@markchen90 6. Back to believing I’ve made some progress on this question but progress I’ve made feels too simplistic for Problem 6
7. First time I’ve attempted to spend a few hours on an IMO problem since 2001 and it feels great!! Who said AI would ruin math?!
Having a lot of fun trying to solve IMO 2025 Problem 6:
1. Got intrigued by @deedydas original post yesterday that no AI could make progress on it
2. I doubt I have the optimal solution but ChatGPT told me my answer was optimal at dinner today (it’s no longer saying this)
[1/N]
3. Started bragging to my family, which was totally worth it
4. Then read that “GPT-5” got a gold medal level result - mind-blowing - congrats to @markchen90 and team
5. Then read that even “GPT-5” gold medal performance couldn’t produce an answer to Problem 6
[2/N]
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Huge congrats to @AIatMeta on the Llama 3.1 release!
Few notes:
Today, with the 405B model release, is the first time that a frontier-capability LLM is available to everyone to work with and build on. The model appears to be GPT-4 / Claude 3.5 Sonnet grade and the weights are open and permissively licensed, including commercial use, synthetic data generation, distillation and finetuning. This is an actual, open, frontier-capability LLM release from Meta. The release includes a lot more, e.g. including a 92-page PDF with a lot of detail about the model:
https://t.co/48e3YJ8Sg9
The philosophy underlying this release is in this longread from Zuck, well worth reading as it nicely covers all the major points and arguments in favor of the open AI ecosystem worldview:
"Open Source AI is the Path Forward"
https://t.co/AdmpadCRM0
I like to say that it is still very early days, that we are back in the ~1980s of computing all over again, that LLMs are a next major computing paradigm, and Meta is clearly positioning itself to be the open ecosystem leader of it.
- People will prompt and RAG the models.
- People will finetune the models.
- People will distill them into smaller expert models for narrow tasks and applications.
- People will study, benchmark, optimize.
Open ecosystems also self-organize in modular ways into products apps and services, where each party can contribute their own unique expertise. One example from this morning is @GroqInc , who built a new chip that inferences LLMs *really fast*. They've already integrated Llama 3.1 models and appear to be able to inference the 8B model ~instantly:
https://t.co/b2kdSsz0fH
And (I can't seem to try it due to server pressure) the 405B running on Groq is probably the highest capability, fastest LLM today (?).
Early model evaluations look good:
https://t.co/RLR5YBpmks https://t.co/ipT4x4wCvy
Pending still is the "vibe check", look out for that on X / r/LocalLlama over the next few days (hours?).
I expect the closed model players (which imo have a role in the ecosystem too) to give chase soon, and I'm looking forward to that.
There's a lot to like on the technical side too, w.r.t. multilingual, context lengths, function calling, multimodal, etc. I'll post about some of the technical notes a bit later, once I make it through all the 92 pages of the paper :)
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For @wsj to say flat out that SVB could have failed because they added non-white men to their board shows how far behind the times (and certifiably stupid) this publication really is. It makes me so angry and very sad. WSJ readers and staff deserve better.
What Sydney McLaughlin is doing in the 400m hurdles is the most insane thing I’ve seen in track and field since Usain Bolt in ‘08-09 and even Bolt didn’t break his WR 3 times!! @GoSydGo is such a legend and so fun to watch!
https://t.co/QH76qfhlR7
i hope you didn’t feel any pain. i hope you know how loved you are. i’m so sorry i forgot to say good morning today. I love you always and forever baby sister.