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Liam Fedus
Periodic Labs
@LiamFedus
Building industrial-scale science at @periodiclabs Past: VP of Post-Training @OpenAI; Google Brain
San Francisco, CA
Joined October 2012
Posts
  • Pinned
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    Today, @ekindogus and I are excited to introduce @periodiclabs. Our goal is to create an AI scientist. Science works by conjecturing how the world might be, running experiments, and learning from the results. Intelligence is necessary, but not sufficient. New knowledge is
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    GPT-4o is our new state-of-the-art frontier model. We’ve been testing a version on the LMSys arena as im-also-a-good-gpt2-chatbot 🙂. Here’s how it’s been doing.
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    This is what I sent to my colleagues at OpenAI: Hi all, I made the difficult decision to leave OpenAI as an employee, but I’m looking to work closely together as a partner going forward. Contributing to the mission of OpenAI and working with world-class teams to create and
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    Happy to release a couple of our reasoning models today (🍓)! At @OpenAI , these new models are becoming a larger contributor to the development of future models. For many of our researchers and engineers, these have replaced a large part of their ChatGPT usage.
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    Was having so much fun, I forgot to Tweet about it: I joined OpenAI! I’m continuously awed by the people, the technology, and the ambition. We’re just scratching the surface with ChatGPT. If you’re interested, get in touch!
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    Today we're releasing all Switch Transformer models in T5X/JAX, including the 1.6T param Switch-C and the 395B param Switch-XXL models. Pleased to have these open-sourced! github.com/google-researc… All thanks to the efforts of James Lee-Thorp, @ada_rob, and @hwchung27
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    Replying to @LiamFedus
    Not only is this the best model in the world, but it's available for free in ChatGPT, which has never before been the case for a frontier model.
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    Replying to @LiamFedus
    But the ELO can ultimately become bounded by the difficulty of the prompts (i.e. can’t achieve arbitrarily high win rates on the prompt: “what’s up”). We find on harder prompt sets — and in particular coding — there is an even larger gap: GPT-4o achieves a +100 ELO over our prior
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    OpenAI is nothing without its people
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    Presenting our survey on emergent abilities in LLMs! arxiv.org/abs/2206.07682 What's it about? Certain downstream language tasks exhibit an interesting behavior: eval curves are flat/random up to a certain model scale, until -- poof -- things start to work. 1/7
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    As part of today, we’re also releasing o1-mini. This is an incredibly smart, small model that can also reason before it’s answer. o1-mini allows us at @OpenAI to make high-intelligence widely accessible. openai.com/index/openai-o… On the AIME benchmark, o1-mini re-defines the
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    GPT-4o is the first model to exceed human performance on MathVista
    🚨 BREAKING: @OpenAI's new GPT-4o model outperforms humans on MathVista for the first time! 📊 Scores: Human avg: 60.3 GPT-4o: 63.8 📖 Learn more: OpenAI : openai.com/blog/gpt-4o/ MathVista: mathvista.github.io
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    Pleased to share new work! We design a sparse language model that scales beyond a trillion parameters. These versions are significantly more sample efficient and obtain up to 4-7x speed-ups over popular models like T5-Base, T5-Large, T5-XXL. Preprint: arxiv.org/abs/2101.03961
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    Fun following LLM retrieval progress. One recent work is Memorizing Transformers which increases context length up to 262k by an external memory of (keys, values) for that document. - Matches quality of Transformers 5x larger - Can fine-tune a prior pre-trained models to use it