feel the agi

Joined October 2011
2,611 Photos and videos
Claude needs to release a new Elbaf model
The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Claude models is not affected. We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible. Read our full statement: anthropic.com/news/fable-mytโ€ฆ
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Hassan Hayat ๐Ÿ”ฅ retweeted
The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Claude models is not affected. We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible. Read our full statement: anthropic.com/news/fable-mytโ€ฆ
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Hassan Hayat ๐Ÿ”ฅ retweeted
We've reset 5-hour and weekly rate limits for all users. Enjoy Fable 5!
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Hassan Hayat ๐Ÿ”ฅ retweeted
behold. THE WORLDS FIRST SIX PENDULUM CARTPOLE SOLVE. Including a sponsor! To solve this task, I built an environment to train an AI. This is what mechanize does, but for larger AIs. Apply! Salaries are up on their page Thank you to mechanize for sponsoring!
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Hassan Hayat ๐Ÿ”ฅ retweeted
I admire Fabrice Bellard. He is almost certainly a better overall programmer than I am.
A French engineer who lives quietly in Paris has spent 30 years writing software that the entire internet now runs on without knowing his name. He wrote the code that streams every YouTube video, every Netflix show, every TikTok clip. He wrote the code that runs the virtual servers underneath AWS, Google Cloud, and Microsoft Azure. He calculated more digits of pi than anyone in history. He has no Twitter. He has no marketing. He just keeps shipping. His name is Fabrice Bellard. Here is the story, because almost nobody outside the systems programming world knows what one man has built. Fabrice was born in 1972 in Grenoble, France. He studied at ร‰cole Polytechnique, the top French engineering school. He never went to Silicon Valley. He never built a startup empire. He just wrote code. In 2000 he started a project called FFmpeg, an open-source multimedia framework for encoding, decoding, and streaming video. He was 28. The project did one thing nobody else had done well. It handled every video and audio format that existed, in one library, on every operating system. He led it himself for years. Today FFmpeg is the invisible engine of the internet. YouTube uses it. Netflix uses it. VLC uses it. Chrome and Firefox use parts of it. Every Android phone, every iPhone, every smart TV, every video editing tool you have ever touched runs FFmpeg somewhere underneath. If you have watched a video on a screen in the last 20 years, Fabrice's code processed it. He was not done. In 2003 he started QEMU, a machine emulator and virtualizer. He wrote it solo until version 0.7.1 in 2005. QEMU lets you run any operating system on any other operating system. It became the foundation of modern virtualization. KVM, the Linux kernel hypervisor, runs on top of QEMU. Every major cloud provider, AWS, Google Cloud, Microsoft Azure, IBM Cloud, runs virtual machines on infrastructure built around it. The Quick Emulator is the most cited piece of cloud infrastructure code on Earth. He kept going. In 2001 he won the International Obfuscated C Code Contest with a small C compiler that grew into TCC, the Tiny C Compiler. TCC can compile and boot a Linux kernel from source in under 15 seconds. In 2004 he calculated the most digits of pi ever computed at the time, using a personal desktop computer and an algorithm he derived himself called Bellard's formula. In 2011 he wrote a complete PC emulator in pure JavaScript that runs Linux in your browser, a project called JSLinux that engineers still cannot believe is real. In 2019 he released QuickJS, a small but complete JavaScript engine that fits where V8 cannot. In 2021 he released NNCP, a neural network based lossless data compressor that immediately took the lead on the Large Text Compression Benchmark. Then he turned his attention to large language models. He built TextSynth Server, a web server with a REST API for running LLMs locally. He released ts_zip and ts_sms, compression utilities that use language models to compress text and short messages at ratios traditional algorithms cannot reach. He released TSAC, a very low bitrate audio compression system. In December 2025 he released Micro QuickJS, a new JavaScript engine for microcontrollers, separate from QuickJS, designed for environments with almost no memory. Fabrice co-founded a telecom company called Amarisoft in 2012, where he serves as CTO. Amarisoft builds 4G and 5G base station software used by carriers and labs around the world. He has been running it for over a decade while continuing to ship personal projects from his own home page at bellard dot org He has no Twitter. He has no Instagram. He gives almost no interviews. His personal website is a flat list of projects with no styling, no fonts, no marketing copy. Just titles and links. A quiet French engineer who never moved to Silicon Valley wrote the code that quietly runs the internet. He is still shipping.
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Clean Done Load bearing You're right Clean Done Load bearing You're right
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Jensen, plz fix
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I've unlocked a new ui element in claude
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i wonder how it knows that it is "almost" done thinking
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Hassan Hayat ๐Ÿ”ฅ retweeted
Alright, it's time for a paper thread about my own first ever vision paper, which is having a bit of a moment on twitter rn thanks to @PINTO03091 and @yacineMTB. BiternionNets: continuous head orientation from discrete labels. Demo video from ~11y ago:
ใชใ‚“ใฆใ‚ทใƒณใƒ—ใƒซใชๅฎŸ่ฃ…ใชใ‚“ใ ใ€‚ใ‚ใกใ‚ƒใใกใ‚ƒ่‰ฏใ„ใžใ€‚
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Hassan Hayat ๐Ÿ”ฅ retweeted
Excited to release ๐ŸŒŸPolar๐ŸŒŸ, our Agent RL rollout infra for real-world harnesses. Be it Codex, Claude Code, OpenClaw, Hermes, or your self-made ones ๐Ÿ”ฅ -- Polar takes your harnesses directly as training environments without code change. Find a problem, design the harness, and train your own agents! ๐Ÿงต
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Hassan Hayat ๐Ÿ”ฅ retweeted
May 26
A little over 2 years ago, I solved the SolidGoldMagikarp stability problem. Today, I am releasing the results of that work as a new technique to regularize training. More details below.
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Hassan Hayat ๐Ÿ”ฅ retweeted
The questions posed by AI are bigger than the AI community. We urgently need the world โ€“ religions, civil society, academics, governments โ€“ to participate in creating a positive outcome. I'm glad the Catholic Church is engaging, and honored to speak at the presentation.
Pope Leo XIVโ€™s first encyclical, Magnifica humanitas, on preserving the human person in the age of artificial intelligence, will be released on May 25. A presentation event with the Pope and various speakers is scheduled for the same day at the Vatican. vaticannews.va/en/pope/news/โ€ฆ
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new arxiv drop
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Hassan Hayat ๐Ÿ”ฅ retweeted

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Train on test is everywhere if you look closely enough
Mo Salah scored 191 goals from 191.44(xG) in the Premier League for Liverpool.
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Hassan Hayat ๐Ÿ”ฅ retweeted
May 23
Some of you noticed limits drained faster in Codex, we root caused it to an optimization that we rolled back that had an impact on cache hit rates when compacting across long running sessions. We fixed this and have now reset usage limits for all accounts. Enjoy the weekend.
CODEX LIMITS ARE FIXED!
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Hassan Hayat ๐Ÿ”ฅ retweeted
Your RL post-training may be sabotaging your LLMโ€™s test-time scaling! Conventional RL pretends that you can collapse all reward signals *upfront* into a single *scalar reward*. We introduce Vector Policy Optimization (VPO), which natively maximizes *vector-valued* rewards, boosting test time search performance, even on the original scalar.
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Push it to the limits
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Building a gameboy emulator is tough
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