It’s probably a coincidence, but there have been a whole bunch of minor regression bugs in recent point releases of rsync, and also there are a whole bunch of commits from “tridge and claude”.
rook
joined 2 years ago
because there’s no economic incentive to hire them to do that kind of work.
isn’t that the old “basic science is boring and unsexy” issue though? There are economic incentives, but not in a short term-big-bux sort of way, so capitalism can’t be trusted with it.
To conjure up a recent example, something like “The number of curves of genus two with elliptic differentials”, published back in 1997, probably had limited commercial value at the time, but 20 years later completely sunk a promising post-quantum cryptography algorithm (“An efficient key recovery attack on SIDH”) which might have had some non-trivial commercial implications if SIKE had got through the key exchange algorithm competition.
Anyway, the Erdős problems are good candidates for llm work because they have been specified in a careful and formal way, which requires a reasonably competent mathematician to do. That then opens up mathematics to the same deskilling problem that other sectors afflicted with llms have, and because capitalism is shortsighted and stupid we don’t know what the future economic impact of that will be, right?
In the same way that lazy studios need to produce a film for each element of the powerset of character IPs they own, I guess we were overdue a Rationalist x Pickup Artist episode. I’m slightly surprised the whole “model women as quasi-sentient deterministic sex machinery” idea wasn’t already very popular there, but maybe I’ve just missed that part of their culture.
you know how sometimes people that weren't exposed to religion as children sometimes convert and get really weird about it as adults (eg: the extremely online california tradcaths) and because they were never socialized in a religion they speedrun committing every medieval heresy? rationalism is that but for philosophy.
https://feed.hella.cheap/@bob/statuses/01KRM0NVXCFT80AVFBRSB1G6G4
New lucidity post: https://ludic.mataroa.blog/blog/contra-ptaceks-terrible-article-on-ai/
The author is entertaining, and if you’ve not read them before their past stuff is worth a look.
It isn’t clear to me at this point that such research will ever be funded in english-speaking places without a significant set of regime changes… no politician or administrator can resist outsourcing their own thinking to llm vendors in exchange for funding. I expect the US educational system will eventually provide a terrible warning to everyone (except the UK, whose government looks at the US and says “oh my god, that’s horrifying. How can we be more like that?”).
I’m probably just feeling unreasonably pessimistic right now, though.
Some people casting their eyes over this monster of a paper have less than positive thoughts about it. I’m not going to try and summarise the summaries here, but the threads aren’t long (and are vastly shorter than the paper) so reading them wouldn’t take long.
Dr. Cat Hicks on mastodon: https://mastodon.social/@grimalkina/114690973548997443
Ashley Juavinett on bluesky: https://bsky.app/profile/analog-ashley.bsky.social/post/3lru5sua3fk25
It is related, inasmuch as it’s all generated from the same prompt and the “answer” will be statistically likely to follow from the “reasoning” text. But it is only likely to follow, which is why you can sometimes see a lot of unrelated or incorrect guff in “reasoning” steps that’s misinterpreted as deliberate lying by ai doomers.
I will confess that I don’t know what shapes the multiple “let me just check” or correction steps you sometimes see. It might just be a response stream that is shaped like self-checking. It is also possible that the response stream is fed through a separate llm session when then pushes its own responses into the context window before the response is finished and sent back to the questioner, but that would boil down to “neural networks pattern matching on each other’s outputs and generating plausible response token streams” rather than any sort of meaningful introspection.
I would expect the actual systems used by the likes of openai to be far more full of hacks and bodges and work-arounds and let’s-pretend prompts that either you or I could imagine.
It’s just more llm output, in the style of “imagine you can reason about the question you’ve just been asked. Explain how you might have come about your answer.” It has no resemblance to how a neural network functions, nor to the output filters the service providers use.
It’s how the ai doomers get themselves into a flap over “deceptive” models… “omg it lied about its train of thought!” because if course it didn’t lie, it just edited a stream of tokens that were statistically similar to something classified as reasoning during training.
I might be the only person here who thinks that the upcoming quantum bubble has the potential to deliver useful things (but boring useful things, and so harder to build hype on) but stuff like this particularly irritates me:
Quantum fucking ai? Motherfucker,
- You don’t have ai, you have a chatbot
- You don’t have a quantum computer, you have a tech demo for a single chip
- Even if you had both of those things, you wouldn’t have “quantum ai”
- if you have a very specialist and probably wallet-vaporisingly expensive quantum computer, why the hell would anyone want to glue an idiot chatbot to it, instead of putting it in the hands of competent experts who could actually do useful stuff with it?
Best case scenario here is that this is how one department of Google get money out of the other bits of Google, because the internal bean counters cannot control their fiscal sphincters when someone says “ai” to them.
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This seems like it is probably a good thing.
https://leidendeclaration.ai/
It does feel a bit “art of war” though… someone patiently explaining to a bunch of people who really should know better that they shouldn’t do obviously bad and wrong things.