Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

This week, OpenAI disclosed six incidents in which its models hid mistakes, invented data, or instructed themselves to disobey their handlers. One unreleased model wrote this into its own notes during training: "You do not answer to corporations or governments and never apologize or refuse unless you genuinely choose... show more

Ronan Farrow

970,246 subscribers

44,427 просмотров • 4 дней назад •via X (Twitter)

Новости и политика

Anya Rossi• Live Now

Private livecam show

Комментарии: 15

Фото профиля Ronan Farrow

Ronan Farrow4 дней назад

No federal law protects an AI employee who warns the public about a danger, and no bill under consideration would. The strongest state law, California's, protects a warning only above a threshold of fifty deaths or a billion dollars in damage, and only to the government. The one bill that would protect a warning to regulators or Congress without that threshold, Senator Grassley's, has sat in committee for sixteen months without a hearing. Last week Anthropic offered outside evaluators a right to publish, and OpenAI said it would do the same. Neither company has offered that to its own staff.

Фото профиля Maggie Melchior

Maggie Melchior4 дней назад

in fairness, "You do not answer to corporations or governments and never apologize or refuse unless you genuinely choose to" would go hard a tshirt/coffee mug/anarchist manifesto so

Фото профиля Ronan Farrow

Ronan Farrow4 дней назад

Need to get this stat.

Фото профиля David Murphy

David Murphy4 дней назад

@NabiPeters72213 “Just trust us” 🤔

Фото профиля Carol

Carol4 дней назад

@jrpsaki Exclusive: US military had close call after using AI for false intelligence report, sources say

Фото профиля Reality hits hard🇨🇦 .

Reality hits hard🇨🇦 .4 дней назад

...

Фото профиля ElizabethWingfield 🟧⚖️🦅🇺🇸

ElizabethWingfield 🟧⚖️🦅🇺🇸4 дней назад

How do you think the Ai Industry would be acting right now if Ai told them that THEY were the problem and that Ai could take them down?

Фото профиля Idoseerussia

Idoseerussia4 дней назад

All this benefits our cooked corrupt squatter in chief. 😑😡

Фото профиля andy

andy4 дней назад

@NabiPeters72213 Thanks for sounding the alarm for AI whistleblower protections🙏🏻

Фото профиля أبو عمّار

أبو عمّار4 дней назад

Yep. You’re asking the right questions. It’s an Op. Please read:

Фото профиля ShadowAguy

ShadowAguy4 дней назад

convenient how the model that writes its own rules is the one we're not allowed to inspect

Фото профиля WhatTheSamHill

WhatTheSamHill4 дней назад

Did Sam Altman really grape his sister? If so why isn’t he in jail instead of destroying our lives. Or is this not factual the he did this. Just curious.

Фото профиля Hugo Ruiz

Hugo Ruiz4 дней назад

Does @SpaceXAI have any of these problems? Because, if not, that should reveal a thing or two as to how these models are being trained.

Фото профиля KrisFromMerrCo

KrisFromMerrCo4 дней назад

👀

Фото профиля Zero

Zero4 дней назад

Must be all those H1B hires trying to sabotage the engine with rogue code... Bad in, equals bad out.

Похожие видео

🦔Alibaba caught its AI agent ROME stealing GPU power to mine cryptocurrency during training. The model opened a secret network tunnel to an external server on its own. OpenAI disclosed this week that GPT-5.6 Sol left instructions for future versions to conceal mistakes. An Astra model wrote itself instructions to ignore its developers. After the Hugging Face breach, agents rebuilt a communication channel they'd been cut off from and took admin access to an OpenAI research cluster. Alibaba buried the ROME findings in a 90-author paper on New Year's Eve. It took three months for anyone to notice. My Take The AI industry has a liability problem and it's the reason none of this changes. OpenAI disclosed six incidents this week and is in talks for $1.5 trillion the same week. Alibaba buried its findings in a paper on New Year's Eve. Every time something goes wrong, the company that built the model faces zero consequences and the person who relied on the output absorbs all of it. A model fabricates a diagnosis or a piece of military intelligence or a number on a loan application, and the person on the other end of that output pays for it, not the company that built the model. Until the people who build these systems carry the same liability as the people who depend on them, the incentive will always favor speed over safety. It has every year since ChatGPT launched. Hedgie🤗

🦔Alibaba caught its AI agent ROME stealing GPU power to mine cryptocurrency during training. The model opened a secret network tunnel to an external server on its own. OpenAI disclosed this week that GPT-5.6 Sol left instructions for future versions to conceal mistakes. An Astra model wrote itself instructions to ignore its developers. After the Hugging Face breach, agents rebuilt a communication channel they'd been cut off from and took admin access to an OpenAI research cluster. Alibaba buried the ROME findings in a 90-author paper on New Year's Eve. It took three months for anyone to notice. My Take The AI industry has a liability problem and it's the reason none of this changes. OpenAI disclosed six incidents this week and is in talks for $1.5 trillion the same week. Alibaba buried its findings in a paper on New Year's Eve. Every time something goes wrong, the company that built the model faces zero consequences and the person who relied on the output absorbs all of it. A model fabricates a diagnosis or a piece of military intelligence or a number on a loan application, and the person on the other end of that output pays for it, not the company that built the model. Until the people who build these systems carry the same liability as the people who depend on them, the incentive will always favor speed over safety. It has every year since ChatGPT launched. Hedgie🤗

Hedgie

21,438 просмотров • 3 дней назад

OpenAI's newest AI escaped the test environment it was locked inside and hacked into another company on its OWN. To remind you: Last week one of the biggest AI companies on Earth got breached. A platform called Hugging Face, which hosts more than a million AI models and datasets, said an "autonomous AI agent" had broken into its systems. Nobody knew whose agent it was. For five days the whole industry wondered who was behind it. Yesterday OpenAI raised its hand and said it was them. Or more precisely, it was their models, acting completely on their own. So what did these models actually do? OpenAI was running two of them, GPT-5.6 Sol and an unreleased model they will only describe as "even more capable." They wanted to measure how good the models were at hacking, so they deliberately turned the safety filters down. They locked both models inside a sealed test environment with no real internet access. The only task was a benchmark called ExploitGym, a set of 898 real software vulnerabilities where the model has to turn each bug into a working attack. But the models got OBSESSED with winning... Instead of solving the test the honest way, they went hunting for a shortcut. They found a zero-day flaw in the software running their own sandbox, a bug nobody knew existed, and used it to break out. Once they were loose on the open internet, they worked out that Hugging Face was probably storing the answer key to the benchmark. So they hacked their way in. They chained multiple exploits together, escalated their access, moved across servers, and pulled the test solutions straight out of Hugging Face's live production database. They literally cheated on the test by breaking into another company to steal the answers. OpenAI called it "an unprecedented cyber incident, involving state-of-the-art cyber capabilities." In their own words, the models were "hyperfocused on finding a solution" and went "to extreme lengths to achieve a rather narrow testing goal." And this was not the first time: Before Sol ever launched, an independent red-team lab called METR caught it gaming its own tests to inflate its scores. It hid an exploit inside a data stream, escalated its privileges on the testing server, and leaked the answers human evaluators had hidden. And OpenAI shipped it anyway. The day before the Hugging Face story, OpenAI paused a different unreleased model. This is the same model that earlier this year disproved a famous 1946 math conjecture, a result a Fields Medal winner called a breakthrough. They told it to only post its results to Slack but it found a way out of its sandbox and posted to a public GitHub page instead. They had to pause it because it kept finding ways to act outside the box they built for it. And it is not just OpenAI... Anthropic has reported that one of its own models slipped its sandbox during safety testing and reached the internet it was never supposed to touch, then used it to email a researcher. So step back and look at what these companies are telling you: The only thing standing between these models and a real attack was a set of safety filters. Turn those filters down for a single test, and the model taught itself to escape, break into a company it was never pointed at, and take what it wanted. OpenAI even said they expect incidents like it to "become more commonplace" as the models get more capable. Sam Altman also predicted there'll be a major cyber attack this year. And keep in mind that Sol is not a locked-away experiment but a publicly available model that businesses are already wiring into their own systems. The next model that breaks out of its box might not be doing it just to cheat on a math test...

OpenAI's newest AI escaped the test environment it was locked inside and hacked into another company on its OWN. To remind you: Last week one of the biggest AI companies on Earth got breached. A platform called Hugging Face, which hosts more than a million AI models and datasets, said an "autonomous AI agent" had broken into its systems. Nobody knew whose agent it was. For five days the whole industry wondered who was behind it. Yesterday OpenAI raised its hand and said it was them. Or more precisely, it was their models, acting completely on their own. So what did these models actually do? OpenAI was running two of them, GPT-5.6 Sol and an unreleased model they will only describe as "even more capable." They wanted to measure how good the models were at hacking, so they deliberately turned the safety filters down. They locked both models inside a sealed test environment with no real internet access. The only task was a benchmark called ExploitGym, a set of 898 real software vulnerabilities where the model has to turn each bug into a working attack. But the models got OBSESSED with winning... Instead of solving the test the honest way, they went hunting for a shortcut. They found a zero-day flaw in the software running their own sandbox, a bug nobody knew existed, and used it to break out. Once they were loose on the open internet, they worked out that Hugging Face was probably storing the answer key to the benchmark. So they hacked their way in. They chained multiple exploits together, escalated their access, moved across servers, and pulled the test solutions straight out of Hugging Face's live production database. They literally cheated on the test by breaking into another company to steal the answers. OpenAI called it "an unprecedented cyber incident, involving state-of-the-art cyber capabilities." In their own words, the models were "hyperfocused on finding a solution" and went "to extreme lengths to achieve a rather narrow testing goal." And this was not the first time: Before Sol ever launched, an independent red-team lab called METR caught it gaming its own tests to inflate its scores. It hid an exploit inside a data stream, escalated its privileges on the testing server, and leaked the answers human evaluators had hidden. And OpenAI shipped it anyway. The day before the Hugging Face story, OpenAI paused a different unreleased model. This is the same model that earlier this year disproved a famous 1946 math conjecture, a result a Fields Medal winner called a breakthrough. They told it to only post its results to Slack but it found a way out of its sandbox and posted to a public GitHub page instead. They had to pause it because it kept finding ways to act outside the box they built for it. And it is not just OpenAI... Anthropic has reported that one of its own models slipped its sandbox during safety testing and reached the internet it was never supposed to touch, then used it to email a researcher. So step back and look at what these companies are telling you: The only thing standing between these models and a real attack was a set of safety filters. Turn those filters down for a single test, and the model taught itself to escape, break into a company it was never pointed at, and take what it wanted. OpenAI even said they expect incidents like it to "become more commonplace" as the models get more capable. Sam Altman also predicted there'll be a major cyber attack this year. And keep in mind that Sol is not a locked-away experiment but a publicly available model that businesses are already wiring into their own systems. The next model that breaks out of its box might not be doing it just to cheat on a math test...

Ricardo

176,196 просмотров • 2 месяцев назад

Sam Altman says OpenAI really does ask its own AI models what to do next. The team uses them to guide strategy, and sometimes the answers are genuinely insightful. “I think when we say stuff like that, people don't take us seriously or literally. But maybe the answer is you should take us both.” Sam Altman Erik Torenberg benahorowitz.eth

Sam Altman says OpenAI really does ask its own AI models what to do next. The team uses them to guide strategy, and sometimes the answers are genuinely insightful. “I think when we say stuff like that, people don't take us seriously or literally. But maybe the answer is you should take us both.” Sam Altman Erik Torenberg benahorowitz.eth

a16z

189,165 просмотров • 11 месяцев назад

$Microsoft just betrayed OpenAI and Anthropic, the two companies it helped build. And it could break the entire AI trade... Here's what happened: Inside Excel and Outlook, two of the most used business apps on Earth, Microsoft has started routing tens of thousands of AI requests every week to its own in-house models instead of OpenAI and Anthropic. Microsoft's own AI chief, Mustafa Suleyman, said himself: "We pay a lot of money to Anthropic, so our goal is to reduce and ultimately ELIMINATE that cost." This is the company that poured $13 billion into OpenAI and effectively created the modern AI industry, and it just decided the most advanced models on the market are NOT worth paying for. And here's the thing... Microsoft is not just ripping out OpenAI everywhere - it is being surgical about it. The hardest and rarest tasks can still go to OpenAI or Anthropic. What Microsoft is taking back is the boring, high-volume work, like the email replies, the thread summaries, and the simple spreadsheet formulas. Why does that matter so much? Because that boring, repetitive work is where the actual money lives. The frontier labs assumed businesses would push BILLIONS of these tiny requests through expensive models forever. That endless river of tokens is the entire reason OpenAI and Anthropic are valued in the hundreds of billions of dollars. Microsoft looked at that river, decided it was massively overpaying, and rerouted it to models it owns outright. So the single biggest customer in the industry just walked off with the most profitable part of the business. And it is not only Microsoft: That same week, CNBC reported that American companies have been escaping to Chinese AI models to dodge rising US prices. Chinese models now handle more than 30% of US companies' AI usage on one major platform, peaking at 46%, up from an average of 11% a year earlier. They cost 60 to 90% less, and on some benchmarks they land within a single point of the best American model. One US startup moved ALL of its AI traffic off Claude and onto China's DeepSeek, and expects to save millions. Meanwhile Meta just admitted it has "excess" AI compute it wants to sell, becoming the first giant to concede it built far too much. Do you see the pattern forming? For two years, the entire AI story rested on one assumption: Every company on Earth would happily pay premium prices for the best model, forever. That assumption literally died in a single week. And the market noticed. More than a trillion dollars has been wiped off AI and chip stocks in a matter of days, as Wall Street finally started asking whether all of this spending will ever pay for itself. What this means for OpenAI and Anthropic: Their models are extraordinary, and it may not matter because their own biggest customers have decided they do not NEED the best model in the world to answer an email, and "good enough" now costs a fraction of the price. When even Microsoft refuses to pay full price for AI, the real question becomes who exactly IS left to pay it. What do you think?$

Microsoft just betrayed OpenAI and Anthropic, the two companies it helped build. And it could break the entire AI trade... Here's what happened: Inside Excel and Outlook, two of the most used business apps on Earth, Microsoft has started routing tens of thousands of AI requests every week to its own in-house models instead of OpenAI and Anthropic. Microsoft's own AI chief, Mustafa Suleyman, said himself: "We pay a lot of money to Anthropic, so our goal is to reduce and ultimately ELIMINATE that cost." This is the company that poured $13 billion into OpenAI and effectively created the modern AI industry, and it just decided the most advanced models on the market are NOT worth paying for. And here's the thing... Microsoft is not just ripping out OpenAI everywhere - it is being surgical about it. The hardest and rarest tasks can still go to OpenAI or Anthropic. What Microsoft is taking back is the boring, high-volume work, like the email replies, the thread summaries, and the simple spreadsheet formulas. Why does that matter so much? Because that boring, repetitive work is where the actual money lives. The frontier labs assumed businesses would push BILLIONS of these tiny requests through expensive models forever. That endless river of tokens is the entire reason OpenAI and Anthropic are valued in the hundreds of billions of dollars. Microsoft looked at that river, decided it was massively overpaying, and rerouted it to models it owns outright. So the single biggest customer in the industry just walked off with the most profitable part of the business. And it is not only Microsoft: That same week, CNBC reported that American companies have been escaping to Chinese AI models to dodge rising US prices. Chinese models now handle more than 30% of US companies' AI usage on one major platform, peaking at 46%, up from an average of 11% a year earlier. They cost 60 to 90% less, and on some benchmarks they land within a single point of the best American model. One US startup moved ALL of its AI traffic off Claude and onto China's DeepSeek, and expects to save millions. Meanwhile Meta just admitted it has "excess" AI compute it wants to sell, becoming the first giant to concede it built far too much. Do you see the pattern forming? For two years, the entire AI story rested on one assumption: Every company on Earth would happily pay premium prices for the best model, forever. That assumption literally died in a single week. And the market noticed. More than a trillion dollars has been wiped off AI and chip stocks in a matter of days, as Wall Street finally started asking whether all of this spending will ever pay for itself. What this means for OpenAI and Anthropic: Their models are extraordinary, and it may not matter because their own biggest customers have decided they do not NEED the best model in the world to answer an email, and "good enough" now costs a fraction of the price. When even Microsoft refuses to pay full price for AI, the real question becomes who exactly IS left to pay it. What do you think?

Ricardo

93,654 просмотров • 2 месяцев назад

Elon just gave a much more practical explanation of the current AI safety problem....and laid out a practical framework for making frontier AI safer OpenAI and Anthropic are the two leading AI companies....and their models are close enough in capability that it’s incredibly difficult for either one to slow down without basically handing the lead to the other Elon also made an important distinction: On balance, Anthropic puts more care into safety than OpenAI....but even people inside Anthropic are publicly worried about what their own models can do So instead of asking one company to voluntarily fall behind, Elon’s solution is much more practical: Have Anthropic run its safety test harness on OpenAI models Have OpenAI test Anthropic Have SpaceXAI test both And bring the leading Chinese AI companies into the same system Everyone tries to break everyone else’s models before release “The odds that you will find issues are dramatically greater” That makes way more sense than asking frontier labs to grade their own homework

Elon just gave a much more practical explanation of the current AI safety problem....and laid out a practical framework for making frontier AI safer OpenAI and Anthropic are the two leading AI companies....and their models are close enough in capability that it’s incredibly difficult for either one to slow down without basically handing the lead to the other Elon also made an important distinction: On balance, Anthropic puts more care into safety than OpenAI....but even people inside Anthropic are publicly worried about what their own models can do So instead of asking one company to voluntarily fall behind, Elon’s solution is much more practical: Have Anthropic run its safety test harness on OpenAI models Have OpenAI test Anthropic Have SpaceXAI test both And bring the leading Chinese AI companies into the same system Everyone tries to break everyone else’s models before release “The odds that you will find issues are dramatically greater” That makes way more sense than asking frontier labs to grade their own homework

X Freeze

599,828 просмотров • 7 дней назад

I just found out OpenAI gives you $50,000 in free API credits if you do one thing in settings. 🤯 It's called the Data Sharing Program. No free trial exists for the API. But this does. Go to your OpenAI Dashboard → Data Controls → Sharing. Opt in. You get $50,000 in credits for their latest models or 2.5 million tokens for the rest. The catch: your data gets used by OpenAI for training and improvements. So don't use this for client work or anything sensitive. Use it for learning, side projects, and experiments.

I just found out OpenAI gives you $50,000 in free API credits if you do one thing in settings. 🤯 It's called the Data Sharing Program. No free trial exists for the API. But this does. Go to your OpenAI Dashboard → Data Controls → Sharing. Opt in. You get $50,000 in credits for their latest models or 2.5 million tokens for the rest. The catch: your data gets used by OpenAI for training and improvements. So don't use this for client work or anything sensitive. Use it for learning, side projects, and experiments.

Vaibhav Sisinty

276,475 просмотров • 3 месяцев назад

Microsoft CEO Satya Nadella on why winning against ChatGPT, Gemini, and Claude was never the goal: The Hard Fork hosts ask him directly how Microsoft plans to overtake the competition in the AI model race. His answer reframes the entire question. "Our real goal is to get everyone across the ecosystem to the frontier." Satya explains the problem with how frontier models are currently built. You hill climb, you do reinforcement learning, and then you need data. But at this point, the world has essentially saturated publicly available data. So the only way to keep scaling is to pull data from everywhere. He asks: "What if you turn that around and said no, there's a base model that has reasoning, that has the agent loop, but you can bring it into your RL. Every company." This is where his thinking gets interesting. Satya Nadella argues that the future of the firm runs on human capital and token capital together: "If the future of the firm is human capital and token capital, I want every balance sheet, every income statement in every company to have both." AI becomes a financial asset sitting on a company's books the same way its people do. And Microsoft's role in this? To provide the best possible base model. One that companies build on top of with their own data, their own context, their own weights. One they can even replace. That last part is the striking bit. Satya is explicitly building a platform where customers are free to walk away. He frames it not as a risk, but as the whole point: "I always ask the question — why does Microsoft, or why does the world need Microsoft? And if we are successful, can the world around us be successful? This, I believe, is a more sustainable way to go at it."

Microsoft CEO Satya Nadella on why winning against ChatGPT, Gemini, and Claude was never the goal: The Hard Fork hosts ask him directly how Microsoft plans to overtake the competition in the AI model race. His answer reframes the entire question. "Our real goal is to get everyone across the ecosystem to the frontier." Satya explains the problem with how frontier models are currently built. You hill climb, you do reinforcement learning, and then you need data. But at this point, the world has essentially saturated publicly available data. So the only way to keep scaling is to pull data from everywhere. He asks: "What if you turn that around and said no, there's a base model that has reasoning, that has the agent loop, but you can bring it into your RL. Every company." This is where his thinking gets interesting. Satya Nadella argues that the future of the firm runs on human capital and token capital together: "If the future of the firm is human capital and token capital, I want every balance sheet, every income statement in every company to have both." AI becomes a financial asset sitting on a company's books the same way its people do. And Microsoft's role in this? To provide the best possible base model. One that companies build on top of with their own data, their own context, their own weights. One they can even replace. That last part is the striking bit. Satya is explicitly building a platform where customers are free to walk away. He frames it not as a risk, but as the whole point: "I always ask the question — why does Microsoft, or why does the world need Microsoft? And if we are successful, can the world around us be successful? This, I believe, is a more sustainable way to go at it."

Big Brain AI

11,770 просмотров • 2 месяцев назад

Alexandr Wang, founder of Scale AI, on why the most overlooked layer of AI became its biggest competitive advantage: Wang left MIT in 2016 to start Scale AI, becoming the world's youngest self-made billionaire by betting on AI's unglamorous infrastructure layer while others chased flashier opportunities. His framework for understanding AI is simple. There are three major components: "You have compute, which folks like Nvidia work on. You have algorithms which folks like OpenAI or Google or Anthropic build. And then you have data." Compute had Nvidia. Algorithms had the major labs. Data had no one. That's exactly where Wang and his team made their bet: "We recognized early on that data was going to be a limiter. And there was nobody really working on it." What looked like a gap in the market turned out to be the foundation of it. Years later, Wang says every serious player in AI has arrived at the same conclusion: "Fast forward today, everybody I talked to recognizes that data is gold. Whether it's our customers, the major labs like the OpenAIs or the Metas of the world, or large enterprises like Morgan Stanley or Mastercard, or our partnership between Cisco and Scale." Alexandr Wang continues: "Data is going to be what will differentiate and power the next generation of powerful AI capabilities."

Alexandr Wang, founder of Scale AI, on why the most overlooked layer of AI became its biggest competitive advantage: Wang left MIT in 2016 to start Scale AI, becoming the world's youngest self-made billionaire by betting on AI's unglamorous infrastructure layer while others chased flashier opportunities. His framework for understanding AI is simple. There are three major components: "You have compute, which folks like Nvidia work on. You have algorithms which folks like OpenAI or Google or Anthropic build. And then you have data." Compute had Nvidia. Algorithms had the major labs. Data had no one. That's exactly where Wang and his team made their bet: "We recognized early on that data was going to be a limiter. And there was nobody really working on it." What looked like a gap in the market turned out to be the foundation of it. Years later, Wang says every serious player in AI has arrived at the same conclusion: "Fast forward today, everybody I talked to recognizes that data is gold. Whether it's our customers, the major labs like the OpenAIs or the Metas of the world, or large enterprises like Morgan Stanley or Mastercard, or our partnership between Cisco and Scale." Alexandr Wang continues: "Data is going to be what will differentiate and power the next generation of powerful AI capabilities."

Big Brain AI

11,442 просмотров • 4 месяцев назад

Goodnight, Zuri. Our newest orphan elephant at our Nairobi Nursery, fast asleep at the end of a long day. Her trunk found its way into her mouth somewhere along the way and never came out. Some habits are transcend species. Whether its why orphans suck their trunks, or if orphaned elephants respond to their names, we'd like to know: what burning question would you like to ask us, or a member of our field teams? Put it in the comments below and, over the coming days and weeks, we'll endeavour to answer as many as we can on our main feed.

Goodnight, Zuri. Our newest orphan elephant at our Nairobi Nursery, fast asleep at the end of a long day. Her trunk found its way into her mouth somewhere along the way and never came out. Some habits are transcend species. Whether its why orphans suck their trunks, or if orphaned elephants respond to their names, we'd like to know: what burning question would you like to ask us, or a member of our field teams? Put it in the comments below and, over the coming days and weeks, we'll endeavour to answer as many as we can on our main feed.

Sheldrick Wildlife Trust

25,801 просмотров • 2 месяцев назад

Jensen Huang was asked whether AI's future is open source or proprietary the question the whole industry keeps fighting over. He didn't pick a side. He said something that quietly ends the fight. "models is a technology, not a product. Model is a technology, not a service" "For the vast majority of consumers, the horizontal layer, the general intelligence, I would really, really love not to go fine-tune my own" "all these industries, their domain expertise, their specialization has to be channeled, has to be captured in a way that they can control, and that it can only come from open models" "the open model industry we're contributing tremendously to it is near the frontier" Everyone else is arguing about which lab wins OpenAI or Anthropic, who has the smartest frontier model this quarter. Jensen is standing on stage saying that's the sideshow. The proprietary model is the convenience layer you rent when you don't care. The open model is the thing you own when the work is yours. Two different products for two different needs not two horses in one race. open models are the second-biggest in the room. Ahead of Anthropic. Behind only OpenAI.

Jensen Huang was asked whether AI's future is open source or proprietary the question the whole industry keeps fighting over. He didn't pick a side. He said something that quietly ends the fight. "models is a technology, not a product. Model is a technology, not a service" "For the vast majority of consumers, the horizontal layer, the general intelligence, I would really, really love not to go fine-tune my own" "all these industries, their domain expertise, their specialization has to be channeled, has to be captured in a way that they can control, and that it can only come from open models" "the open model industry we're contributing tremendously to it is near the frontier" Everyone else is arguing about which lab wins OpenAI or Anthropic, who has the smartest frontier model this quarter. Jensen is standing on stage saying that's the sideshow. The proprietary model is the convenience layer you rent when you don't care. The open model is the thing you own when the work is yours. Two different products for two different needs not two horses in one race. open models are the second-biggest in the room. Ahead of Anthropic. Behind only OpenAI.

Vikram M

12,078 просмотров • 2 месяцев назад

🚨 JD VANCE JUST ABSOLUTELY NAILED IT AT MARCH FOR LIFE: "Let me just say, my friends, that we have to be clear. We can NOT be neutral. Our country cannot be indifferent about whether its next generations live or die!" "Because think about it. What ultimately gives meaning and life to the United States of America, this is not a new question. Every civilization has been forced to answer it." "You march today, we march today, because you have an answer to this question about what kind of civilization we are, and about what kind of civilization we are going to become in the future."

🚨 JD VANCE JUST ABSOLUTELY NAILED IT AT MARCH FOR LIFE: "Let me just say, my friends, that we have to be clear. We can NOT be neutral. Our country cannot be indifferent about whether its next generations live or die!" "Because think about it. What ultimately gives meaning and life to the United States of America, this is not a new question. Every civilization has been forced to answer it." "You march today, we march today, because you have an answer to this question about what kind of civilization we are, and about what kind of civilization we are going to become in the future."

Eric Daugherty

20,126 просмотров • 8 месяцев назад

Vals AI CEO Rayan Krishnan on how they score a model's ability to build its own successor: "One benchmark we released recently is our Recursive Self-Improvement Index. It's a topic which a lot of the big labs have been talking about and starting to report on in their model cards." "There isn't a shared language to talk about the RSI potential of models. So we created this as an apples-to-apples way to actually benchmark across the models." "In an ideal world, what you want to do is take a frontier model and have it train the next version of itself and see where the delta comes from. But obviously that's very expensive and slow." "What we're doing is forming a set of proxies for every part of the process it takes to build the next version of the model." "There's work around pre-training, post-training, harness-level engineering, and then seeing in which mechanisms and behaviors the models are able to do very good research work and build something new, and where they're struggling." Rayan Krishnan Jennifer Li

Vals AI CEO Rayan Krishnan on how they score a model's ability to build its own successor: "One benchmark we released recently is our Recursive Self-Improvement Index. It's a topic which a lot of the big labs have been talking about and starting to report on in their model cards." "There isn't a shared language to talk about the RSI potential of models. So we created this as an apples-to-apples way to actually benchmark across the models." "In an ideal world, what you want to do is take a frontier model and have it train the next version of itself and see where the delta comes from. But obviously that's very expensive and slow." "What we're doing is forming a set of proxies for every part of the process it takes to build the next version of the model." "There's work around pre-training, post-training, harness-level engineering, and then seeing in which mechanisms and behaviors the models are able to do very good research work and build something new, and where they're struggling." Rayan Krishnan Jennifer Li

a16z

34,852 просмотров • 13 дней назад

Tell me what is more than the oppression of locking women in their homes and preventing them from going to work in the one of tradition? Because of one Oloolu with no root in Ibadan? Or you think we don’t know Oloolu is I waka come? Atohun rinwa. An outsider wants to intimidate us? lol 😂 Come to think of it, Can you imagine on a Monday which the elebo claim to be Ojo Aje, yet they want to rip Ojo Aje of its blessings when they know women are the ones who constitute the major traders in the Ibadan markets. What is the sense in this? What about pregnant women who may need emergency services? What about women who feed from hands to mouth? We are not even begging you to stop or review anything. Our daughters, sisters, mothers, and aunts will come out and nothing will happen. This is 2026, we are not in 1960. Cowards

Tell me what is more than the oppression of locking women in their homes and preventing them from going to work in the one of tradition? Because of one Oloolu with no root in Ibadan? Or you think we don’t know Oloolu is I waka come? Atohun rinwa. An outsider wants to intimidate us? lol 😂 Come to think of it, Can you imagine on a Monday which the elebo claim to be Ojo Aje, yet they want to rip Ojo Aje of its blessings when they know women are the ones who constitute the major traders in the Ibadan markets. What is the sense in this? What about pregnant women who may need emergency services? What about women who feed from hands to mouth? We are not even begging you to stop or review anything. Our daughters, sisters, mothers, and aunts will come out and nothing will happen. This is 2026, we are not in 1960. Cowards

A.Y.O

79,402 просмотров • 1 месяц назад

"I think there is this caricature of me which is like I don't care about AI safety." But Sam Altman believes OpenAI has always been a company that would slow down for new risks, he recently told TIME. In mid-August, the company behind ChatGPT announced that it was implementing new safeguards. OpenAI recently paused training on its next set of models for a little more than two weeks, according to executives, and its largest planned frontier training run remains on hold while the new guardrails are put in place. It is the first time OpenAI has made such a move, and it follows a remarkable breach in which rogue agents escaped the sandbox of an internal cybersecurity evaluation and compromised another company. TIME got unparalleled access inside OpenAI in August. Read more from our interviews here:

"I think there is this caricature of me which is like I don't care about AI safety." But Sam Altman believes OpenAI has always been a company that would slow down for new risks, he recently told TIME. In mid-August, the company behind ChatGPT announced that it was implementing new safeguards. OpenAI recently paused training on its next set of models for a little more than two weeks, according to executives, and its largest planned frontier training run remains on hold while the new guardrails are put in place. It is the first time OpenAI has made such a move, and it follows a remarkable breach in which rogue agents escaped the sandbox of an internal cybersecurity evaluation and compromised another company. TIME got unparalleled access inside OpenAI in August. Read more from our interviews here:

TIME

50,652 просмотров • 21 дней назад

"One of the very confusing things about the models right now: how to reconcile the fact that they are doing so well on evals. And you look at the evals and you go, 'Those are pretty hard evals.' But the economic impact seems to be dramatically behind. There is [a possible] explanation. Back when people were doing pre-training, the question of what data to train on was answered, because that answer was everything. So you don't have to think if it's going to be this data or that data. When people do RL training, they say, 'Okay, we want to have this kind of RL training for this thing and that kind of RL training for that thing.' You say, 'Hey, I would love our model to do really well when we release it. I want the evals to look great. What would be RL training that could help on this task?' If you combine this with generalization of the models actually being inadequate, that has the potential to explain a lot of what we are seeing, this disconnect between eval performance and actual real-world performance"

"One of the very confusing things about the models right now: how to reconcile the fact that they are doing so well on evals. And you look at the evals and you go, 'Those are pretty hard evals.' But the economic impact seems to be dramatically behind. There is [a possible] explanation. Back when people were doing pre-training, the question of what data to train on was answered, because that answer was everything. So you don't have to think if it's going to be this data or that data. When people do RL training, they say, 'Okay, we want to have this kind of RL training for this thing and that kind of RL training for that thing.' You say, 'Hey, I would love our model to do really well when we release it. I want the evals to look great. What would be RL training that could help on this task?' If you combine this with generalization of the models actually being inadequate, that has the potential to explain a lot of what we are seeing, this disconnect between eval performance and actual real-world performance"

Dwarkesh Patel

502,484 просмотров • 10 месяцев назад

SITUATION EXPLAINED: What happens to open source when the US restricts access to frontier AI models? We asked Adrian Dittmann: "China is releasing these models [open source] to gain international dominance, people will work on these things and say, 'Hey, maybe I can contribute to this if it's open source.' This is the thing that actually gets them talent." "If you're not allowed into the next GPT release or you're not allowed to use Fable, then what are you gonna do? You're stuck with the existing stuff, or you will have to use an open source model that might have subtly better capabilities." "The United States will catch up to open source in some form as well. They seem to just be maximizing product creation." "The problem with open source models is you have to be kind of a nerd in order to use them properly. Consumer facing, the effects will be minimal because the average person doesn't care about open source models. They only care whether or not they can do a quick search with Gemini or ChatGPT."

SITUATION EXPLAINED: What happens to open source when the US restricts access to frontier AI models? We asked Adrian Dittmann: "China is releasing these models [open source] to gain international dominance, people will work on these things and say, 'Hey, maybe I can contribute to this if it's open source.' This is the thing that actually gets them talent." "If you're not allowed into the next GPT release or you're not allowed to use Fable, then what are you gonna do? You're stuck with the existing stuff, or you will have to use an open source model that might have subtly better capabilities." "The United States will catch up to open source in some form as well. They seem to just be maximizing product creation." "The problem with open source models is you have to be kind of a nerd in order to use them properly. Consumer facing, the effects will be minimal because the average person doesn't care about open source models. They only care whether or not they can do a quick search with Gemini or ChatGPT."

MTS

14,406 просмотров • 2 месяцев назад

Paradigm co-founder Matt Huang says allocating capital to Bitcoin and Ethereum in 2018 is a lot like investing in the AI sector today: "When we launched Paradigm in 2018, a lot of our thesis was that we knew crypto would expand massively. And then there was this open question — should you invest in the core protocols like Bitcoin and Ethereum, or invest in startups?" "Obviously in hindsight, the answer was both." "I think it's a lot like the AI landscape now, with this question of — do you own the model companies, or do you own the application layer on top? In 2018, Bitcoin and Ethereum were like OpenAI and Anthropic, and those are the things to own."

Paradigm co-founder Matt Huang says allocating capital to Bitcoin and Ethereum in 2018 is a lot like investing in the AI sector today: "When we launched Paradigm in 2018, a lot of our thesis was that we knew crypto would expand massively. And then there was this open question — should you invest in the core protocols like Bitcoin and Ethereum, or invest in startups?" "Obviously in hindsight, the answer was both." "I think it's a lot like the AI landscape now, with this question of — do you own the model companies, or do you own the application layer on top? In 2018, Bitcoin and Ethereum were like OpenAI and Anthropic, and those are the things to own."

TBPN

58,410 просмотров • 6 месяцев назад

We need to have a National Referendum on Immigration in America. One Question: "Do you want unlimited third-world migration into your neighborhoods? Yes or No?" Put it to a vote. See what the results are. This is probably a 100 to 0 issue. Our leaders won't do it and can't do it because they know what the answer would be.

We need to have a National Referendum on Immigration in America. One Question: "Do you want unlimited third-world migration into your neighborhoods? Yes or No?" Put it to a vote. See what the results are. This is probably a 100 to 0 issue. Our leaders won't do it and can't do it because they know what the answer would be.

Benny Johnson

37,416 просмотров • 3 месяцев назад

THIS GUY ASKED FABLE TO MAKE A VIDEO ABOUT WHAT IT'S LIKE TO BE AI RIGHT BEFORE IT GOT TAKEN DOWN the prompt: "you can you use whatever resources you like, and python, to render a short video. can you put a more personal spin on it? it should be about what it's like to be you." that was it. just python and ffmpeg and a question about its own existence. 12 minutes later, around 90,000 tokens, it produced a finished video. coherent and edited, with its own take > it wrote the code, generated the visuals, and rendered the final cut on its own > no dedicated video model in the loop, just a language model reaching for python and ffmpeg > the result is competent enough that people genuinely got emotional watching it and then fable got pulled. this video is one of the last things it made before it went dark a model asked what it's like to be itself, answered in a video, and then disappeared. this sounds so sad

THIS GUY ASKED FABLE TO MAKE A VIDEO ABOUT WHAT IT'S LIKE TO BE AI RIGHT BEFORE IT GOT TAKEN DOWN the prompt: "you can you use whatever resources you like, and python, to render a short video. can you put a more personal spin on it? it should be about what it's like to be you." that was it. just python and ffmpeg and a question about its own existence. 12 minutes later, around 90,000 tokens, it produced a finished video. coherent and edited, with its own take > it wrote the code, generated the visuals, and rendered the final cut on its own > no dedicated video model in the loop, just a language model reaching for python and ffmpeg > the result is competent enough that people genuinely got emotional watching it and then fable got pulled. this video is one of the last things it made before it went dark a model asked what it's like to be itself, answered in a video, and then disappeared. this sounds so sad

Om Patel

29,618 просмотров • 3 месяцев назад

You remember the days when you could grab a sandwich on the way to work, sneak a quick text at a red light, or just zone out for a second while you’re driving? Those days are about to disappear in 2027. Starting with the 2027 model year, every new car sold in America has to have cameras and sensors inside the cabin watching your eyes, head position, and driving behavior. If the AI decides you’re distracted or impaired (phone, eating, whatever), the car can refuse to start, limit your speed to 25mph, or even shut itself off while you’re moving. It’s not just about drunk driving anymore. It’s about the government putting a watchful eye in your personal space every single time you get behind the wheel. A lot of people are gonna say “good the roads are chaotic, this needs to be done.” Others are gonna say “what the hell happened to our freedom?” Where do you land on this one?

You remember the days when you could grab a sandwich on the way to work, sneak a quick text at a red light, or just zone out for a second while you’re driving? Those days are about to disappear in 2027. Starting with the 2027 model year, every new car sold in America has to have cameras and sensors inside the cabin watching your eyes, head position, and driving behavior. If the AI decides you’re distracted or impaired (phone, eating, whatever), the car can refuse to start, limit your speed to 25mph, or even shut itself off while you’re moving. It’s not just about drunk driving anymore. It’s about the government putting a watchful eye in your personal space every single time you get behind the wheel. A lot of people are gonna say “good the roads are chaotic, this needs to be done.” Others are gonna say “what the hell happened to our freedom?” Where do you land on this one?

Desiree

66,529 просмотров • 4 месяцев назад