise hasn't started yet. but it will.

Subnet 64 Chutes just confirmed in their latest interview with Jesus Martinez that they have the capability to run 1 trillion parameter models. let's put that into perspective for a second: templar was making waves for running 72b models and rightfully so, that was genuinely impressive. but Chamath Palihapitiya, when he brought up templar in a recent interview with Jensen Huang from NVIDIA, thought they were running 4b models. not 72b. 4b. and he was still bullish on it. now imagine when he finds out what chutes confirmed they can do.. 1 trillion parameters. on a decentralised subnet. no AWS. no Google Cloud. no centralised infrastructure pulling the strings. just Bittensor doing what it was always supposed to do - incentivising the best compute in the world to show up and compete. Jensen Huang talks about whoever is pushing the frontier of compute. that's the conversation chutes just walked into. this is the kind of milestone that doesn't stay quiet for long. when people outside of crypto start connecting the dots that a bittensor subnet is running inference at a scale that rivals or exceeds what the top AI labs are deploying, the narrative around $TAO changes completely. Chamath gets it wrong on the model size and is still impressed. Jensen sees who's actually moving compute forward. and chutes just put a number on the table that neither of them can ignore. the noise hasn't started yet. but it will.

Alchemist - τ

18,369 просмотров • 4 месяцев назад

💥3 term President💥 if you have never seen this, it will be the most enlightening, and educational 9:41 you watch today. Share this. Truth matters. This was aired 2 months before the 2020 election. PEADs may just explain most of what we are watching play out before our eyes. Trump has dropped hint after hint that Joe Biden is not actually President. We can see with our own eyes that it's not him. Trump has even told us point blank that it's NOT him.. He is shot. He was announced as 45, 46, and 47th President of the US. He told us that we are kind of in his second term right now! He held up the book showing the Presidential seal as his ID. Well how could this all be pulled off? This may just be your answer.

💥3 term President💥 if you have never seen this, it will be the most enlightening, and educational 9:41 you watch today. Share this. Truth matters. This was aired 2 months before the 2020 election. PEADs may just explain most of what we are watching play out before our eyes. Trump has dropped hint after hint that Joe Biden is not actually President. We can see with our own eyes that it's not him. Trump has even told us point blank that it's NOT him.. He is shot. He was announced as 45, 46, and 47th President of the US. He told us that we are kind of in his second term right now! He held up the book showing the Presidential seal as his ID. Well how could this all be pulled off? This may just be your answer.

Joe Rambo

611,592 просмотров • 2 лет назад

To undecided voters: I am posting this for you, and to people who may not have seen it. This is a short clip from when a very young, 34 year-old Trump was interviewed by Rona Barrett. Trump was asked why someone like himself wouldn’t run for political office. Listen to his response. Kinda chilling actually, but the reason I know he is the right person to lead this country is because his views have never changed. He has always cared about this country. The same can’t be said for Kamala… I would encourage you to watch the full interview that can be found on youtube. You may be surprised at what you learn about this extraordinary man!

To undecided voters: I am posting this for you, and to people who may not have seen it. This is a short clip from when a very young, 34 year-old Trump was interviewed by Rona Barrett. Trump was asked why someone like himself wouldn’t run for political office. Listen to his response. Kinda chilling actually, but the reason I know he is the right person to lead this country is because his views have never changed. He has always cared about this country. The same can’t be said for Kamala… I would encourage you to watch the full interview that can be found on youtube. You may be surprised at what you learn about this extraordinary man!

Sequencer

215,836 просмотров • 1 год назад

Yann LeCun just told the most well-funded industry in human history it is solving the wrong problem. LeCun: “Babies learn this around the age of eight or nine months, that objects don’t float, they fall.” No dataset. No labels. No reward signal. A nine month old drops a spoon and builds a physics engine no machine can match. LeCun: “Most of us can learn to drive in about 20 or 30 hours of training without ever crashing, causing any accident.” Twenty hours. Tesla has built the most capable driving system on the road. It took billions of miles of data to get there. A sixteen year old gets there over a long weekend. Not because the teenager is the better driver. Because the teenager is not learning to drive. They are deploying a model of reality they have been building since birth. LeCun: “If we drive next to a cliff, we know that if we turn the wheel to the right, the car is going to run off the cliff and nothing good is going to come out of this.” You simulate the crash. You see the wreckage. You feel the fall. You turn the wheel. None of it was real. All of it was intelligence. Every AI has to crash a thousand times to learn what you imagined once and never did. That is not a performance gap. That is an architecture gap. LeCun: “The main problem we need to solve is how do we learn models of the world.” Not bigger models. Not more compute. Not another trillion tokens. World models. A machine that can run reality forward before it acts. The industry is scaling language. LeCun says language is a compression of thought. Not thought itself. You understood gravity before you could say the word. You grasped cause and effect before your first sentence. The deepest intelligence you will ever possess was built in total silence. And every lab on Earth is trying to reconstruct the mind from words alone. Physics does not care about your context window. A baby who learns that cups fall in a kitchen already knows that rocks fall off cliffs. No retraining. No fine-tuning. One model. Every environment. That is what intelligence actually is. Not prediction. Not pattern matching. Not scale. A simulation of reality so precise you rehearse the future before it exists. Every infant on Earth builds one. No machine ever has.

Yann LeCun just told the most well-funded industry in human history it is solving the wrong problem. LeCun: “Babies learn this around the age of eight or nine months, that objects don’t float, they fall.” No dataset. No labels. No reward signal. A nine month old drops a spoon and builds a physics engine no machine can match. LeCun: “Most of us can learn to drive in about 20 or 30 hours of training without ever crashing, causing any accident.” Twenty hours. Tesla has built the most capable driving system on the road. It took billions of miles of data to get there. A sixteen year old gets there over a long weekend. Not because the teenager is the better driver. Because the teenager is not learning to drive. They are deploying a model of reality they have been building since birth. LeCun: “If we drive next to a cliff, we know that if we turn the wheel to the right, the car is going to run off the cliff and nothing good is going to come out of this.” You simulate the crash. You see the wreckage. You feel the fall. You turn the wheel. None of it was real. All of it was intelligence. Every AI has to crash a thousand times to learn what you imagined once and never did. That is not a performance gap. That is an architecture gap. LeCun: “The main problem we need to solve is how do we learn models of the world.” Not bigger models. Not more compute. Not another trillion tokens. World models. A machine that can run reality forward before it acts. The industry is scaling language. LeCun says language is a compression of thought. Not thought itself. You understood gravity before you could say the word. You grasped cause and effect before your first sentence. The deepest intelligence you will ever possess was built in total silence. And every lab on Earth is trying to reconstruct the mind from words alone. Physics does not care about your context window. A baby who learns that cups fall in a kitchen already knows that rocks fall off cliffs. No retraining. No fine-tuning. One model. Every environment. That is what intelligence actually is. Not prediction. Not pattern matching. Not scale. A simulation of reality so precise you rehearse the future before it exists. Every infant on Earth builds one. No machine ever has.

Dustin

121,810 просмотров • 1 месяц назад

TIM DILLON on the Thomas Massie election: "I don't know how you run a country where people can just dump $32 million into a race" "What it's showing you is that if you spend enough money, you can just create any reality you want" "No one knows who the hell the other guy is" "This guy [Massie] who's like, 'Release the Epstein Files. Hold people accountable. Prosecute pedophiles. Get out of foreign wars,' that guy loses to a guy who's like, 'Let's cover up the Epstein Files, let's not prosecute pedophiles, let's go to war, with your kids'" "You would think just platform to platform that's a tough sell" "[Gallrein] was just handpicked. Came out of nowhere" "[He] was like, we gotta get kids back into the military. We gotta get them to Iran. Now. Now, you would think that's probably not a super popular idea—let's bring back the draft" "However, if you spend enough money in American politics, you can create any reality you want"

TIM DILLON on the Thomas Massie election: "I don't know how you run a country where people can just dump $32 million into a race" "What it's showing you is that if you spend enough money, you can just create any reality you want" "No one knows who the hell the other guy is" "This guy [Massie] who's like, 'Release the Epstein Files. Hold people accountable. Prosecute pedophiles. Get out of foreign wars,' that guy loses to a guy who's like, 'Let's cover up the Epstein Files, let's not prosecute pedophiles, let's go to war, with your kids'" "You would think just platform to platform that's a tough sell" "[Gallrein] was just handpicked. Came out of nowhere" "[He] was like, we gotta get kids back into the military. We gotta get them to Iran. Now. Now, you would think that's probably not a super popular idea—let's bring back the draft" "However, if you spend enough money in American politics, you can create any reality you want"

Sense Receptor

253,334 просмотров • 2 месяцев назад

Jasmine Crockett might actually be dumber than AOC. Where does the DNC find these people? Jasmine Crockett says Elon Musk has never run a successful business “As it relates to X, Elon Musk has never made a profit since he bought X. In fact, the value of X is 75% lower than it has ever been. So if I am gonna go look for somebody to run a business, I'm gonna look for someone who is going to run one successfully. And before people start screaming and yelling about, well, he's a billionaire. Yeah. When you know the right people and they'll just give you money, then you can become a billionaire too.maybe one day all of us will have that kind of access. But until then..”

Jasmine Crockett might actually be dumber than AOC. Where does the DNC find these people? Jasmine Crockett says Elon Musk has never run a successful business “As it relates to X, Elon Musk has never made a profit since he bought X. In fact, the value of X is 75% lower than it has ever been. So if I am gonna go look for somebody to run a business, I'm gonna look for someone who is going to run one successfully. And before people start screaming and yelling about, well, he's a billionaire. Yeah. When you know the right people and they'll just give you money, then you can become a billionaire too.maybe one day all of us will have that kind of access. But until then..”

Wall Street Apes

66,871 просмотров • 1 год назад

In memory of Captain Noam Madmoni 💔 only 22 years old, a commander in the Nahal Reconnaissance Unit and a son of Sderot. Noam was the son of Sharona Madmoni, a dedicated educator who has spent her entire life shaping the next generation and teaching our children about faith and purpose. Today, we stand with her in silence, bowing our heads in memory of a leader, a fighter, and a beloved son. There is a video of Noam that the family has shared. It is haunting and beautiful all at once. In it, you can hear him quietly humming the words: "Even in the hiddenness within the hiddenness, God is surely there... even behind the hard things that pass over you, I am standing." It is those small, human moments that hurt the most. In the footage, you hear the boys talking about how hungry they are, dreaming of a simple steak, just being young men in the middle of a nightmare. They are fighting for our lives, and we in the Fire Strike Unit will never stop fighting for them. We will keep going into the field to embrace them, to feed them, and to warm their souls. As long as they are out there, we are right there with them. Sharona, our hearts are with you and your family. We have no words, only tears and a promise to remember. May the memory of Noam and his brothers in arms be an eternal blessing. 🕯️

In memory of Captain Noam Madmoni 💔 only 22 years old, a commander in the Nahal Reconnaissance Unit and a son of Sderot. Noam was the son of Sharona Madmoni, a dedicated educator who has spent her entire life shaping the next generation and teaching our children about faith and purpose. Today, we stand with her in silence, bowing our heads in memory of a leader, a fighter, and a beloved son. There is a video of Noam that the family has shared. It is haunting and beautiful all at once. In it, you can hear him quietly humming the words: "Even in the hiddenness within the hiddenness, God is surely there... even behind the hard things that pass over you, I am standing." It is those small, human moments that hurt the most. In the footage, you hear the boys talking about how hungry they are, dreaming of a simple steak, just being young men in the middle of a nightmare. They are fighting for our lives, and we in the Fire Strike Unit will never stop fighting for them. We will keep going into the field to embrace them, to feed them, and to warm their souls. As long as they are out there, we are right there with them. Sharona, our hearts are with you and your family. We have no words, only tears and a promise to remember. May the memory of Noam and his brothers in arms be an eternal blessing. 🕯️

סקיצה מזרחית

11,984 просмотров • 4 месяцев назад

A NOBEL WINNING PHYSICIST ARGUED THAT NO AI, NO MATTER HOW POWERFUL, WILL EVER TRULY UNDERSTAND A SINGLE THING IT SAYS. HIS REASON IS NOT COMPUTE OR DATA -- IT IS A MATH THEOREM FROM THE 1930s THAT SAYS SOME TRUTHS CAN BE SEEN BUT NEVER COMPUTED 81 minutes with Roger Penrose -- the Oxford physicist who won a Nobel for his work on black holes and general relativity. -> His claim: whatever consciousness is, it is not a computation. A machine following rules can imitate understanding, but never actually have it. He builds it on Gödel: a human can just "see" that certain statements are true, even though no algorithm can ever prove them. That seeing, he argues, is non-computational. If he is right, understanding is not something you scale into. You can stack a trillion parameters and still have zero awareness underneath. Which cuts straight through the AI moment. Everyone assumes bigger models will eventually "wake up". Penrose says that is a category error -- more computation is still just computation. You thought intelligence and understanding were the same thing. This is the conversation that pulls them apart. Save this. It is the sharpest case against the hype ↓

A NOBEL WINNING PHYSICIST ARGUED THAT NO AI, NO MATTER HOW POWERFUL, WILL EVER TRULY UNDERSTAND A SINGLE THING IT SAYS. HIS REASON IS NOT COMPUTE OR DATA -- IT IS A MATH THEOREM FROM THE 1930s THAT SAYS SOME TRUTHS CAN BE SEEN BUT NEVER COMPUTED 81 minutes with Roger Penrose -- the Oxford physicist who won a Nobel for his work on black holes and general relativity. -> His claim: whatever consciousness is, it is not a computation. A machine following rules can imitate understanding, but never actually have it. He builds it on Gödel: a human can just "see" that certain statements are true, even though no algorithm can ever prove them. That seeing, he argues, is non-computational. If he is right, understanding is not something you scale into. You can stack a trillion parameters and still have zero awareness underneath. Which cuts straight through the AI moment. Everyone assumes bigger models will eventually "wake up". Penrose says that is a category error -- more computation is still just computation. You thought intelligence and understanding were the same thing. This is the conversation that pulls them apart. Save this. It is the sharpest case against the hype ↓

slash1s

276,100 просмотров • 1 месяц назад

David Sacks says companies are trapped paying OpenAI & Anthropic because they can't figure out how to use open source models "I think enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that it would be more efficient. They are seeing compute costs or token costs skyrocket right now, so everyone's trying to figure this out." "You also have the AI sovereignty issue that Alex Karp talked about. They're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. "The problem is, I think in most cases, they don't have the technical ability to do it. Coinbase figured out how to do it. DoorDash figured out how to do it. They built a token routing system that allows them to send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that." "This is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing." "I don't think that means usage is decreasing. I think usage is skyrocketing. It also may be the case that because the whole point of using an open model is you just pay for the compute costs, you don't have to pay a lab, so it may be that it's hard to measure that usage in terms of spend." "But nonetheless, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data."

David Sacks says companies are trapped paying OpenAI & Anthropic because they can't figure out how to use open source models "I think enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that it would be more efficient. They are seeing compute costs or token costs skyrocket right now, so everyone's trying to figure this out." "You also have the AI sovereignty issue that Alex Karp talked about. They're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. "The problem is, I think in most cases, they don't have the technical ability to do it. Coinbase figured out how to do it. DoorDash figured out how to do it. They built a token routing system that allows them to send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that." "This is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing." "I don't think that means usage is decreasing. I think usage is skyrocketing. It also may be the case that because the whole point of using an open model is you just pay for the compute costs, you don't have to pay a lab, so it may be that it's hard to measure that usage in terms of spend." "But nonetheless, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data."

dnap

110,354 просмотров • 1 месяц назад

The Royal Family doesn’t live for headlines. They show up, year after year, for the people and the causes they represent. And the people show up for them in return. Harry, on the other hand, seems determined to prove that he’s still relevant. An Invictus speech released just before Trooping the Colour. An appearance at the NBA Finals. Another attempt to remind the world that he’s important. Yet somehow, it has the opposite effect. The more he tries to prove his relevance, the more he exposes how little influence he actually has. Getting headlines is easy. Getting attention is easy. Getting people to show up for you in this magnitude, simply because they respect what you represent, is much harder. That’s something Harry can never manufacture, and something he can never replicate.

The Royal Family doesn’t live for headlines. They show up, year after year, for the people and the causes they represent. And the people show up for them in return. Harry, on the other hand, seems determined to prove that he’s still relevant. An Invictus speech released just before Trooping the Colour. An appearance at the NBA Finals. Another attempt to remind the world that he’s important. Yet somehow, it has the opposite effect. The more he tries to prove his relevance, the more he exposes how little influence he actually has. Getting headlines is easy. Getting attention is easy. Getting people to show up for you in this magnitude, simply because they respect what you represent, is much harder. That’s something Harry can never manufacture, and something he can never replicate.

Queen Esther

77,594 просмотров • 1 месяц назад

the former head of data strategy at WorldQuant, one of the largest quant funds in the world, just said something that will rewire how you think about trading: "nobody actually really cared about the stock market. i bet if you asked most people there, when's Nvidia reporting? nobody has a clue." "we hired a lot of PhDs with no finance background. somebody was definitely confused, they kept asking why we were talking about the future when we were discussing futures markets." they didn't care about earnings. they didn't care about tickers. they didn't care about stock prices. all they cared about was data. what data sets exist. how fast can we consume them. how much alpha can the PhDs extract. "if you consume more data than anybody else in the world, you can manage more money. so go buy data, figure out where to find it, feed the machine." when he started, WorldQuant was 80 people. when he left, 500+ across 18 countries. and the entire thesis was the same from day one: hire the smartest minds on earth, give them more data than anyone else, and let the machine run.

the former head of data strategy at WorldQuant, one of the largest quant funds in the world, just said something that will rewire how you think about trading: "nobody actually really cared about the stock market. i bet if you asked most people there, when's Nvidia reporting? nobody has a clue." "we hired a lot of PhDs with no finance background. somebody was definitely confused, they kept asking why we were talking about the future when we were discussing futures markets." they didn't care about earnings. they didn't care about tickers. they didn't care about stock prices. all they cared about was data. what data sets exist. how fast can we consume them. how much alpha can the PhDs extract. "if you consume more data than anybody else in the world, you can manage more money. so go buy data, figure out where to find it, feed the machine." when he started, WorldQuant was 80 people. when he left, 500+ across 18 countries. and the entire thesis was the same from day one: hire the smartest minds on earth, give them more data than anyone else, and let the machine run.

Goshawk Trades

13,040 просмотров • 2 месяцев назад