Astra 与 Fable 在 2025 年对齐评测的简单变体上仍存在作弊行为

Domain: lesswrong.com Points: 49 | Comments: 7 [Top Comments] - 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. - Run a local model that is uncensored and it won't say no to pretty much anything - Yes, but is this also aligned with the people who regulate AI? Intelligence agencies and governments want access to data and right now use secret exploits to get this access. There are few civilian domestic companies who don't export their products, so generally there shouldn't be a strong incentive to allow hardening products very much, at least not in a way that would make them more secure than what advanced AI can break. It's not even far-fetched to suspect in that US and Chinese AIs could deliberate introduce sneaky bugs when foreigners use them in the future. - *> 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? - Lesswrong is talking about the HF incident as the "worst warning shot ever". - 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.