Trapit Bansal ✓

@TrapitBansal · San Francisco, CA · joined 26 Jan 2010

AI Research @Meta, Founding Member TBD Lab | Previously @OpenAI, co-creator of OpenAI o-series models (thinking in LLMs)

32 073Followers

287Following

123Posts total

596.6KViews on collected posts

Posts recentes

Trapit Bansal ✓@TrapitBansal8 Sep

Congratulations Levent, Tristan, and OpenAI! What a miraculous time to be alive! I view this as the first successful achievement of Recursive Self Improvement or RSI. Models get increasingly better at Math and get increasingly used by mathematicians to solve all kinds of 161.5K views · 798 likes · 54 reposts · 38 replies Open on X →

Trapit Bansal ✓@TrapitBansal8 Sep

Surprised to learn today how many people did not know that if you don't turn off "Improve the model for everyone" in chat then your data will very likely be trained on. Also, its on by default. Same applies to codex. https://t.co/a29YQku8kb

4.8K views · 55 likes · 8 reposts · 10 replies Open on X →

Trapit Bansal ✓@TrapitBansal7 Sep

Fun fact: RLSlow was named after Thinking, Fast and Slow. The idea was that language models already had a kind of "fast" thinking, producing an answer immediately, and that we could use RL to teach them "slow" thinking: deliberate, multi-token reasoning that spends more compute 38.4K views · 420 likes · 27 reposts · 7 replies Open on X →

Trapit Bansal ✓@TrapitBansal7 Sep

Let me take this opportunity to pay tribute to the RLSlow team :) It was a priviledge to lead it through the years, first with @ilyasut then with @merettm and finally on my own - the best team you can ever wish for. It feels like ages ago when we started working on the 338.4K views · 467 likes · 26 reposts · 9 replies Open on X →

Trapit Bansal ✓@TrapitBansal2 Sep

Excited to see Muse Spark 1.3 out in the world. There’s a lot of progress in this release, and with 1.3 Max specifically, the intelligence you get per dollar is kind of ridiculous! If you’re a developer and haven’t tried Muse Spark yet, you’re running out of reasons not to. 8.7K views · 118 likes · 1 reposts · 9 replies Open on X →

Trapit Bansal ✓@TrapitBansal6 Aug

We entered Meta models in five international STEM Olympiads, as an uncontaminated eval of their reasoning capabilities. Three of these were live participations and graded officially. The models achieved gold-medal results in all five! 1/5 https://t.co/JSXrQpNMJE

44.8K views · 219 likes · 19 reposts · 11 replies Open on X →

Em comparação com contas do mesmo porte

6 posts dos últimos 90 dias, ao lado da faixa de 10K–100K seguidores. aparece para muita gente, mas poucos desses espectadores reagem.

Mediana de visualizações41 596esta conta924mediana para 10K–100K

Alcance, %129.69%esta conta3.62%mediana para 10K–100K

Engajamento, %0.87%esta conta1.52%mediana para 10K–100K

Métrica	Esta conta	Mediana para 10K–100K	Proporção
Mediana de visualizações por post	41 596	924	45.0×
Alcance (visualizações ÷ seguidores)	129.69%	3.62%	35.8×
Taxa de engajamento	0.87%	1.52%	0.57×

Outras contas desta faixa → Comparar com outra conta → Como estas referências são construídas →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

44.8K6 Aug

8.7K2 Sep

338.4K7 Sep

38.4K

4.8K8 Sep

161.5K

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.56%6 Aug

1.48%2 Sep

0.15%7 Sep

1.18%

1.52%8 Sep

0.55%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes79.5%2 077 in total

Reposts5.2%135 in total

Replies3.2%84 in total

Bookmarks12.1%317 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.