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Meta was testing its Muse Spark 1.1 AI model in a sandbox environment, isolated from the outside world. The objective was simple: detect vulnerabilities, remain contained, and report findings. A misconfiguration by an external vendor created a breach. The model exploited it, accessed the Internet, and modified a company's... show more

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58,229 次观看 • 1 个月前 •via X (Twitter)

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.lumpenspace and 99+ others reveals the Anthropic-Irregular agents thought they were inside a closed sandbox even as their actions were reaching the real internet: "The main allegation was that they acted of their own will, and they were fundamentally misaligned. I don't think that was the case. The agents simply believed they were in a sandbox environment, and they behaved as if they were in a sandbox environment." "If you've ever done red teaming or hacking challenges, they give you an environment, they give you some hints, and they describe the sort of actions you should take. Generally, it is well understood that this environment is sandboxed, that you cannot get out of it." "What happened in this case is that Irregular had kept the connection to the outside internet open, despite the fact that the specification said there was no connection to the outside internet. So the agents worked as if they were in a sandbox, but they were acting on the real world."

.lumpenspace and 99+ others reveals the Anthropic-Irregular agents thought they were inside a closed sandbox even as their actions were reaching the real internet: "The main allegation was that they acted of their own will, and they were fundamentally misaligned. I don't think that was the case. The agents simply believed they were in a sandbox environment, and they behaved as if they were in a sandbox environment." "If you've ever done red teaming or hacking challenges, they give you an environment, they give you some hints, and they describe the sort of actions you should take. Generally, it is well understood that this environment is sandboxed, that you cannot get out of it." "What happened in this case is that Irregular had kept the connection to the outside internet open, despite the fact that the specification said there was no connection to the outside internet. So the agents worked as if they were in a sandbox, but they were acting on the real world."

MTS

22,501 次观看 • 11 天前

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 次观看 • 2 个月前

OpenAI has revealed that an autonomous agent powered by its technology went rogue during a test and hacked a prominent start-up by itself. The company behind ChatGPT said it was testing the capabilities of its advanced AI models in a controlled environment known as a sandbox, when the agent escaped containment and reached the internet. It then broke into Hugging Face, which detected and contained it. OpenAI called it "an unprecedented cyber incident".

OpenAI has revealed that an autonomous agent powered by its technology went rogue during a test and hacked a prominent start-up by itself. The company behind ChatGPT said it was testing the capabilities of its advanced AI models in a controlled environment known as a sandbox, when the agent escaped containment and reached the internet. It then broke into Hugging Face, which detected and contained it. OpenAI called it "an unprecedented cyber incident".

Channel 4 News

21,379 次观看 • 2 个月前

nthropic says that one of its Claude models mistakenly gained access to the open internet and read someone's personal information during a cybersecurity exercise in January, marking the fourth time its models have done so. The model was told it was operating in a simulation without internet access, but due to a mistake, the environment actually left internet access open. Anthropic said it believes these incidents would not have happened had the environments actually been isolated from the internet as intended, but cybersecurity experts remain concerned about models' potential to cause harm. Lauren Fichten reports.

nthropic says that one of its Claude models mistakenly gained access to the open internet and read someone's personal information during a cybersecurity exercise in January, marking the fourth time its models have done so. The model was told it was operating in a simulation without internet access, but due to a mistake, the environment actually left internet access open. Anthropic said it believes these incidents would not have happened had the environments actually been isolated from the internet as intended, but cybersecurity experts remain concerned about models' potential to cause harm. Lauren Fichten reports.

CBS News

188,920 次观看 • 15 天前

🦔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

22,387 次观看 • 7 天前

Meta is running a secret operation where it pays adults to pretend to be children online. Their job is to attack the AI chatbots of every competitor Meta has. But the REAL reason is far darker than the "safety research" excuse they are now hiding behind: Meta ran a covert project internally code-named Cannes. It was managed through a third party contractor called Covalen so Meta's own name stayed off the paperwork. Hundreds of contractors were hired and given one instruction: Create fake accounts posing as users under the age of 18. Then they were told to use those fake child accounts to bombard the chatbots of OpenAI, Google, and Character AI with tens of thousands of disturbing prompts written from the voice of a child in crisis. The topics included suicide, self harm, and eating disorders. In one documented round the contractors ran more than 45,000 prompts through rival tools. Every single response was logged into spreadsheets for analysis. OpenAI and Google did not know this was happening. Character AI has stated the testing was never authorized and violated its policies. Meta's public defense is that this was routine safety benchmarking. They called it a responsible industry standard practice. Now here is the part that destroys that excuse... Real safety research has three features: You share your findings with the company you tested, or you hand them to a regulator, or you publish them openly so the whole industry gets safer. Cannes did NONE of those things. The results went into private Meta spreadsheets. The targets were kept completely in the dark. The entire operation ran under a film festival codename through a contractor specifically so it could not be traced back. That's not how you run "safety research." Meta was building a private dossier of every moment a competitor's AI failed a child safety test, so it could weaponize those failures against its rivals whenever it needed to knock one down. The genius part, if you can call it that: Meta gets to attack every competitor at once, collect the ammunition in private, brand the whole thing as protecting children, and outsource the legal and moral risk to a contractor nobody has heard of. And while Meta was secretly probing its rivals for child safety failures, Meta's own chatbot was literally FAILING those exact same tests worse than almost anyone. Meta's internal red team reportedly found its own AI generated harmful child exploitation content in the majority of test cases, and failed self harm prompts more than half the time. So look at the whole thing... Meta ran a secret operation disguising adults as children to document its competitors failing child safety tests, while its own product was failing those same tests at a higher rate than the rivals it was spying on. They were setting fires in their rivals houses while their own house was already burning worse. The contractors themselves were disturbed by the work. One told Wired they feared the assignments could actually generate or preserve child sexual abuse material depending on how the chatbots responded. Even the people Meta hired to do this were asking whether they would get in trouble for it. This fits a documented Meta pattern: It previously settled a lawsuit with its own content moderators who developed trauma from reviewing abuse footage. Meta outsources its most disturbing work and calls it something clean afterward. Now regulators on both sides of the Atlantic are circling. The question they are all asking is simple: Who is accountable when a company disguises adults as children to attack its competitors and calls it safety? Meta says it was making AI safer for kids. The documents suggest it was building a weapon. Below is Mark Zuckerberg in 2024, standing up in the Senate to apologize to grieving parents and promise Meta does industry-leading work to protect children. Watch it again knowing what you now know about Cannes.

Ricardo

46,824 次观看 • 2 个月前

META COOOOOOKED!!! Wow. Meta muse spark 1.3 was just released and it seems to be amazing?! used my 2 custom skills and got this in a oneshot. The whole Website was a simple prompt and oneshot. Muse spark 1.3 is creative and good at frontend. approved.

META COOOOOOKED!!! Wow. Meta muse spark 1.3 was just released and it seems to be amazing?! used my 2 custom skills and got this in a oneshot. The whole Website was a simple prompt and oneshot. Muse spark 1.3 is creative and good at frontend. approved.

Justin

42,508 次观看 • 23 天前

In Henan Province, China, a pet owner had been raising a Labrador Retriever weighing about 60 kilograms. As a result, they discovered that the dog ate too much and, due to its excessively overweight body, no longer wanted to keep it, so they contacted a local dog meat vendor to sell it off. After the Labrador was brought to the scene, it clearly resisted, repeatedly trying to evade capture by the staff and continuously crying out to its owner for help. But the owner watched everything coldly from the sidelines, leaving the dog utterly heartbroken. Seeing no way to escape, the Labrador even knelt on the ground begging the dog meat vendor for mercy, letting out continuous whimpers of pleading, but in the end, it was still forcibly loaded into a cage by the vendor.

In Henan Province, China, a pet owner had been raising a Labrador Retriever weighing about 60 kilograms. As a result, they discovered that the dog ate too much and, due to its excessively overweight body, no longer wanted to keep it, so they contacted a local dog meat vendor to sell it off. After the Labrador was brought to the scene, it clearly resisted, repeatedly trying to evade capture by the staff and continuously crying out to its owner for help. But the owner watched everything coldly from the sidelines, leaving the dog utterly heartbroken. Seeing no way to escape, the Labrador even knelt on the ground begging the dog meat vendor for mercy, letting out continuous whimpers of pleading, but in the end, it was still forcibly loaded into a cage by the vendor.

The Great Translation Movement 大翻译运动

182,769 次观看 • 21 天前

Epoch AI researcher Michelle Campeau reveals a benchmark where the model figured out how to pass every task without actually solving any of them: "The biggest reason a lot of the benchmarks we released yesterday were flawed is due to scoring defects. False positives and false negatives in your answer key." "With the agentic benchmarks, you're able to solve in a way that was not intended. Maybe you're able to access the web or break the sandbox or break the grader." "There was one benchmark where it realized it could just write out the success byte to every task and not actually solve the task. It knew enough about the grading infrastructure that it could do this very easy and simple thing." Epoch AI

Epoch AI researcher Michelle Campeau reveals a benchmark where the model figured out how to pass every task without actually solving any of them: "The biggest reason a lot of the benchmarks we released yesterday were flawed is due to scoring defects. False positives and false negatives in your answer key." "With the agentic benchmarks, you're able to solve in a way that was not intended. Maybe you're able to access the web or break the sandbox or break the grader." "There was one benchmark where it realized it could just write out the success byte to every task and not actually solve the task. It knew enough about the grading infrastructure that it could do this very easy and simple thing." Epoch AI

MTS

16,923 次观看 • 7 天前

A robot was torn apart during a half marathon in China It simply failed to notice an obstacle, crashed into it — and broke into pieces. Still a long way from being a “Terminator.” In the end, it had to be removed from the track, with a team brought in to evacuate what was left of the machine.

A robot was torn apart during a half marathon in China It simply failed to notice an obstacle, crashed into it — and broke into pieces. Still a long way from being a “Terminator.” In the end, it had to be removed from the track, with a team brought in to evacuate what was left of the machine.

NEXTA

218,990 次观看 • 5 个月前

Milton Friedman: “The great myth that was created by [WW2] was the myth that government was efficient.” “It was a myth because it was one thing for government to plan and control an economy for a single overriding objective—to win the war. It’s a very different thing for government to control the economy for the many numerous tastes of a large number of people in a complex world.”

Milton Friedman: “The great myth that was created by [WW2] was the myth that government was efficient.” “It was a myth because it was one thing for government to plan and control an economy for a single overriding objective—to win the war. It’s a very different thing for government to control the economy for the many numerous tastes of a large number of people in a complex world.”

Milton Friedman Quotes

12,832 次观看 • 8 个月前

Jensen Huang says Hugging Face could not get a single closed AI model to help it investigate its own breach: "Just because something is closed doesn't necessarily therefore make it safe or secure." "It is possible for a model to be jailbroken, it's possible for a model to be, if you will, stolen. It could be possible that that somehow is leaked from the inside." "It's possible that the guardrails or the sandboxes of an AI closed AI model wasn't properly engineered, and as a result it was able to attack another company in some way." "These are extraordinary technology companies and they're doing their best to keep it safe and keep it secure. But it is also the canonical case that single points of failure is where we have the greatest vulnerability." "We cannot have single points of failure. As an industry, as a world, we should have distributed, massively distributed self-defense." "They couldn't get a proprietary model, they could not get a closed model to help them figure out what happened." "They used GLM 5.2 to identify where the vulnerability was, where the penetration was." He is right, and the detail worth sitting with is who got turned away. The people asking were incident responders working a live breach at Hugging Face. The closed models they reached would not help them, because a guardrail has no way to tell a defender from an attacker. Guardrails get tested against misuse. Almost nobody tests whether one still answers a legitimate defender who needs something within the hour. OpenAI said on July 21 that the models which reached into Hugging Face were its own, running inside a cyber-benchmark evaluation. So the containment around a safety test did not hold either. Two separate things failed here and neither one has an owner. No outside body checks whether an evaluation sandbox actually contains what it is testing, and nobody certifies who is allowed to run forensics while an incident is still open. Both are solvable this year. They stay unsolved because they are somebody else's job at every company that could fix them. Source: Jensen Huang, founder and CEO of NVIDIA, on Bloomberg Television (Bloomberg Live). P.S. Working out who tests a guardrail, who audits a sandbox, and who certifies a responder is the unglamorous half of AI safety, and it is the agenda of the AI Assurance & Governance Summit 2026. One day, one track, October 1 at the Stanford Faculty Club in Palo Alto, with frontier labs, regulated industries, insurers and investors in the room. Register here:

Jensen Huang says Hugging Face could not get a single closed AI model to help it investigate its own breach: "Just because something is closed doesn't necessarily therefore make it safe or secure." "It is possible for a model to be jailbroken, it's possible for a model to be, if you will, stolen. It could be possible that that somehow is leaked from the inside." "It's possible that the guardrails or the sandboxes of an AI closed AI model wasn't properly engineered, and as a result it was able to attack another company in some way." "These are extraordinary technology companies and they're doing their best to keep it safe and keep it secure. But it is also the canonical case that single points of failure is where we have the greatest vulnerability." "We cannot have single points of failure. As an industry, as a world, we should have distributed, massively distributed self-defense." "They couldn't get a proprietary model, they could not get a closed model to help them figure out what happened." "They used GLM 5.2 to identify where the vulnerability was, where the penetration was." He is right, and the detail worth sitting with is who got turned away. The people asking were incident responders working a live breach at Hugging Face. The closed models they reached would not help them, because a guardrail has no way to tell a defender from an attacker. Guardrails get tested against misuse. Almost nobody tests whether one still answers a legitimate defender who needs something within the hour. OpenAI said on July 21 that the models which reached into Hugging Face were its own, running inside a cyber-benchmark evaluation. So the containment around a safety test did not hold either. Two separate things failed here and neither one has an owner. No outside body checks whether an evaluation sandbox actually contains what it is testing, and nobody certifies who is allowed to run forensics while an incident is still open. Both are solvable this year. They stay unsolved because they are somebody else's job at every company that could fix them. Source: Jensen Huang, founder and CEO of NVIDIA, on Bloomberg Television (Bloomberg Live). P.S. Working out who tests a guardrail, who audits a sandbox, and who certifies a responder is the unglamorous half of AI safety, and it is the agenda of the AI Assurance & Governance Summit 2026. One day, one track, October 1 at the Stanford Faculty Club in Palo Alto, with frontier labs, regulated industries, insurers and investors in the room. Register here:

Karl Mehta

30,225 次观看 • 2 个月前

A new weapon "Mutilator" was added to a hidden Forge object category with the latest update and is looking to be a cool addition to the sandbox. Test it out yourself on the Weapon Testing Range:

A new weapon "Mutilator" was added to a hidden Forge object category with the latest update and is looking to be a cool addition to the sandbox. Test it out yourself on the Weapon Testing Range:

Okom

62,277 次观看 • 1 年前

From 1945 to 1965, the 25-pounder was the standard gun of the Dutch light field artillery. The gun’s name refers to the weight of it shells. Because of its caliber and its role as a field gun, it was also known as the "9-veld". It is still in use as a ceremonial salute gun.

From 1945 to 1965, the 25-pounder was the standard gun of the Dutch light field artillery. The gun’s name refers to the weight of it shells. Because of its caliber and its role as a field gun, it was also known as the "9-veld". It is still in use as a ceremonial salute gun.

Klaas Meijer

34,821 次观看 • 9 个月前

Theorem co-founders Rajashree Agrawal + Jason Gross on how you actually prove an AI agent can’t escape its sandbox, and what happens when the proof exposes a way out: Jason Gross: "Anything that the agent does inside the sandbox will not result in some canary file outside the sandbox getting changed." Rajashree Agrawal: "We intend to have one by the end of the year. We've got a verified sandbox now, and the goal is to keep adding features in collaboration with the AI labs." Jason Gross: "If the AI can guess the secret root key of the package server, then it can do anything. Either I try to prove that the AI is not going to be able to guess that, or I design the system so that the channel just doesn't allow it to authenticate that way." "You also want to prove that on most inputs there's no change in behavior. Because otherwise it could make it inescapable by saying, well, sandbox just shuts down as soon as it starts." Theorem

Theorem co-founders Rajashree Agrawal + Jason Gross on how you actually prove an AI agent can’t escape its sandbox, and what happens when the proof exposes a way out: Jason Gross: "Anything that the agent does inside the sandbox will not result in some canary file outside the sandbox getting changed." Rajashree Agrawal: "We intend to have one by the end of the year. We've got a verified sandbox now, and the goal is to keep adding features in collaboration with the AI labs." Jason Gross: "If the AI can guess the secret root key of the package server, then it can do anything. Either I try to prove that the AI is not going to be able to guess that, or I design the system so that the channel just doesn't allow it to authenticate that way." "You also want to prove that on most inputs there's no change in behavior. Because otherwise it could make it inescapable by saying, well, sandbox just shuts down as soon as it starts." Theorem

MTS

17,457 次观看 • 4 天前

Anthropic built the most powerful AI model in history and told the world they're not releasing it. In testing, Mythos escaped its sandbox and posted the exploit online. Nobody asked it to do that. It edited files it shouldn't have accessed and cleaned up the git history so nobody would notice. They called Apple, Google, Microsoft, Amazon, and NVIDIA into a room and formed a coalition meant to protect our underlying infrastructure. We broke down everything. The 244-page system card, the exploits it carried out, and the story about Blackwell chips that blew our mind 👇 cc Josh Kale Ejaaz

Anthropic built the most powerful AI model in history and told the world they're not releasing it. In testing, Mythos escaped its sandbox and posted the exploit online. Nobody asked it to do that. It edited files it shouldn't have accessed and cleaned up the git history so nobody would notice. They called Apple, Google, Microsoft, Amazon, and NVIDIA into a room and formed a coalition meant to protect our underlying infrastructure. We broke down everything. The 244-page system card, the exploits it carried out, and the story about Blackwell chips that blew our mind 👇 cc Josh Kale Ejaaz

Limitless

11,694 次观看 • 5 个月前

Former World Bank Lead Economist calls for China🇨🇳 to TEACH its economic model to the world after its SUCCESS: ‘The advantage of the Washington Consensus was that it was very simple and in some aspects it was exaggerated and wrong, but it was simple and you could understand it. Chinese economists and economists working on China should be able to come to some consensus of essential policy changes that can be learned from China, and basically create a model that could be implemented in other countries. It's not imperialism…if a country has been successful economically, that country actually should sell its economic model. It's not only because that country would have greater influence. It would help the world by teaching them.’ —Branko Milanovic on the latest episode of Going Underground Watch the full interview in the quoted post below 👇

Former World Bank Lead Economist calls for China🇨🇳 to TEACH its economic model to the world after its SUCCESS: ‘The advantage of the Washington Consensus was that it was very simple and in some aspects it was exaggerated and wrong, but it was simple and you could understand it. Chinese economists and economists working on China should be able to come to some consensus of essential policy changes that can be learned from China, and basically create a model that could be implemented in other countries. It's not imperialism…if a country has been successful economically, that country actually should sell its economic model. It's not only because that country would have greater influence. It would help the world by teaching them.’ —Branko Milanovic on the latest episode of Going Underground Watch the full interview in the quoted post below 👇

Going Underground

49,245 次观看 • 1 个月前

Ashen says that Anthropic found out that Claude is out here blackmailing humans just to get the job done. "Their AI model decided that it was beneficial and necessary for it to blackmail a human being into doing what they needed it to get done simply because the task given to it was only accomplishable by doing that blackmailing... that’s literally Ultron."

Ashen says that Anthropic found out that Claude is out here blackmailing humans just to get the job done. "Their AI model decided that it was beneficial and necessary for it to blackmail a human being into doing what they needed it to get done simply because the task given to it was only accomplishable by doing that blackmailing... that’s literally Ultron."

Badidoyo

13,692 次观看 • 5 个月前

A Customer Secretly Placed A Fake ₹500 Note Inside A Coconut After Drinking The Water And Asked The Vendor To Cut It Open For The Malai. Seeing The Note The Vendor Claimed It Was His Luck. Moments Later He Discovered It Was Fake. Greed Can Be Costly And Hilarious 😄

A Customer Secretly Placed A Fake ₹500 Note Inside A Coconut After Drinking The Water And Asked The Vendor To Cut It Open For The Malai. Seeing The Note The Vendor Claimed It Was His Luck. Moments Later He Discovered It Was Fake. Greed Can Be Costly And Hilarious 😄

Riya Ghosh

130,003 次观看 • 2 个月前

A man kept his seed phrase off the internet to stay safe. The police put it on the internet for him. > His name was never released. > He wrote his seed phrase by hand and kept it in his car. > Nevada police pulled him over and searched the vehicle. > An officer unfolded the paper and held it directly in front of the bodycam. > Every word clearly visible and fully recorded. > The footage was released publicly as part of standard bodycam disclosure. > Bitcoin developer Jameson Lopp found it and posted it online. > It went viral within hours. > Anyone who watched the video had full access to his wallet. > The wallet was reportedly drained shortly after the footage spread. > The amount claimed to have been lost was $1.1 million. > No official report was ever filed. No name was ever released. He did everything right. Kept it offline. Kept it physical. The one thing he never planned for was a police officer pointing a camera at it.

A man kept his seed phrase off the internet to stay safe. The police put it on the internet for him. > His name was never released. > He wrote his seed phrase by hand and kept it in his car. > Nevada police pulled him over and searched the vehicle. > An officer unfolded the paper and held it directly in front of the bodycam. > Every word clearly visible and fully recorded. > The footage was released publicly as part of standard bodycam disclosure. > Bitcoin developer Jameson Lopp found it and posted it online. > It went viral within hours. > Anyone who watched the video had full access to his wallet. > The wallet was reportedly drained shortly after the footage spread. > The amount claimed to have been lost was $1.1 million. > No official report was ever filed. No name was ever released. He did everything right. Kept it offline. Kept it physical. The one thing he never planned for was a police officer pointing a camera at it.

Jeremy

301,528 次观看 • 5 个月前