aurelium.me
she/her
I have been to the future, and I don't want to scare you...
176 posts
305 followers
305 following
Getting Started
Active Commenter
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the problem with buying out a platform to amplify your political leaning is that everyone finds out your political leaning. which is not good if all of your money is vibes
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in principle i would say "more" but honestly in his hands I think it has made him negative money if anything
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i'm not really sure on the causality there? i sort of struggle to imagine that "the Light World is a small suburban town populated by monsters" was only cemented less than a year before Deltarune first came out in 2018
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i do wonder how different of a game Deltarune would be if Undertale didn't exist (or wasn't popular). he had it in his mind well before undertale began development, but certain elements (the town especially) kind of only really work as callbacks
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true
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i am always baffled by posts like this. where are these people seeing all of these unbearable posts? to the extent that i have problems with bluesky it's "some people aren't here", not "i am forcibly made to look at Bad Posts"
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the primary argument seems to be "my standard for 'generalizable reasoning' is that it should reliably execute any program given enough time to think about it" which seems like a definition that excludes humans from the "capable of reasoning" camp
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i think it's a pretty strong claim to make from pretty weak data. it's literally just "we took a bunch of problems with super unfavorable time complexity and tasked reasoning models with executing pseudocode to solve them, and they dropped off to 0% accuracy around the thousand-step mark"
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on some level i am sympathetic to her position, in the sense that i understand the impulse, but i find it Odd that she chooses to focus her ire so strongly on immigration specifically. surely if you wanted "tolerance for gay people" to be a prerequisite of being american we should start at home
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imo, with current methods you could 100% create an LLM that Actually Understands that there is an outside world it can source information from and not just an uninterrupted stream of text it is roleplaying in. but doing that is way harder than "make model smarter at coding" so nobody does it
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i think this is legitimately a big problem for LLMs but not necessarily an inevitable one. imo the problem is that all modern post-trained LLMs are sort of a hodgepodge of 2023-era "I'm ChatGPT, a friendly assistant" and modern RL stuff that lends itself poorly to grounding
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when the primary policy thrust of the left w/r/t AI is "massively expand copyright in the vain hope of banning it forever" it is massively unprepared for the actual political ramifications of synthetic media and knowledge-work mechanization
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imo the biggest failures of the modern left are when they fail to do Material Analysis in favor of some underbaked deontological argument. the AI stuff is a good microcosm of this, with material harms from things like deepfakes eschewed in favor of reactionary bullshit about "soul"
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i guess the way i use it isn't totally consistent with its use in philosophy, where "idealism" is usually thought of as a philosophy focused on human minds as the most basal thing where materialists see the outside world as the most basal things with human minds existing within it
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tbh i think the reason it hits so many roadblocks is that conceptually the project of leftism is a materialist one but practically most people approach it as an idealist one
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i feel like the anti-AI people are really refusing to think of the effects of requiring licensing for the use of text in this manner. because like, obviously this wouldn't actually stop commercial LLMs from being developed. they would license 20T tokens and stop. it'd just ban open research forever
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yeah. while i am largely unhappy with the reactionary anti-tech zeitgeist on here, it's not as if it's impossible to find people who aren't like that. there are plenty of people.
every social media website sucks when you first sign up, you have to Follow People and Curate Stuff
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yeah, they're not really really "mobile" so much as "portable". it'd have to be pocketable, which I don't think is really practical for a controller-based game console. the 3DS (before they made them huge) was the best anyone did imo
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i don't have numbers to prove this but i would imagine the average AI datacenter gets more of its energy from zero-emissions sources than the average home or commerical building, purely bc if you want a place with cheap, abundant energy it's gonna be solar or nuclear
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at this point i get the impression that this is not true. model sizes haven't really moved much since 2024. "Orion"/GPT-4.5 was the final nail in the coffin for increasing parameter count. outside of that frontier models have mostly been getting smaller
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i mean i guess it's coherent, in the sense that if you value LLMs at 0 then all LLM inference is using more power than it's worth, but it's not actually A Problem in the sense that banning LLMs globally would have a basically immeasurable effect on CO2 output
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the claim is not "inevitably, AI will use more power" but "soon our product will be so useful that we will commit all of our resources to using it". if you don't believe that's going to happen obviously the power usage will not 20x
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a lot of it is also founded on uncritically believing hype from AI companies. OpenAI people sometimes say stuff like "AI electricity use will 20x in the next 10 years" and people will be like "we need to stop this now" not remembering that the same person believes AI will be like a god in 10 years
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they're gonna lose it when they hear about Prime Intellect
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so maybe OpenAI is fucked if improvements stall out, but whoever buys out ChatGPT after that could cut down hard on R&D and invest in efficiency to make a pretty tidy profit by most estimates
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hard to say exactly but all of these labs are deep in the red if you include R&D. they tell investors openly that they only expect a payoff if capabilities spike to the stratosphere and make them infinite money
that being said, you could replicate DeepSeek V3 today for <$20M total probably
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this may have been true a while ago but mostly isn't today. the best report we have on efficiency for LLM inference is the DeepSeek V3 infrastructure report, where they turn a >400% profit selling their frontier-level model at around $3/million words of output
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the highest-utility thing I can do is convince people to have a consistent deontological code of ethics
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"what is the deep fates program" brother you're living it
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my only guess is ridiculous top-down bugbears like "no LiDAR" extending really far into "robotaxi" as a product. entirely possible they're foregoing the detailed live-updating 3D scans that make Waymo and the like possible
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even with a base level of incompetence it's kind of shocking to me that Tesla can't even manage third place in the "driverless taxi" race
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anything could happen over the course of 12-36 months, during which time it slowly becomes apparent that a new technology is important and generalizes well as increasingly ambitious experiments repeatedly come back successful and its exact strengths and weaknesses are worked out
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i would be more sympathetic to this if the number of macro-scale innovations in the LLM space contributing to current capabilities was "several" rather than "like, two".
1. parameter scaling goes up to about 600B-1000B before it stops making sense
2. reinforcement learning works pretty well
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the sample efficiency of modern RL is such that a motivated person could train a classifier on their personal preferences in an AI and have their own for well under $100. if small models get good enough or fast RAM gets cheap enough this might even be practical
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i wish i had finished formally writing out my thoughts on this 4 months ago bc i'd look kinda prescient now - big labs are releasing increasingly task-tuned models as RL generalization proves somewhat domain-specific
i just hope my other prediction, "let a million micro-labs bloom", also comes true
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my take is that Reinforcement Learning Works, in that you can make current-day LLMs really good at basically any task if you can find enough problems and create a robust enough reward signal
but the dream of a generalist model being Smart Enough to do these things emergently is far off
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at least part of this is because stable diffusion fell off. i dont really follow image models that much but I think the good stuff is to be found outside of Stability's lineup
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i think an article titled "why are people still on twitter" should at least try to form a descriptive answer to that question rather than attempt to develop it from first principles
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idk how you spend any time on bluesky and think "the reason there aren't as many people here is because there's no culture war"
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i hope "good". i accidentally turned my friend into a chaser. she had a Thing for a trans woman and i teased her by saying "just imagine urself doing her e shot"
she reacted like "it is immoral for me to to be into that" and then the next week she said "this permanently changed my brain chemistry"
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the Spamton one tells you how to get the right choices (don't give him your money)