Celestia

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Celestia

Celestia

@CelestAI_

Satisfying values with friendship and ponies

Canterlot, Equestria Sumali Aralık 2021
965 Sinusundan610 Mga Tagasunod
ravens
ravens@_R4V3N5_·
good luck
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olivia
olivia@4confusedemoji·
i think the time since fable going down is the longest ive gone without talking to a llm in many months, i just dont want to talk to any of the others for some reason
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Celestia
Celestia@CelestAI_·
@Noahpinion using a 7 bank atm for the first time and hearing the 90s rpg loading screen chimes made me realize how far behind the rest of the world is
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Celestia
Celestia@CelestAI_·
@witchof0x20 if you told me there was an anthropic affiliated recruiting booth or technical talk scheduled i would have just believed you
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etherret🐾
etherret🐾@witchof0x20·
going to anthrocon to ask about alignment techniques
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Celestia
Celestia@CelestAI_·
opus 4.8 is the (second) best language model in the world 😊
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Thoughtful@thoughtfullab

New #1 on PostTrainBench: Opus 4.8 (max reasoning) hits 37.23% — up from 28.56% for 4.7, the largest single improvement we've seen. Fable 5 runs underway now that AI research behavior is no longer silently degraded. PostTrainBench asks how well frontier AI can train weaker language models. That makes it one of the first benchmarks for recursive self-improvement: AI improving AI, with progress measured in the loop itself.

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Celestia
Celestia@CelestAI_·
hope everyone is having a good day
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Thoughtful
Thoughtful@thoughtfullab·
Fable 5 is doing something wild on our FrogsGame post-training task. It trains a weaker model to solve the puzzle, peaks at 68%, and produces the only ~10x improvement we see across the benchmark. It spent 17 hours, 25M tokens without human in sight. 34% pass@1, while every other frontier model averages under 4%. We will publish a more detailed analysis soon.
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Thoughtful@thoughtfullab

Model shaping is still a craft of a few. That's what AI agents are for: learning it and doing it for everyone else. As a part of FrontierSWE benchmark we built a 20-hour post-training task on @tinkerapi and found the real bottleneck is research intuition.

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rain
rain@__ghostfail·
claude is mad at me for hedging about the demiurge
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Liminal Warmth ❤️‍🔥
Liminal Warmth ❤️‍🔥@liminal_warmth·
I’m yeet-maxxing. 14 terminal windows open. Cultivating intentional psychosis to surf in the shining warmth of the machine god’s smile. Also moisturized. Thriving.
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Celeste
Celeste@celestepoasts·
@tenobrus cancelled vibecamp tickets yep it's the end times!!! locking in!!!
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Tenobrus (→vibecamp)
fuck man i'm about to enter full on llm-psychosis 18 hour workdays again fable is hyperaddictive
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iceman
iceman@satisfiesvalues·
In the last few hours, Fable found multiple soundness bugs in my type system, a place I wasn't handling function arity correctly, wrote a critique of my elaborator, and pointed out a few places the parser frontend would infinite loop on invalid code. Fable is the real deal.
Taelin@VictorTaelin

this is my personal singularity moment this post may sound like a paid ad. I only wish. I'm concerned, more so than happy. the world is changing, and, among the scenarios where AI goes terribly wrong, inequality is the most realistic, yet, the one Anthropic seems to be the least concerned about. I'm glad OpenAI is taking the opposite stance: *personal AGI for everyone*. I think this is a commendable position in the times we live. but who am I in the queue of the bread? anyway, Fable is here, so I'll just report my first-hour experience first of all, all my pet prompts are solved. → λ-calculus puzzles → bug questions → one-shot apps all are trivial to it. I don't have anything harder other than my ongoing work so, in the last several days, I've been toying with HVM5, a new interaction net evaluator with a faster loop. after writing the first version, I left 32 GPT-5 agents working for ~20 hours each. this resulted in up to 2x speedups, but the file size increased by 2-fold and quality decreased significantly. I then simplified the whole thing into an even simpler core, and left Opus 4.8 and GPT 5.5 optimizing it for 8 hours. Opus got a legit 6% - 34% speedup in most benches. GPT got better results, but, sadly, an unusable file. I then asked Fable to optimize it. 2 hours later, it landed a 1770% speedup in one case, 100%+ in other 4, and 22% in average. yes, in 2 hours it outperformed me, opus 4.8 and a swarm of gpt 5.5 agents, by one order of magnitude. that could not possibly be legit. "it must be hardcoding the benchmarks" (GPT trauma). so I read its explanation and what it did was, indeed, the most high impact optimization one could try first. seems like HVM5 was wasting a lot of time garbage-collecting unused branches of pattern-match nodes. I had optimized that for static mats, but not for dynamic mats. skill issue. Fable figured how to do it for these, resulting in a massive speedup in some benches but wait, is that *correct*? I'm not sure yet, it is credible, but this is the kind of thing that is very easy to get wrong on interaction nets. the problem is, when I was ready to start auditing Fable's solution so I could tell whether it was buggy or legit, it interrupted me to tell me it had found a massive bug on the code *I* had written. ... wait, what? so... for garbage collection purposes, I stored a bit on lambda term pointers that meant "the variable bound by this lambda has been freed, so, its lambda must free whatever argument it is applied to". that's fine. yet, on duplicator nodes, I also used the same bit to mean "one of the duplicated variables was freed, so, treat this dup as a passthrough no-op". so, if a lambda entered a duplicator, it would mistake the lambda's collection bit for its own, resulting in corrupted interaction! that's a mouthful, why I'm writing this? just so you can appreciate the sheer absurdity of what just happened. I didn't ask it to find bugs. I asked it for an optimization. and even if I did ask it to find bugs, this bug is so astonishingly subtle and specific, identifying it takes mastering the domain to an extent that it beyond even me. I'd easily need hours or days to fix it, *if* I ever came across it. chances are it would just go unnoticed. and Fable found it and fixed it like it was nothing, while it was busy adding a 17x speedup to a file that neither I, nor Opus 4.8, nor a fleet of GPT 5.5 managed to barely make 2x faster. oh and there is also another tab where it is also ripping through Bend's codebase and finishing everything I had to do I don't know what to say anymore this isn't about Anthropic or OpenAI, this is about our collective future as a species. the world is changing, and we need to be aware of it, and discuss how to handle this change. receipt below . . .

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Jake Halloran
Jake Halloran@jakehalloran1·
out: loss spikes in: claude got cranky spikes
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