The classifiers Anthropic puts in front of Fable are too zealous

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• The most basic machine learning-related query gets flagged for me. For example:

    In flax nnx, what's the idiomatic way to store state on a Module. For example, if I'm handling the carry manually for an nnx.RNN.
  

  Or one asking about a checkpointing package:

    How do I restore one of the orbax checkpoints into NNX from this script?
  

  I also got flagged for asking about syntax highlighting in the Helix editor.

  It's a shame - I like Fable for writing tasks over ChatGPT and I do believe Anthropic is a more ethical outfit than OpenAI. But with the safeguards (and Fable access expiring in a few days) there's no reason to pay for draconian guardrails and harsh rate limits.

  by ainch
• The story here is that proprietary AI sucks and you shouldn't use it.
  by Cider9986
• all useful models are proprietary.
  by doodlesarefun
• the ancestry predicate at the beginning of the formal problem statement here is dominance, at least as applied to their rooted trees.

  Because it is a rooted tree, only DFS intervals are required to determine ancestry.

  You can detect whether a new blocking loop is going to be formed through online dominator maintenance/online cycle detection, etc, during optimization, rather than use a heuristic, if you wanted to.

  Not sure it's practically faster, but that's at least the graph-theoretic answer.

  In practice, outside of the suggested heuristic, I have to imagine you'd normally throw branch and bound at this, using some lazy-cut for the blocking loops (IE you can keep any of these edges but not all of them) and let it go to town.

  The paper (at least, this paper) doesn't compare that to what they did, and i'd be shocked if someone hasn't tried this before, so not sure it's useful.

  I'll also say you can get existing AI models to tell you the above, but you have to push them a bit most of the time step by step. Just handing them the whole overall problem, as described, and saying "what are the graph theoretical problems related to this" it sort of gets lost.

  Probably because the LLM isn't doing a good job of predicting graph-theoretic words when the language is not graph theoretic, but if you translate it into a graph theoretic language piece by piece, and ask it about that, the prediction becomes better :)

  by DannyBee
• To summarize: the classifiers Anthropic puts in front of Fable are way, way too zealous and have way too many false positives.

  From my experience, the model itself is very useful when it isn't refusing any of your prompts.

  by meowface
• How do you know? Is it really that obvious of a tell between Opus and Fable? My understanding is that they silently downgrade you.
  by ares623
• Thanks - that's a good phrase we can use to replace the baity title. I've done so above.

  (Normally we prefer to find a representative phrase from the article itself, but I found that too daunting and gave up.)

  by dang
• It is, but it's also using tokens at absurd rate, I asked it to review the planned architecture for a medium scale project and it used my 5 hours limit on one prompt just zaaaaap, not even the fable limit straight up the full 5 hour session no more Claude for the afternoon thank you for paying you Max x20 sub. Hell it didn't even bother to finish produce anything worthwhile.

  And just to be clear, plan was already done, just had to review it, it got opus 4.8 Max and gpt 5.5 Extra High validated already and they didn't use much resource for it so I just don't get it. I guess they want to use it as a way to feed the extra credit money income.

  I'm using a homemade ai consensus thing for planning and I wanted to add fable to it but forget it.

  Or maybe I should use fable in low effort reasoning mode and it will be better than opus 4.8 at max ?

  by nolok
• I've found in my current work on a security auditing harness and benchmarks, both Fable and Opus are useless. I recently switched to using GPT for Nelson and the security benchmarks I've been doing because Opus started refusing to do the work. I guess I probably could also use GLM or DeepSeek or MiMo, and I'll probably do some experiments to see the shape of all of their guardrails in this area soon, now that I see it's more than one model that behaves this way (Gemini in Antigravity also refuses any security auditing task, even as simple as "find security bugs").

  I blogged about it: https://swelljoe.com/post/why-i-had-to-switch-to-gpt/

  by SwellJoe
• This underscores a huge risk of broad agentic adoption in an enterprise. Your engineers atrophy and if the agent provider decides to squeeze you, you’re SOL.
  by christophilus
• I've had good luck getting it to debug (and patch) a tricky WebRTC issue that had all the other models stumped. Sorry it didn't work on your problem, I guess?
  by ai_critic
• I'm curious what the state of alignment research is. My gut says this is basically impossible. People have different moral frameworks. Each individual probably has an inconsistent moral framework. Even granting perfect consistency, applying these typically requires some knowledge of reality. And these LLM / harness combos are turing complete.

  So you don't know what it should do, you may not even know what you would do, you don't necessarily know what's happening, and can't predict what will happen. How do you align that?

  Seems like these overly sensitive filters are responding to this difficulty.

  by sobellian
• it's anthropics moral framework that matters, not the myriad of moral frameworks of the individual users
  by htrp
• I'm a medical physicist. I literally haven't been able to get Fable to answer a question I have written -- all of my work is verboten. I have however asked Claude Code (opus 4.8) to ultracode "a Fable oracle that <deals with the high level difficult problems> in a digraphed, clean content, isolated environment with a minimally scoped working codebase. Ask the model at the start and the end to report exactly what its version string is. If it is not claude-fable-5, stop the agent and refine the prompt until this changes"

  It burns through tokens like anything but apparently Claude is much better at prompting Claude than I am.

  Would I pay for it? God no. I'm still smarter than I am and it just will not work on my actual problems.

  by azalemeth
• My theory is that they included/didn't align-away extra biology/chemistry in the training in preparation to offer an unrestricted/less restricted model to pharmaceutical companies/trusted partners. This would necessarily require a filter between the, now more "dangerous", model.

  I always assumed this would be the eventual way to manage high intelligent/"dangerous" models, since all evidence shows that alignment makes them stupid: leave the actual model on the "too dangerous for the public" side, and put a censor between. When I've mentioned this a few years ago, people said this would be too expensive, but I think everyone underestimated the amount of money being thrown at all of this. :)

  by nomel
• I asked it a question about indoor carbon dioxide levels (wholly innocuous question), which it flagged as involving biology, therefore downgraded to Opus.

  It's a pretty good strategy if they're hoping to fail as a business, I guess.

  by ergonaught
• I think they're not testing Fable as much as they're testing guardrails which they can later apply to anything they want.
  by pmdr
• Fable was refusing to patch vllm for me when trying to get mtp to work on r9700 gpus. Kept on bumping down to opus. Tried to really sanitize my prompts and everything but it seemed intrinsically prohibited from doing this sort of work. I guess it’s useful for making inane one shot games and websites, lol.
  by vardalab
• same experience here, as soon as it touched any gpu code it stopped working
  by _davide_
• That's where the free marketing comes from.
  by pmdr
• I was recently using self-hosted DeepSeek V4 Flash to poke around the DSpark implementation in vLLM (well outside of my domain)

  I did wonder if I was doing anything Fable would have flagged - sounds like yes.

  by wolttam
• Anthropic's TOS clearly says they don't want to facilitate any sort of distillation, it's not a stretch to think they will limit any sort of learning on improving other models.
  by chews
• > Tried to really sanitize my prompts

  And in doing so, you probably got your account and prompt flagged for 'attempted jailbreaking' (apparently, such scores are remembered for up to 7 years).

  by mrandish
• For anyone using these models for anything remotely sensitive, keep in mind that Anthropic says [0]:

  > We retain inputs and outputs for up to 2 years and trust and safety classification scores for up to 7 years if your chat is flagged by our automated trust and safety systems as violating our Usage Policy.

  And, since those automated systems apparently have a ludicrous false-positive rate, you should assume that your inputs and outputs are being retained for 2 years even if you are doing nothing that any reasonable person would consider to be problematic.

  Oh, and they'll train on that data [1]:

  > We will use your chats and coding sessions (including to improve our models) if:

  >You choose to allow us to use your chats and coding sessions to improve Claude, learn more here

  > Your conversations are flagged for safety review (in which case we may use or analyze them to improve our ability to detect and enforce our Usage Policy, including training models for use by our Safeguards team, consistent with Anthropic’s safety mission)

  It appears that the usual controls (including for businesses) to prevent Anthropic from training on your data will not apply.

  [0] https://privacy.claude.com/en/articles/7996866-how-long-do-y...

  [1] https://privacy.claude.com/en/articles/10023580-is-my-data-u...

  by amluto
• As a related note: The only way a consumer can get ZDR protections for Claude or OpenAI is to use Amazon Bedrock. But as you say, doesn't work for Fable. I think it even requires approval for anything past Opus 4.6.
  by matthewdgreen
• This post can essentially be distilled down to: yes, Fable's classifier (which is meant to downgrade cybersecurity, biology, or jailbreak attempts to Opus 4.8) is definitely overly sensitive to the point of uselessness.

  e.g. a colleague asked Fable to help create an simple app to help calculate the statistics for phase II and III trials. (Ignoring that such things already exist) it passed his request down to Opus, despite only being very marginally, tangentially, somewhat related to biology.

  by mft_
• The post can be distilled down to a simple statement, but part of the writing is for the author to express themselves and tell a story. I thought it was an interesting read.
  by mattjoyce
• Anyone test the "Gay" jailbreak to see if it works on Fable?
  by t1234s
• I've been working with it heavily since its first release. I use it for software architects, complex debugging and some development and I have not had it refuse or downgrade even once.
  by smcleod
• I've been working on a SDN software for mikrotik routers (and wireguard, etc) and Fable dies when working with any kind of wireline protocol or potentially implementing any authentication mechanism.

  It's too the point where I just stopped using it. If you do generic stuff, it's fine. But the second it tries to start debugging protocols (which may include auth) that's where it begins to fail.

  by bb88