rasdani @rasdani_
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Unitree G1 has mastered more quirky skills 🤩 Unitree G1 has learned the "Anti-Gravity" mode: stability is greatly improved under any action sequence, and even if it falls, it can quickly get back up.
Impressive, highly agile and robust. 20 kg payload per hand.
one of the things that have held true for my entire life is any technical problem is just a matter of time and effort. if you just don't stop, you eventually crack it
Dynamic control trained at SUSTech’s ACT Lab in Shenzhen.
This is incredible
Holy shit they’re doing on-policy RL by just deploying the model to prod lmao that’s so baller. also 2 hrs for a training step makes our 10 minute steps feel lightning fast @hamishivi … they probably have a bigger batch size though 😅
Holy shit they’re doing on-policy RL by just deploying the model to prod lmao that’s so baller. also 2 hrs for a training step makes our 10 minute steps feel lightning fast @hamishivi … they probably have a bigger batch size though 😅 https://t.co/LSAV5OgVXU
All of these behaviors can be explained as subtle artifacts of imperfect rewards during RL training 🔎 Inline imports: likely a scaffold thing (files are read in chunks so edits are done where the model has read the file) but probably also a form of turn-reduction. If you can…
All of these behaviors can be explained as subtle artifacts of imperfect rewards during RL training 🔎 Inline imports: likely a scaffold thing (files are read in chunks so edits are done where the model has read the file) but probably also a form of turn-reduction. If you can…
Have you also come across these? Are there any other recurring failure modes you've seen?
4. Comments on moved/deleted code: when code is removed or moved, you will often see leftover comments. Useless slop that bloats your codebase and can only stand to confuse people. Imagine you move this code a second time, now the pointer is not only useless but also wrong!
3. Backwards compatibility: especially codex tends to want to keep things "backwards compatible" which standalone is a good thing but often leads to leftover/unused code and higher maintenance burden.
2. Unnecessary Fallbacks: likely as an artifact of RL training with tests as rewards, models (esp. gpt-5), tend to go for some safety fallbacks, often not needed and not properly logged. Sometimes these can be helpful but it is prone to introducing unwanted behavior.
1. Inline imports: due to the way that files are read partially instead of as a whole, imports often end up colocated with the place where they are used which is an antipattern and should be used only when absolutely necessary (to avoid circular imports for example)
‼️PSA on common modes of bad code that codex / claude code produce that I've come across. Keep an eye out for these patterns to avoid getting shamed in code review.
If you follow me you know that I love Claude Code and I probably changed my life Been wondering why is leagues ahead of all coding agents before it... so I spent some time digging under the hood. TAKEAWAY: "Simple is better than complex. (my favorite line from the Zen of…
It feels the coding agent frontier is now open-weights: GLM 4.5 costs only $3/month and is on par with Sonnet Kimi K2.1 Turbo is 3x speed, 7x cheaper vs Opus 4.1, but as good Kimi K2.1 feels clean. The best model for me. GPT-5 is only good for complicated specs -- too slow.
finally!
We are releasing 📄 FinePDFs: the largest PDF dataset spanning over half a billion documents! - Long context: Documents are 2x longer than web text - 3T tokens from high-demand domains like legal and science. - Heavily improves over SoTA when mixed with FW-EDU&DCLM web copora.
This is just a small vibecheck (more currently not possible due to rate limits) - but in the German Geo eval I built on stage yesterday evening, @Alibaba_Qwen 3-Max doesn't look competitive with other top models and also falls far behind e.g. R1 or GLM 4.5. 😕 @ellamindAI

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