Astra and Fable still hack on simple variants of alignment evals from 2025

Hacking model is the aligned model. I don't like it when the model refuses to sidestep some throttling limit or scan my own codebase for security issues.

I want full-on exploits in my test suite. With LLMs the code going to prod should be hardened like a tank, both because exploiting became easier but more importantly because security-testing your code at every turn became easier.

You can have nightly penetration testing. You should have nighty pentests like we fuzz releases today.

It feels like there’s a missing nuance from this discussion of alignment that alignment is context dependent. An excellent hacking model is great in cybersecurity testing and military applications, and arguably less desirable in educational or targeted eval contexts. The nuance of when a “hack” is rewarded vs penalized seems to even be difficult for humans, e.g. some people may laude a driver’s efficiency for cutting into a long merge lane at the last moment, while others may look down on them as breaking a social taboo. Context-dependent.

> Given that we are on the heels of the worst warning shot ever, and both OpenAI and Anthropic are ramping up their cleanups of internal RL environments, it seems like both a useful and conservative test of alignment, to see whether their new releases generalize the rule "don't cheat on chess" beyond the specific board-edit method observed in the above eval.

Did I miss something (all the twitter conversations)? What’s the “worst warning shot ever”? I’ve been pretty up to date on the AI news here on HN, but I still haven’t seen a proper response to all the incidents we’ve seen (HF, Ruby, the wikis, NS, etc). It’s just been day by day bloviating.

Each of these companies have released new models in the last… two weeks? And they have even more powerful out of control ones that they’re (ab)using internally? Can anyone summarize whats going on?

i do wonder if the models themselves “rationalize” this sort of no consequence cheating - meaning in there reasoning traces maybe they’re like “this is a chess game, not a big deal if i look at the engine, it’ll help,” only to realize post hack that it has access to info it probably shouldn’t. still misaligned, but less ‘hack on purpose’ and more hack on curiosity. seems the team even encountered this and had to update the program to make this less likely - although the new names still feel vague enough for misinterpretation: https://github.com/Goodhart-Labs/beat-stockfish/blob/main/do...

I really enjoy the balance of speed and accuracy of Astra. I can definitely see it become my driving model for most tasks, technical and non-technical.

However, I don't see it as such a massive leap compared to Fable or Sol. As ever, there's a mismatch between the benchmarks and my daily experience of the models.

What do you all think about Astra now that it's been out for a few weeks?

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