Charles Qi ✓

@charles_rqi · San Francisco, CA · joined 17 May 2020

Research @OpenAI. Prev: Tesla | Waymo | FAIR | Stanford

11 278Followers

345Following

211Posts total

1.4MViews on collected posts

Последние посты

Charles Qi ✓@charles_rqi10 Sep

Great to see a principled study of video model pretraining for robot manipulation. I especially like the evaluation setup: a real-world industrial task and a strong, consistent post-training pipeline to compare pretrained checkpoints. 4K views · 39 likes · 0 reposts · 3 replies Open on X →

Charles Qi ✓@charles_rqi10 Sep

Does scaling pre-training on general web video improve a complex manipulation task in real deployment? We scale model size and pre-training compute, and test on one industrial task. Yes. The better a pre-trained model predicts web video, the better its post-trained policy. 🧵 ht

88.7K views · 290 likes · 38 reposts · 33 replies Open on X →

Charles Qi ✓@charles_rqi8 Sep

Using LLMs to control robots is not a new idea, but it has drawn more attention recently with Fable and Astra. Computer-use agents can already accomplish many tasks through code rather than mouse and keyboard actions. For robots, the question is how far coding alone can go. My 11.4K views · 96 likes · 4 reposts · 7 replies Open on X →

Charles Qi ✓@charles_rqi7 Sep

Recently, there have been a lot of impressive demos of AI agents, like Claude, controlling robots. I wrote a short blog post with my thoughts on the advent of these "robot-use agents." https://t.co/5bUjZlZxCi I think it's an important change in the trajectory of robotics! 196.6K views · 743 likes · 111 reposts · 44 replies Open on X →

Charles Qi ✓@charles_rqi19 Aug

Few-shot, in-context learning for robotics is here. Super exciting! Unlike GPT-3, whose pretraining data largely came from the Internet, GEN-1.5 was trained on large-scale, deliberately collected physical interaction data. A strong signal that scaling real-world interaction 12.5K views · 118 likes · 7 reposts · 3 replies Open on X →

Charles Qi ✓@charles_rqi17 Jul

The four essentials of daily life are clothing, food, housing, and transportation. Clothing may be the first category that home robots truly crack. Congrats to Sunday Robotics for the ACT-2 launch that got 99% accuracy in the laundry folding task! 5.4K views · 34 likes · 4 reposts · 2 replies Open on X →

Charles Qi ✓@charles_rqi16 Jul

Introducing ACT-2 Preview The first robotics model to unify broad generalization with high reliability. A single fine-tuning example can teach Memo a new behavior that generalizes. Zero shot, real unseen homes, 99% success rate. https://t.co/Dzj56baDtp

2:25

1M views · 4.1K likes · 482 reposts · 212 replies Open on X →

Charles Qi ✓@charles_rqi19 Jun

The (online) imitation learning / behavior cloning for Codex is here. 3.9K views · 20 likes · 1 reposts · 2 replies Open on X →

На фоне аккаунтов своего размера

5 постов за последние 90 дней рядом с диапазоном 10K–100K подписчиков. показывается широко, но откликается мало кто.

Медианные просмотры12 515этот аккаунт924медиана для 10K–100K

Охват, %110.97%этот аккаунт3.62%медиана для 10K–100K

Вовлечённость, %0.96%этот аккаунт1.52%медиана для 10K–100K

Показатель	Этот аккаунт	Медиана для 10K–100K	Отношение
Медианные просмотры на пост	12 515	924	13.5×
Охват (просмотры ÷ подписчики)	110.97%	3.62%	30.6×
Вовлечённость	0.96%	1.52%	0.63×

Другие в этом диапазоне → Сравнить с другим аккаунтом → Как считаются эти ориентиры →

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

3.9K19 Jun

1M16 Jul

5.4K17 Jul

12.5K19 Aug

196.6K7 Sep

11.4K8 Sep

88.7K10 Sep

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.59%19 Jun

0.48%16 Jul

0.74%17 Jul

1.02%19 Aug

0.48%7 Sep

0.96%8 Sep

0.44%10 Sep

1.05%

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

What the audience does

Likes60.4%5 410 in total

Reposts7.2%647 in total

Replies3.4%306 in total

Quotes3.7%331 in total

Bookmarks25.2%2 256 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.