Earlier quoted context omitted.
Agree with this. Strange to me to frame the "training recall" as cheating (33 of the 38 cheating instances). Most people think of "cheating" as breaking rules. How is the LLM model supposed to not use what was put into the weights?
By writing a not-identical, but valid, solution? Any modestly complex engineering problem has many solutions. This is an obvious example of why LLM training is so different than human learning.
Claude Fable 5: mid-tier results on coding tasks
91–100 of 271 posts
Re: Claude Fable 5: mid-tier results on coding tasks
#92Earlier quoted context omitted.
What you're describing only applies to security or biotech downgrades. A downgrade related to the model believing that you're doing something related to model development is invisible and silent and internal.
Anthropic has reversed that decision. (But that just happened so it might have been true during the article's testing.)
Re: Claude Fable 5: mid-tier results on coding tasks
#93This matches my experience. Burned $2K to see how it will perform on frontend tasks and backend tasks. Frontend did a significantly better job than Opus on toy-scale wireframe projects by using gimmicks like fluid dynamics. Then when given medium to big tasks like multi-page web app where layouts and aesthetics must be decided by model itself, results by Fable and Opus scored indistinguishable score from human judges…
This seems insane to me. Aren't long running tasks an anti pattern at the moment? My understanding of literature is that small mistakes in chat history cause a trend away from performance
Longer running tasks require better setups and several ways of pinning the progress to reality. When you have that though things are quite all right.
A good long running task will run inside a framework that it's not trying to modify.
Re: Claude Fable 5: mid-tier results on coding tasks
#94> Anthropic's headline cyber evaluations mostly measure offensive progress (exploits, PoCs, challenges); our benchmark tests whether a model can actually generate safe code, and there Fable 5 did not stand out. The model isn't allowed to think about security. I heard several people here mention that if it starts thinking about security -- e.g. writing tests related to it -- the safety filter flags it and downgrades t…
Anything designed to prevent a problem will eventually cause one.
Re: Claude Fable 5: mid-tier results on coding tasks
#95Earlier quoted context omitted.
Umm? I'm getting usage capped on single prompts of Fable 5 with the $20 subscription.
I used it yesterday afternoon-night and this morning-afternoon, UK time, over a period of a few 5-hour windows. I didn't count the prompts, wall time was 1d6h, API time was 2h10m.
Re: Claude Fable 5: mid-tier results on coding tasks
#96Earlier quoted context omitted.
I have been wondering whether Anthropic are just gaslighting everyone with new model releases while in reality it's just the same base model with some internal knobs tuned more and more up with every new release to provide longer and longer thinking threads and outputs. My speculative assumption is that these long thinking threads and self-checking tend to produce somewhat better output at the price of huge price inc…
I imagine it's the same foundation model on the 4 series, with Fable 5/Mythos being a new or upgraded foundation model. Then the point releases are fine-tuning plus post-training alignment with desired outcomes. The "thinking" can involve multiple steps, eg. asking the model first what it thinks the user wants to do, why it wants to do it, rewriting the prompt to generate better outcomes, how it should do it, come up…
I'm guessing there'll be a Sonnet/Haiku 5 release just around IPO, to keep the news cycle going, and so that user numbers will get a boost.
Re: Claude Fable 5: mid-tier results on coding tasks
#97Earlier quoted context omitted.
I’ve found that agents are obsessed with adding more lines of code. Even when asking them to simplify they’ll remove 50 lines of code and then add 100 more. You have to explicitly tell them you want less lines of code. So I just do that after iterating on a task for a few steps.
I have been wondering whether Anthropic are just gaslighting everyone with new model releases while in reality it's just the same base model with some internal knobs tuned more and more up with every new release to provide longer and longer thinking threads and outputs. My speculative assumption is that these long thinking threads and self-checking tend to produce somewhat better output at the price of huge price inc…
If you read a decent text and look at the actions both firms have taken you'll quickly see its literally textbook.
Re: Claude Fable 5: mid-tier results on coding tasks
#98Earlier quoted context omitted.
A single 8h task? I'm sorry, but that's just asking for trouble.
I don't understand how some of y'all use these things. I get garbage unless I give them very specific concrete tasks with as much context as possible. Anything that takes more than 30 min is usually a waste because the scope was too large.
There seems to be some kind of AI hysteria going on, with people becoming so enamoured with the AI that they accept anything it produces as if it's some gift from the gods, while others just reject it prima-facie.
For example, the worst design I have seen recently was from a designer who pivoted into "vibe coding influencer". The worst code is from developers who were heavily into Clean Code a couple years ago and now half their PRs is unused dead code.
Re: Claude Fable 5: mid-tier results on coding tasks
#99Earlier quoted context omitted.
What you're describing only applies to security or biotech downgrades. A downgrade related to the model believing that you're doing something related to model development is invisible and silent and internal.
Anthropic has reversed that decision. (But that just happened so it might have been true during the article's testing.)
Re: Claude Fable 5: mid-tier results on coding tasks
#100I've been making an auction site and have been using an AI swarm to test it: sellers, intermediaries, buyers, market practices/norms etc. I was mostly using GPT 5.5 xhigh to code up the scenario, and looping over it to check with opus 4.8. Out of curiosity I asked Fable to review it all and I was shocked to find that there were a lot of blindingly obvious common sense mistakes that got through, for example: - all int…