Does ruby just die now?
Part of the background to this issue is the development of rv which apparently offers a future where rubygems is much less important, and some folk seem to be taking that as a threat.
Whether or not the new tooling delivers, the rubygems debacle has probably helped the new project considerably.
Haven’t read the source paper yet (apparently it came out two weeks ago, maybe it already got sneered?) but this might be fun: OpenAI admits AI hallucinations are mathematically inevitable, not just engineering flaws.
Full of little gems like
Beyond proving hallucinations were inevitable, the OpenAI research revealed that industry evaluation methods actively encouraged the problem. Analysis of popular benchmarks, including GPQA, MMLU-Pro, and SWE-bench, found nine out of 10 major evaluations used binary grading that penalized “I don’t know” responses while rewarding incorrect but confident answers.
I had assumed that the problem was solely technical, that the fundamental design of LLMs meant that they’d always generate bullshit, but it hadn’t occurred to me that the developers actively selected for bullshit generation.
It seems kinda obvious in retrospect… slick bullshit extrusion is very much what is selling “AI” to upper management.
Woke up to some hashtag spam this morning
AI’s Biggest Security Threat May Be Quantum Decryption
which appears to be over of those evolutionary “transitional forms” between grifts.
The sad thing is the underlying point is almost sound (hoarding data puts you at risk of data breaches, and leaking sensitive data might be Very Bad Indeed) but it is wrapped up in so much overhyped nonsense it is barely visible. Naturally, the best and most obvious fix — don’t hoard all that shit in the first place — wasn’t suggested.
(it also appears to be a month-old story, but I guess there’s no reason for mastodon hashtag spammers to be current 🫤)
One to watch from a safe distance: dafdef, an “ai browser” aimed at founders and “UCG creators”, named using the traditional amazon-keysmash naming technique and and following the ai-companies-must-have-a-logo-suggestive-of-an-anus style guide.
Dafdef learns your browsing patterns and suggests what you’d do next After watching you fill out similar forms a few times, Dafdef starts autocompleting them. Apply with your startup to YC, HF0 and A16z without wasting your time.
So… spicy autocomplete.
But that’s not all! Tired of your chatbot being unable to control everything on your iphone, due to irksome security features implemented by those control freaks at apple? There’s a way around that!
Introducing the “ai key”!
A tiny USB-C key that turns your phone into a trusted AI assistant. It sees your screen, acts on your behalf, and remembers — all while staying under your control.
I’m sure you can absolutely trust an ai browser connected to a tool that has nearly full control over your phone to not do anything bad, because prompt injection isn’t a thing, right?
(I say nearly full, because I think Apple Pay requires physical interaction with a phone button or face id, but if dafdef can automate the boring and repetitive parts of using your banking app then having full control of the phone might not matter)
h/t to ian coldwater
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.
deleted by creator
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,
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.
And back on the subject of builder.ai, there’s a suggestion that it might not have been A Guy Instead, and the whole 700 human engineers thing was a misunderstanding.
https://blog.pragmaticengineer.com/builder-ai-did-not-fake-ai/
I’m not wholly sure I buy the argument, which is roughly
I guess the question then is: if they did have a good genai tool for software dev… where is it? Why wasn’t Microsoft interested in it?
Turns out some Silicon Valley folk are unhappy that a whole load of waymos got torched, fantasised that the cars could just gun down the protesters, and use genai video to bring their fantasies to some vague approximation of “life”
https://xcancel.com/venturetwins/status/1931929828732907882
The author, Justine Moore is an investment partner at a16z. May her future ventures be incendiary and uninsurable.
(via garbageday.email)
I was reading a post by someone trying to make shell scripts with an llm, and at one point the system suggested making a directory called ~ (which is a shorthand for your home directory in a bunch of unix-alikes). When the user pointed out this was bad, the llm recommended remediation using rm -r ~ which would of course delete all your stuff.
So, yeah, don’t let the approximately-correct machine do things by itself, when a single character substitution can destroy all your stuff.
And JFC, being surprised that something called “YOLO” might be bad? What were people expecting? --all-the-red-flags
LLMs aren’t profitable even if they never had to pay a penny on license fees. The providers are losing money on every query, and can only be sustained by a firehose of VC money. They’re all hoping for a miracle.
(this probably deserves its own post because it seems destined to be a shitshow full of the worst people, but I know nothing about the project or the people currently involved)
Did you know there’s a new fork of xorg, called x11libre? I didn’t! I guess not everyone is happy with wayland, so this seems like a reasonable
It’s explicitly free of any “DEI” or similar discriminatory policies… [snip]
Together we’ll make X great again!
Oh dear. Project members are of course being entirely normal about the whole thing.
Metux, one of the founding contributors, is Enrico Weigelt, who has reasonable opinions like everyone except the nazis were the real nazis in WW2, and also had an anti vax (and possibly eugenicist) rant on the linux kernel mailing list, as you do.
In sure it’ll be fine though. He’s a great coder.
(links were unashamedly pillaged from this mastodon thread: https://nondeterministic.computer/@mjg59/114664107545048173)
Relatedly, the gathering of (useful, actually works in real life, can be used to make products that turn a profit or that people actually want, and sometimes even all of the above at the same time) computer vision and machine learning and LLMs under the umbrella of “AI” is something I find particularly galling.
The eventual collapse of the AI bubble and the subsequent second AI winter is going to take a lot of useful technology with it that had the misfortune to be standing a bit too close to LLMs.
It isn’t clear that anyone in trump’s government has ever paused to consider than any of their plans might have downsides.
Today’s related news: the tailwind css guy is a big fan of dhh and the rubygems takeover.
https://bsky.app/profile/jaredwhite.indieweb.social.ap.brid.gy/post/3lzofv4wi4yz2
I miss the days when being publicly fashy was considered poor pr, but on the other hand it does make it a lot easier to avoid their companies and products.
Tailwind is pointless, incidentally.