20 karma · joined September 21, 2025
You don't create a security measure then tell everyone how to bypass it.
I think OP is pointing something interesting out but the undertones of caution and "what else are they hiding" seem melodramatic and I find that hard to take serious.
The internet gives people a platform and, in a lot of ways, this supplants the typical role of journalism. The issue with this is no one wants to act like a journalist and actually explain the truth around a set of facts. Instead, they'll portray their opinions as a narrative and every time that resonates with someone or gets signal boosted, that narrative grows more assertive in the typical discourse I see nowadays. I would find it far more interesting to see what explanation Anthropic gives for these features than to immediately cry foul.
to give you an idea of what I mean, I'm checking bluesky, reddot, HN, youtube, instagram, tiktok, discord basically every hour. every morning, lunch, and evening I'm checking my email where I receive about a dozen or so newsletters either weekly or daily. a few times a week (usually weekends) I'm browsing github and arxiv for the whatever random thought or interest is the flavor of the week (lately its been on EOE techniques and classifiers). This has lead me to collect the names of a good number of authors I trust and that appear to be thought leaders in the space.
I don't think this approach is good at all, in fact, it feels neurotic and I think its an unhealthy obsession borne from my adhd, but its kept me going for the last 3ish years and I don't feel the slightest bit burnt out. personally I find the whole field of AI/ML to be immensely exciting so I think that part of it is a huge driver for how I personally stay up-to-date.
ideally I would offload a lot of these activities to a research agent and tbh I "plan" to eventually, same way I plan to gut short form videos and social media from my life and get 8hrs of sleep. Eventually.
I feel like they report in a vaccum. take this anti exfil policy for claude, it was plainly explained as part of the launch of Anthropics new product. Security like this isn't novel, it isn't bad, you don't explain how your security works to the people you're securing against. Nobody freaks out about Steam's VAC ban system, no one is investigating gmail's spam filtering, Reddits vote fuzzing, cloudflares bot detection, or Vercel for blocking proxying services.
whats really the distinguishing principle? Is it really just not liking Anthropic's opinions? then just say that and use a different llm. chemist, biologists, and AI researchers cry a river lmao
o3 is getting it no problem, first try, a simple and reasonable answer, 101 months. claude (opus 4.1) does as well, 88-92 months, though it uses target inflation numbers instead of something more realistic.
seems anything to do with asteroids (or explosions I imagine) are blocked.
this plays back into my original comment, which you have to understand to know that the sampler, for all its "randomness" should only be seeing and picking from a variety of correct answers, i.e. the sample pool should only have all the acceptable answers to "randomly" pick from. so when there are bad or nonsensical answers that are different every time, it's not because the models are too random, it's because they're dumb and need more training. tweaking your architecture isn't going to fully prevent that.
I think my deck of cards example still holds.
You could argue I'm being uselessly pedantic, that could totally be the case, but personally I think that's cope to avoid having to think very hard.
models themselves are deterministic, this is a huge pet peeve of mine, so excuse the tangent, but the appearance of nondeterminism comes from a few sources, but imho can be largely attributed to the probabilistic methods used to get appropriate context and enable timely responses. here's an example of what I mean, a 52-card deck. The deck order is fixed once you shuffle it. Drawing "at random" is a probabilistic procedure on top of that fixed state. We do not call the deck probabilistic. We call the draw probabilistic. Another exmaple, a pot of water heating on a stove. Its temperature follows deterministic physics. A cheap thermometer adds noisy, random error to each reading. We do not call the water probabilistic. We call the measurement probabilistic.
Theoretical physicists run into such problems, albeit far more complicated, and the concept for how they deal with them is called ergodicity. The models at the root of LLM's do exhibit ergodic behavior; the time average and the ensemble average of an observable are identical, i.e. the average response of a single model over a long duration and the average of many similar models at a fixed moment are equivalent.