This kind of thing only can happen in nascent/rapidly expanding fields that are desperate for talent. For example, post WW2 academia, early wall st, early big tech. Once a field is mature and more stable, young people are able to optimize their resumes and it becomes too competitive to enter.
Is it actually possible now in this information environment? The first 'day in the life of x' will lead to 100x applications submitted that very next day.
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Really interesting how the general view on Twitter of Fable 5.2 has been "eh, it's okay" while in these sorts of benchmarks it places extremely high.
Big news: Claude Fable 5.2 (Max) by @AnthropicAI takes #1 in Agent Arena with an unprecedented lead: +30.4% net improvement, about 1.6x the #2 model Opus-5.5, across 4.7k real-world agentic sessions from our global community. It's also #1 in Code, Chat and Work.
A major leap over Claude Fable 5.1 (Max)
- Rank: #5 → #1, Net improvement: +14.8% → +30.4%
- Median cost per task: $7.7 → $7.3 (6% lower). The API pricing $10/$50 → $8/$40 per million input/output tokens (20% lower)
vs. The Frontiers
- #1 Claude Fable 5.1 (Max): +30.4% | $7.3/task
- #2 Claude Opus 5.5 (Max):+19.5%) | $5.5/task
- #3 Gemini 4 Carbon (High):+17.0%) | $1.5/task
- #6 GPT-6-Astra (Max): +14.5% | $6.0/task
Breaking down performance across signals:
Fable 5.2 improves over 5.1 across all four reported signals, with particularly large gains in user satisfaction and steerability.
- #1 Praise vs. Complaint , +73%, biggest jump vs +41% the next model.
- #1 Steerability: +33%
- #1 Confirmed Success: +22%
- #3 Bash Reliability: +14%
#1 across all major categories
- #1 Code: +34%
- #1 Work: +31%
- #1 Chat: +27%
- Versus Fable 5.1: Code #6 → #1 (+19.8 %), Work #4 → #1 (+15.8 %), Chat #6 → #1 (+12.0%).
Huge congrats to the @AnthropicAI team on this incredible release!
I got the feeling that this would be the case after talking to opus 5.5 on its release.
going to pre-register this prediction (might end up very wrong!): we are now crossing the threshhold where a significant majority of *technical users* (white collar workers, but not at the frontier of their field, so like normal coders, finance people etc) will not be able to meaningfully distinguish between the actual best models (fable 5.5, astra 6.1) and their distills (sol 6.1, opus 5.5) because their work isn't hard enough to elicit the full capabilities of the frontier models. I think I crossed this point fairly recently with my professional work, and am probably getting close to it on some of my personal research projects.
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I think we are hitting a saturation point for routine coding tasks, the same way models after Opus 4 plateaued as chatbots.
For taste/judgement tasks like high quality art or open-ended research, Fable 5.2 is dramatically better.
I got the feeling that this would be the case after opus 5.5 dropped
going to pre-register this prediction (might end up very wrong!): we are now crossing the threshhold where a significant majority of *technical users* (white collar workers, but not at the frontier of their field, so like normal coders, finance people etc) will not be able to meaningfully distinguish between the actual best models (fable 5.5, astra 6.1) and their distills (sol 6.1, opus 5.5) because their work isn't hard enough to elicit the full capabilities of the frontier models. I think I crossed this point fairly recently with my professional work, and am probably getting close to it on some of my personal research projects.
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>maxed out at 25mph
>just under $20k
They will sell very few and then they will complain that Americans are lying when they say they want kei cars.
flaw retweeted
This is a good thread to understand the mentality of smart, well educated professors born abroad -- who now make up (in some cases) the majority of faculty in their departments.
Essentially, the system works fairly well for people born abroad.
I oppose this system because:
1. It does not work for americans.
2. It worked okay for internationals, but has been breaking down for awhile.
3. There are better ways to do this.
flaw retweeted
Replying to @doomslide
My biggest reason for skepticism about any remaining hard barriers is the intellectual history of ML itself leading to this moment, history which fractally resembles its output. Recall Rosenblatt? Hinton, Sutskever, Kingma, Vaswani? Mordvintsev's DeepDream, my personal "aha" moment? He's ResNet lol? What in all of that was a great paradigmatic leap? The King's road was just ironing out the logistics for connectionism, It's been continuous relaxation, iterative problem-solving, with some natural science analogies and combinations of tools of applied math available to above-average erudite scientists, and indeed pruning of too clever by half branches; and spectacular crashes of programs of those luminaries who grew too intellectually ambitious, like LeCun. Hinton himself assumed that his invention is a dead end facsimile, half-clever research prototype that can't measure up to the brain's actual algorithm; and his confidence in that was shattered by a joke from a model we'd only laugh at in pity today. At no point did we stall in need of some profoundly new mafs or a breaking conceptual insight – and yet we're here, where networks have learned to competently operate with human concepts, with the entire repertoire of reasoning motifs available to a frozen human mind (no I do not agree that the best models are wholly incapable of abduction, which you brought up before; they are grasping at it in long sessions, they try to condense their representations into compact hypotheses and come up with research arms to test them). Something is missing, partially clearly due to lack of demand, partially for reasons I don't understand. Indeed, I think the best public models can't even write this post unless provided with massive authored input, nor your rebuttals. But is that necessary? They are fast and cheap. From now on they will do hundreds of times as much qualitatively comparable iterative work as had been done to create them, as much as we can afford to pay. And incredibly, obscenely much had been paid upfront already. Where does this lead? Naive induction provides the answer. They will gradually do better and better ML research, developing better and better models. That is what is called "RSI". Its exact exponent is subject to debate and market incentives. When continual learning is adequately solved (with actual parametric learning on small batches), whether under human guidance or not, it will accelerate. I think it will be solved.
I can abstractly imagine being wrong, I've written on that xitter.twitterapi.xyz/teortaxesTex/status/18…, but do not actually believe that we have any solid reason to believe this ride stops or meaningfully slows down. That would be hubris, and unearned hubris in my case, and I – perhaps narcissistically – believe it'd still be hubris on part of those who have earned the right to it. The journey from perceptron to Astra was longer than from Astra to some Scholze. Humans differ a lot but they are not qualitatively different species, for all that mathematicians like to imagine themselves as such. If LLMs stop after conquering the level of mathematicians' parents, that'd be a big anthropological discovery before it is a finding about LLMs, and we're not exactly doing anthropology here, I think.
btw I've started having doubts about near-term transformative AGI. Timelines up to 2035 or 2040 seem plausible (my mainline scenario is ≤2028 still).
We have scant theory of human scientific genius and near zero reliable data on its inner operation. «A genius is just a scaled-up error-corrected human… with extra obsession», perhaps. Something something MCTS, neural noise, branching factor, iterative algorithms; there's no space in the genome for occasionally rolling a superior subspecies with very different mechanics and inductive biases; of course. But is even a properly trained LLM a scaled-anything human, or just an error-corrected interpolation of human reflections? What is the scaling law for the latter towards the genius?
And our attempts at making genius obsolete with scale and error-correction procedures have been, I believe, floundering since 1950s-70s; we're coasting on applied science and providing opportunities to geniuses which we do discover in a frenetically expanded talent pool. All papers I've seen about LLMs exceeding humans in "creativity", proving complex theorems or whatnot, discovering this compound or that architecture – have been meh upon scrutiny.
Scaling test time compute allows to approximate ever better the flawless work of a mediocre mind that is content to terminate itself in rabbitholes. We are not used to mediocre minds working flawlessly, as in flesh all faults tend to be conjoined. But flawless mediocrity is not genius. Since 2014 I've been a believer in artificial genius, and since 2015 all we've been getting in this regard were amazing demos that can't walk on their own legs towards the summit. Will this change by EoY? By EoY 2025? 2028, surely? On fundamentals, I have to keep predicting "yes, very likely so". But my faith wavers.
Galkovsky had this metaphor about a rat being chased into a bloodied corner with a multitude of tools (the rat representing himself, a Soviet citizen somehow incompatible with the regime and society around). A normal rodent is crushed swiftly. A talented one fights back, jumps more adroitly, bites at the fingers that hold the prongs, and perhaps even escapes into some lateral hole to survive another day or week. But a genius rat, if there is such a thing – flies away. Breaks the rules of the rat gridworld, violates the whole theory of the game in which the adversary exists. (Later this was, I think, referenced in Pelevin's Hermit and Six-Toe).
No doubt rats cannot fly, and certainly humans can't do super-Turing computations; whatever it is that we can do, our machines can do it too. Yet this is no guarantee that we won't need one more revolution before finally building a machine that is peer to the Gods among us – not merely a clearer reflection of their cast-off shells, still hopelessly beneath it.
What this means in practical terms is: we might not get all that many technological breakthroughs within a decade or two even if LLMs and their successors supercharge economic growth. Doordash bots but no cryonics. Automated Walmart but not SpaceX or CERN. It's possible that the world is a tougher nut to crack. You'd probably be wise not to act as if the end is nigh. Do your taxes, raise your kids, study your craft, live – and allow that you will die the way all previous generations have, with much the same means to minimize regret.
flaw retweeted
Very true. Almost all genuinely great artists take inspiration from diverse sources or direct experiences. Miyazaki was heavily influenced by Moebius for example. Modern anime is almost all self-referential slop xitter.twitterapi.xyz/animeupdates/status/21…
Hayao Miyazaki on modern anime, via Roland Kelts the author of 'Japanamerica'
"Hayao Miyazaki said to me at one point: 'The problem with young anime artists today is that the only thing they study is anime. When we were young, we studied French literature, we studied impressionism, we read Dostoevsky. We swallowed everything. And then we went and created original anime. But if you grow up and all you watch is anime, you're just regurgitating spinning wheels.'"
He also spoke about his work on the upcoming documentary 'Tezuka! God of Manga'
10/7 was about as precise as the pager op. 30-40% of victims were lawful combatants iirc.
Cool that you think it was incredible, very open minded of you Elai
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Just from looking at publicly available figures (Wikipedia), this seems false. The death toll claimed by Lebanon is 42, 12 of whom were civilians. Injuries were approx 4000, and there isn't official information on the makeup of injured.
en.wikipedia.org/wiki/2024_L…
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Era of math as experimental science. AI proof dumps are more like cern saying "we have experimental data for new particle" than anything else.
Replying to @ElliotGlazer
For the cited theorems, I’ve had my agents do a full inventory of conventions used in each, to avoid incidents like OpenAI withdrawing three manuscripts due to a convention-mismatch sign error. It would be unprecedented for a faulty manuscript to survive this level of scrutiny.
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we have reached levels of linguistic drift where 12 year old boy preferring hatchet over Jane Eyre apparently makes him an incel... Like what are we doing here guys?
in this case you might be typical minding them I fear. there’s a certain subtype of being a shut in who reads a lot more tho. Reading books especially rather than web fiction slop is probably pretty rare. (I read web fiction slop but I am 31 LOL)
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Replying to @MaleManlpulator
I would have found her comment totally unobjectionable if she had merely said "hatchet is not that good, we can do better." -- what bothers me is the framing of young boys as "would be incels" in the first place.
Like imagine if we were like, "the scarlet letter sucks. There must be a better way to reach would be sluts". Like it's just a gross way to talk about kids.
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Replying to @MaleManlpulator
That's the charitable reading sure. But why even mention incels here? We're talking about prepubescent children, none of them are having sex lol. It's purely to signal a distate for boys who have different preferences than her.
flaw retweeted
Claude successfully disputed this erroneous tax charge, not proactively but otherwise with no input from me. Correlations being what they are, should this make me optimistic about life extension?
This shit put my age at 39 years old time to kms and/or go clean shaven
TikTok also scores how attractive you are, guesses your age/gender, and calculates your mood with some of these on-device models.
I pulled them out of the app, so you can try it directly here: ayoships.com/tools/tiktok-fa…
I ported them from ByteNN so they run in your browser. My tests showed significant negative bias against darker skin and older faces.
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We really do need to inform the children that reading a non-preferred text will not kill them.
Hatchet was boring. So what? It's only 41k words. You will live. This is not a thing to be butthurt about *as an adult.*
I don’t remember girls hating Hatchet. But unfortunately it is kinda true that girls will read anything and boys need books to be “boy books” to be interested.
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