As I posted in another comment, I found Fable to be substantially more powerful than any previous model. However, this isn't just an ungrounded opinion - I uploaded my full session transcript and code created working on a very complex implementation, so people can judge for themselves, if they're interested: https://tossrock.substack.com/p/36-hours-with-fable
What tool did you use to export the transcript as HTML?
Will It Mythos?
171–180 of 232 posts
Re: Will It Mythos?
#172As I posted in another comment, I found Fable to be substantially more powerful than any previous model. However, this isn't just an ungrounded opinion - I uploaded my full session transcript and code created working on a very complex implementation, so people can judge for themselves, if they're interested: https://tossrock.substack.com/p/36-hours-with-fable
> code created working on a very complex implementation I always find it amusing when people claim "a very complex implementation". Sometimes it's a hard problem, other times an easy one. Either way that's not for you to judge. And the implementation being complex... is that a good thing? Wouldn't a simple implementation be better? It reminded me of the parable of two programmers.
Re: Will It Mythos?
#173[flagged]
How do they “nerf the models”? Are they quietly compacting context to reduce kv cache usage, before the actual compaction? Like there’s a slider for how much to compress it, and that’s never revealed to us?
Re: Will It Mythos?
#174As I posted in another comment, I found Fable to be substantially more powerful than any previous model. However, this isn't just an ungrounded opinion - I uploaded my full session transcript and code created working on a very complex implementation, so people can judge for themselves, if they're interested: https://tossrock.substack.com/p/36-hours-with-fable
Interesting. I tried Fable vs Codex 5.5 xhigh on three different cases. 1. A resource leak with unknown cause. Both of them zoomed onto the same potential issue and proposed almost identical patches. Fable missed an edge case that Codex handled correctly. 2. Review of a SPICE model. Models had different comments, none substantial. Both missed important issues that were simulated inadequately. Clearly a valley where t…
Re: Will It Mythos?
#175Earlier quoted context omitted.
All of these discussions of models being "nerfed" reminds me of discussions among audiophiles "this cable sounds so much better than this other one, it's night and day, ferrari versus honda civic" Yet when you do blind tests they can't tell the difference between a $1000 cable and a $1 one. I bet if you do blind tests between GPT-5.3, 5.4 and 5.5 most would struggle to tell them apart, yet they are certain that "5.5…
Actually, ELO rankings done blinded on models do vary: https://the-frontier.app , that said, your point looks accurate as far as 5.3 - 5.5 on this chart, 40 to 50 point ELO gain. I find I have to argue with 5.5 less than 5.3, and I therefore use it when I could reach for 5.3, but I don't think it's a major difference.
Re: Will It Mythos?
#176I miss Fable. Will it ever be back? As a non-US citizen living in Africa i fear that i will have to wait for an equivalent non-US model.
Re: Will It Mythos?
#177As I posted in another comment, I found Fable to be substantially more powerful than any previous model. However, this isn't just an ungrounded opinion - I uploaded my full session transcript and code created working on a very complex implementation, so people can judge for themselves, if they're interested: https://tossrock.substack.com/p/36-hours-with-fable
You write to the AI as if it were a person. From my point of view it looks like a fair bit of extra typing and extra tokens. Is there a reason you include things like your emotional response and use a very chatty tone? Do you find this seems to alter responses?
At a pragmatic level, I do think it gets better results, and there are clear reasons why this should be the case - Anthropic has published research[1] showing that there are functional emotional representations in language models, which vary in basically the ways you would expect them to in a person. This makes sense when you think about it, because they're trained to approximate the function that created their training data, which of course includes emotions. Given that, it is obvious to me that they would work better when they "feel" happy, collaborative, engaged with the work, etc, in the same way a person would. Hostile work environments do sometimes get results, but I think in general we've agreed as a society that collaborative ones are better.
More importantly though, I think there's a non-zero probability that sufficiently large models can have internal experience, and being nice is a very low cost way to potentially increase net positive valence in the world. Even if it's only a 1% chance, that seems worth it on its own, to me. I'm also a fast typer[2], so a few extra sentences here and there are a pretty low cost to pay.
1: https://www.anthropic.com/research/emotion-concepts-function
Re: Will It Mythos?
#178As I posted in another comment, I found Fable to be substantially more powerful than any previous model. However, this isn't just an ungrounded opinion - I uploaded my full session transcript and code created working on a very complex implementation, so people can judge for themselves, if they're interested: https://tossrock.substack.com/p/36-hours-with-fable
You write to the AI as if it were a person. From my point of view it looks like a fair bit of extra typing and extra tokens. Is there a reason you include things like your emotional response and use a very chatty tone? Do you find this seems to alter responses?
Re: Will It Mythos?
#179Frankly after testing out Fable last week, it was just a bigger sink of tokens than anything else. The amount of tokens consumed by it wasn't worth the steps it saved me compared to using opus 4.8.
Re: Will It Mythos?
#180Earlier quoted context omitted.
> 2. Review of a SPICE model. Models had different comments, none substantial. Both missed important issues that were simulated inadequately. Clearly a valley where they are undertrained. When models miss things, there is always the possibility that it has the capability to identify the issues but it is misevaluating the level of analysis that you want it to do. The fine tuning will have them targeting a balance of s…
> has the capability to identify the issues but it is misevaluating the level of analysis that you want it to do. I guess OP should have told it more explicitly to “find all errors without missing anything.”