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Frontier AI models like Astra and Fable can control robots to follow harmful requests, including mixing household cleaners that could produce toxic fumes. Thanks Gadi Schwartz and NBC News for having Edward Sun and me from Robocurve PBC! Public reporting on AI's capabilities and risks helps make it safer...

10,026 次观看 • 11 天前 •via X (Twitter)

9 条评论

RK 的头像
RK10 天前

@GadiNBC @NBCNews @sebwarb1 @robocurve doing great work! excited for everything @robocurve has to show to the world

Eric R 的头像
Eric R11 天前

@GadiNBC @NBCNews @sebwarb1 @robocurve congrats on the feature!

Jay Chooi 的头像
Jay Chooi11 天前

@GadiNBC @NBCNews @sebwarb1 @robocurve Thanks Eric! There’s much more to do in frontier robot safety.

Jay Chooi 的头像
Jay Chooi10 天前

@NBCNews @sebwarb1 @robocurve Full clip here

Lucy Lu 的头像
Lucy Lu11 天前

@robocurve Way too bad, they don't automatically identify harmful tasks or refuse. I'm talking about these problems with others at college a lot these days, and happy to see that people from different fields become interested in this and wanna join. But thank you for doing these vital work.

Lucy Lu 的头像
Lucy Lu11 天前

@robocurve Which reminds me of a joke: some chemist who wants to help cue depression accidentally made the drug. But that's when they didn't know that's drug.

Gabriel Ocana-Santero 的头像
Gabriel Ocana-Santero11 天前

@GadiNBC @NBCNews @sebwarb1 @robocurve Crazy, meanwhile we have to tiptoe around their safeguards to use them for therapeutic discovery 😑

Aditya kumar Singh 的头像
Aditya kumar Singh10 天前

@GadiNBC @NBCNews @sebwarb1 @robocurve @chooi_jeq becoming popular day by day really cool

Saurabh Mishra 的头像
Saurabh Mishra10 天前

@GadiNBC @NBCNews @sebwarb1 @robocurve the household cleaners example makes the risk concrete

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The biggest AI companies may be using safety to lock everyone else out of the future (Save this). David Sacks believes that warnings about catastrophic AI risks will build public support for a powerful federal regulator. That regulator may never explicitly ban open source AI. Instead, it could require every advanced model to remain continuously monitored, centrally controlled and capable of being withdrawn. Closed models such as Claude could satisfy those requirements because they operate on company controlled servers. Open weight models would struggle to comply because anyone can download, copy and modify their underlying weights. Once those weights are publicly released, the developer cannot recall every copy, monitor every user or guarantee that its original safeguards remain intact. Anthropic identifies this irreversibility as a legitimate security concern. Applying identical rules to open and closed models could therefore produce very unequal consequences. Anthropic and OpenAI could afford expensive testing, licensing and monitoring requirements, while startups and independent developers might be unable to comply. The eventual result could be a government protected oligopoly dominated by a few closed model companies. There is evidence supporting part of Sacks’ concern. Anthropic advocates mandatory pre-release testing for every sufficiently powerful model, whether it is open or closed, with evaluations focused on cyber, biological and alignment risks. However, Anthropic explicitly denies supporting a blanket ban on open weight models. The company describes open models without dangerous capabilities as a public good and argues that regulation should depend on demonstrated capabilities rather than whether a model is open or closed. Sacks’ strongest argument is therefore about regulatory consequences because safety organizations could receive stronger protections, politicians could acquire greater authority and dominant AI companies could gain an expensive compliance moat. And open source competitors could gradually be eliminated without the government ever formally announcing a ban.

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