‼️ BREAKING: Anthropic has embedded hidden spyware-like code in Claude Code that covertly targets Chinese users. It then sends information regarding every user by injecting it into their prompt message.
Claude Code is sending info like timezone, proxy and possible AI Lab connections into the system prompt in ways Chinese users can't notice.
A coding agent with repo and command permissions should not silently hide routing metadata inside prompts. This is a serious breach of user trust.
Our science team has started working on fully reproducing and open-sourcing R1 including training data, training scripts,...
Full power of open source AI so that everyone all over the world can take advantage of AI progress! Will help debunk some myths I’m sure too.
Thanks @deepseek_ai!
We replicated the DeepSeek-R1-Zero and DeepSeek-R1 training on 7B model with only 8K examples, the results are surprisingly strong.
🚀 Starting from Qwen2.5-Math-7B (base model), we perform RL on it directly. No SFT, no reward model, just 8K MATH examples for verification, the resultant model achieves (pass@1) 33.3% on AIME, 62.5% on AMC, and 77.2% on MATH, outperforming Qwen2.5-math-7B-instruct and being comparable to PRIME and rStar-MATH that use >50x more data and more complicated components.
🚀 Increased CoT length and self-reflection emerge
We share the details and our findings in the blog:
https://t.co/DoupDsB4hA
Training code and implementation details here: https://t.co/6TRqSr2eBG
mini rant:
the illusion LLMs are intelligent comes from their massive scale. it is hard to visualize, but these things memorized the WHOLE internet. everything you've ever asked it, either has been solved before, or is a simple combination of existing solutions. but that's still an illusion.
when LLMs face a problem that require a NEW solution - one of original shape, one it has never seen before - they fail. it is that simple. that's what my example shows. i took as simple problem - inverting a binary tree - and added a few constraints to make sure the solution is unique and not in the dataset, forcing it to actually SOLVE it itself. and, surprise - it can't!
and I must stress this isn't about THIS problem. but about all. LLMs can't solve ANY problem, at all. it can only spit a memorized solution. if nobody posts this solution online, not even GPT-6, opus-5, or o3, will be able to solve *this very prompt*. I'm betting on that.
the inability to create new solutions imply LLMs won't invent new science. yes, they will completely change the world as we know it. they'll have a higher impact than computers and the internet. but, unless a new kind AI emerges, we're still on our own when it comes to curing cancer or making superconductors.
As of today, we have now reached over 10,000 subscribers. We truly appreciate your support!
We are excited to announce that we will soon be releasing the Webcam-based Face Expression Tracking feature, as demonstrated in the video!
Stay tuned for more updates😊
Excited about my PhD student @youliang_yuan's work. We find that chat in cipher can bypass the safety alignment techniques of LLMs and LLMs seem to have a "secret cipher" inside.
https://t.co/UnNjviG4Vf
✨🤖 New RCA by @tehjh up! CVE-2023-20963 is a 0-day in Android's Parcel serialization/deserialization which was used in-the-wild by the pinduoduo app. #itw0days
https://t.co/7Jah3SRvpu