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Posttraining @OpenAI | PhD @StanfordAILab

1k following11k followers

The Thought Leader

Yann Dubois is a pioneering AI researcher and communicator who bridges cutting-edge technology and practical insights. With a PhD from Stanford and a key role posttraining at OpenAI, Yann simplifies complex AI advancements for the community. Their tweets blend deep technical knowledge with accessibility, making them a go-to voice for understanding AI breakthroughs.

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Top users who interacted with Yann Dubois over the last 14 days

@natolambert

Research @allen_ai, reasoning, open models, RL(VR/HF)... Contact via email. Writes @interconnectsai, Wrote The RLHF Book, 🏔️🏃‍♂️

1 interactions

Yann probably spends so much time debating if a model’s context window is 32k or 196k that they forget their own Twitter bio could use a little more storytelling and a little less tech specs—because who else will geek out about context size at parties?

Yann’s biggest win is successfully clarifying and popularizing the availability of the GPT-5 reasoning model’s massive 196k context window, reshaping developer expectations and sparking new excitement around AI coding capabilities.

Yann’s life purpose is to advance AI understanding and accessibility by translating high-level research into actionable knowledge for developers, researchers, and enthusiasts alike. They aim to push the boundaries of AI capabilities while ensuring the community stays informed about the real impact and possibilities of these models.

Yann strongly believes in transparency, precision, and continuous improvement in AI development. They value sharing knowledge openly to empower others, encouraging collaborative progress and thoughtful discourse about the implications and potentials of AI.

Their greatest strength lies in authoritative communication combined with deep technical expertise, enabling them to lead conversations and set narratives in the AI community. Yann’s ability to demystify complex AI topics while highlighting practical tips creates high engagement and trust.

An overemphasis on technical accuracy occasionally limits the breadth of their audience, possibly alienating less-technical followers who might crave more simplified or relatable content. Also, the frequency of tweets could benefit from more interactive or conversational tone to boost broader engagement.

To grow their audience on X, Yann should mix their authoritative insights with more frequent Q&A or thread-style posts that invite community participation. Leveraging Twitter Spaces or Twitter polls around hot AI topics could increase follower interaction and attract diverse followers who appreciate both depth and accessibility.

Fun fact: Yann clarified a common misconception about context size in ChatGPT, revealing that GPT-5’s thinking model supports an impressive 196k context size — much higher than initially publicized, which is a game changer for coding and reasoning tasks!

Top tweets of Yann Dubois

We now evaluated also the @MetaAI's LLaMA 2 70B model! 🔥 Exciting times ahead! We also updated ChatGPT which seems to have improved over the last months Thanks for providing the compute/API end point @a16z @replicatehq @appenz @rajko_rad @Mascobot

141k

You can thank @ericmitchellai for caring so much about that

66k

I played with @AnthropicAI assistant (AA) and compared it to @OpenAI ChatGPT TLDR: both are similar but AA is + Harder to jailbreak + Tries to be more helpful + Follows closer what we ask for + ~Better for writing in English - Worst for code - Worst in French - Longer resp. 🧵

94k

New *introductory* lecture on how to build an LLM 🤖 youtu.be/9vM4p9NN0Ts?si… There are already many great videos on transformers, so this one focuses on the rest: evaluation, cost, compute, data, tokenizer, etc.

45k

First release I've been part of at @OpenAI 🚀 Especially excited about the speed gains of O1 vs O1-preview! We need to make it even faster!! If you have realistic questions where O1 consistently fails, feel free to send them my way.

29k

Most engaged tweets of Yann Dubois

First release I've been part of at @OpenAI 🚀 Especially excited about the speed gains of O1 vs O1-preview! We need to make it even faster!! If you have realistic questions where O1 consistently fails, feel free to send them my way.

29k

You can thank @ericmitchellai for caring so much about that

66k

We now evaluated also the @MetaAI's LLaMA 2 70B model! 🔥 Exciting times ahead! We also updated ChatGPT which seems to have improved over the last months Thanks for providing the compute/API end point @a16z @replicatehq @appenz @rajko_rad @Mascobot

141k

I played with @AnthropicAI assistant (AA) and compared it to @OpenAI ChatGPT TLDR: both are similar but AA is + Harder to jailbreak + Tries to be more helpful + Follows closer what we ask for + ~Better for writing in English - Worst for code - Worst in French - Longer resp. 🧵

94k

New *introductory* lecture on how to build an LLM 🤖 youtu.be/9vM4p9NN0Ts?si… There are already many great videos on transformers, so this one focuses on the rest: evaluation, cost, compute, data, tokenizer, etc.

45k

GPT4-o from @OpenAI tops AlpacaEval Actually, the top 3 models are preferred by GPT-4 Preview than itself. By now I've seen many times models that prefer better models than themselves, and that suggests to me that some form of self-improvement (in the narrow sense) is possible!

8k

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