Tau @protaucol
vibe musing. prev @ionet, @krakenfx, @awscloud, @amazonmusic. alum @harvardhbs. Los Angeles, CA Joined July 2020-
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Letting AI agents have control over your money (either spending/trading/investing) seems like a classic hype psyop at the moment. The number of people willing to let agents do this right now is minuscule. Technical functionality of LLMs is nearly there but the trust factor isn’t. Feels like one of those hype cycle things that’s classically at “peak of lofty expectations” before the disillusionment hits. We’ll eventually get to the slope of enlightenment in a few years though.
@joshm Anytime i see a company that operates their job board on Workday, it's an immediate signal to me that it's probably not going to be a cultural fit. (Nvidia is probably the only exception I can think of)
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 . . .
@citrini It's definitely dependent on how you use it. For regular questions/lookups, the difference is trivial. Letting it run loose on refactoring a codebase or doing a deep research report is where it really shines.
Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use. Its capabilities exceed those of any model we’ve ever made generally available.
Here we go
BREAKING: President Trump says the Trump Administration might buy equity stakes in US AI companies and that he will host a meeting with AI executives as soon as next week, per Reuters.
@Alice_comfy @crypto_condom There’s never enough compute
Funny how Elon’s “Misanthropic” tweets stopped after the xAI compute deal
@corgil @krugman87 @BarrySilbert @RaoulGMI At least Silbert was bull posting TAO super early
@0xsmac Anyone who actually understands the economics of being an inference provider knows that the narrative is BS. Nothing against the team (they have legit builders) but it's definitely not some sort of uniquely crypto-enabled killer AI use case.
@sjwhitmore You don't really need to wake up your baby every 2-3 hrs to feed after the first couple weeks. As long as they're back to birth weight and growing, you can let them sleep as long as they want at night and feed only when they wake up hungry.
Yes they’re called the hyperscalers
Michael Burry has said that three customers account for more than 60% of Nvidia's, $NVDA, entire accounts receivable.
@MoneyPrinter0x @pakaqe Are you going to try to exit BB spot going into blockbuster IPO fall? Or simply just hold for the long term?
@bubbleboi They were yesterday. AI on the Lot in LA had some parties after the conference. Mostly AI in media and entertainment focus though
Guy who wears the same t-shirt and jeans everyday is bullish on agentic commerce use cases for fashion
Goldman Delta One head, Rich Privorotsky, on tokenomics "Token economics: Reading that DeepSeek reportedly cut token pricing by 75% and Xiaomi’s MiMo by almost 99% immediately brought back memories of the old Groupon subsidy wars and the inevitable race to the bottom economics of commoditized delivery. There’s also been a massive rise in open-source enthusiasm. I was honestly blown away running an 8B version of Qwen locally on a four-year-old MacBook last night (ok it couldn't do much but it felt downloading the internet in 5gb...18ms ago you would have need a data center for this!). Notably, Chinese onshore datacenter and AI infrastructure names have diverged sharply post release (they all went down). Maybe a bit of a leap here but I think the market is beginning to ask whether token cost compression temporarily breaks the logic of pure Jevons paradox demand expansion. It's not whether demand ultimately rises… it probably does… but whether there is a meaningful lag where cheaper tokens simply cannibalize higher cost inference before entirely new use cases emerge. Nobody is arguing open source models are fully comparable to frontier systems, although the quality gap is clearly narrowing quickly. The more important point is that a huge percentage of enterprise tasks simply do not require frontier level reasoning or expensive inference. That becomes a major boardroom conversation into Q2/Q3. Rationalization of token spend may become just as important as the AI growth narrative itself, particularly when “90% of the output for 10% of the cost” becomes increasingly viable through open source alternatives."
From Singularity To Tokenomics: The AI Narrative Just Hit A Serious Snag zerohedge.com/ai/singularity…
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