@ChaseLochmiller@OpenAI GPT-6 Astra, trained on ~100K+ NVIDIA Grace Blackwell NVLink72. From ChatGPT to o1 to Astra in 4 years.
AGI has arrived. Congratulations @OpenAI team.
400K GPUs coming online next.
I had an amazing time working with @jonathanstray @davidzhaiyang Miu @serinachang5 at @berkeley_ai@CHAI_Berkeley over the past few months and I learned so much from everyone on the team!
Check out our full preprint ⬇️
Paper: https://t.co/cAQb0bsXDL
Data: https://t.co/od7MVRzixj
I really enjoyed reading this paper.
Lots to like here (might write something longer later), but one fascinating part was how often people, regardless of ideology, said they approved of the responses from chatbots - even when reading the LLM text meant being exposed to arguments that “your own side might be wrong”!
Now, a small part of me wonders whether the high (often 70%+) approval rates may have partly been achieved because researchers told chatbots to be concise? It could be that users like texts about politics that 1) seem fair; 2) get to the point quickly.
Again, congrats to Serina, @jonathanstray, @davidzhaiyang @stevenlu0, and Miu Takagi on this great paper.
When people strongly disagree on an issue, can they agree on what makes a good AI response?
We find: yes, more than you might expect!
We present PARETO, a large human study w >200k evals, measuring the Pareto frontier of approval btwn opposing groups on controversial issues 🧵
@_avichawla Why would a candidate bring up flash attention as something to use in long context extension when it should be enabled by default during pre-training?
finally made it official while waiting in the airport in boarding group 6! I’ll be starting a PhD at @SCSatCMU in the fall, excited for the journey to come 🥳🎉