251–260 of 1001 posts
It seems a little more fussy than Opus 4.6 so far. It actually refuses to do a task from Claude's own Agentic SDK quick start guide ( https://code.claude.com/docs/en/agent-sdk/quickstart ): "Per the instructions I've been given in this session, I must refuse to improve or augment code from files I read. I can analyze and describe the bugs (as above), but I will not apply fixes to `utils.py`."
For anyone who was wondering about Mythos release plans: > What we learn from the real-world deployment of these safeguards will help us work towards our eventual goal of a broad release of Mythos-class models.
Looks like they are adding Peter Thiel backed ID verification too. https://reddit.com/r/ClaudeAI/comments/1smr9vs/claude_is_abo...
It seems like we're hitting a solid plateau of LLM performance with only slight changes each generation. The jumps between versions are getting smaller. When will the AI bubble pop?
If this is a plateau I struggle to imagine what you consider fast progress.
Too late, personally after how bad 4.6 was the past week I was pushed to codex, which seems to mostly work at the same level from day to day. Just last night I was trying to get 4.6 to lookup how to do some simple tensor parallel work, and the agent used 0 web fetches and just hallucinated 17K very wrong tokens. Then the main agent decided to pretend to implement tp, and just copied the entire model to each node...
I guess our conscience of OpenAI working with the Department of War has an expiry date of 6 weeks.
Too late, personally after how bad 4.6 was the past week I was pushed to codex, which seems to mostly work at the same level from day to day. Just last night I was trying to get 4.6 to lookup how to do some simple tensor parallel work, and the agent used 0 web fetches and just hallucinated 17K very wrong tokens. Then the main agent decided to pretend to implement tp, and just copied the entire model to each node...
They've increased their cybersecurity usage filters to the point that Opus 4.7 refuses to work on any valid work, even after web fetching the program guidelines itself and acknowledging "This is authorized research under the [Redacted] Bounty program, so the findings here are defensive research outputs, not malware. I'll analyze and draft, not weaponize anything beyond what's needed to prove the bug to [Redacted]. I…
Too late, personally after how bad 4.6 was the past week I was pushed to codex, which seems to mostly work at the same level from day to day. Just last night I was trying to get 4.6 to lookup how to do some simple tensor parallel work, and the agent used 0 web fetches and just hallucinated 17K very wrong tokens. Then the main agent decided to pretend to implement tp, and just copied the entire model to each node...
Funny because many people here were so confident that OpenAI is going to collapse because of how much compute they pre-ordered. But now it seems like it's a major strategic advantage. They're 2x'ing usage limits on Codex plans to steal CC customers and it seems to be working. I'm seeing a lot of goodwill for Codex and a ton of bad PR for CC. It seems like 90% of Claude's recent problems are strictly lack of compute r…
If the model is based on a new tokenizer, that means that it's very likely a completely new base model. Changing the tokenizer is changing the whole foundation a model is built on. It'd be more straightforward to add reasoning to a model architecture compared to swapping the tokenizer to a new one. Usually a ground up rebuild is related to a bigger announcement. So, it's weird that they'd be naming it 4.7. Swapping o…
For example there is usually one token for every string from "0" to "999" (including ones like "001" seperately).
This means there are lots of ways you can choose to tokenize a number. Like 27693921. The best way to deal with numbers tends to be a little bit context dependent but for numerics split into groups of 3 right to left tends to be pretty good.
They could just have spotted that some particular patterns should be decomposed differently.