Earlier quoted context omitted.
In my experience LLMs can't get basic western music theory right, there's no way I would use an LLM for something harder than that.
> In my experience LLMs can't get basic western music theory right, there's no way I would use an LLM for something harder than that. This take is completely oblivious, and frankly sounds like a desperate jab. There are a myriad of activities whose core requirement is a) derive info from a complex context which happens to be supported by a deep and plentiful corpus, b) employ glorified template and rule engines. LLMs…
Recent AI model progress feels mostly like bullshit
471–478 of 478 posts
Re: Recent AI model progress feels mostly like bullshit
#472* Model creation has exploded with people training their own models and fine tunes, etc but these are all derivatives of parent models from large companies
So I'm not really sure what they mean when they refer to "recent model progress"...I don't think anybody is putting out a llama finetune saying "this is revolutionary!111" nor have I seen OAI, et al make any such claims either.
Is the sensation just because forward momentum is stalling while we wait for the next big leap?
Re: Recent AI model progress feels mostly like bullshit
#473The biggest story in AI was released a few weeks ago but was given little attention: on the recent USAMO, SOTA models scored on average 5% (IIRC, it was some abysmal number). This is despite them supposedly having gotten 50%, 60% etc performance on IMO questions. This massively suggests AI models simply remember the past results, instead of actually solving these questions. I'm incredibly surprised no one mentions th…
Re: Recent AI model progress feels mostly like bullshit
#474The biggest story in AI was released a few weeks ago but was given little attention: on the recent USAMO, SOTA models scored on average 5% (IIRC, it was some abysmal number). This is despite them supposedly having gotten 50%, 60% etc performance on IMO questions. This massively suggests AI models simply remember the past results, instead of actually solving these questions. I'm incredibly surprised no one mentions th…
Re: Recent AI model progress feels mostly like bullshit
#475Earlier quoted context omitted.
It's obvious that humans imitate concepts and don't come up with things de-novo from a blank slate of pure intelligence. So your claim hinges on LLMs parrotting the words they are trained on. But they don't do that, their training makes them abstract over concepts and remix them in new ways to output sentences they weren't trained on, e.g.: Prompt: "Can you give me a URL with some novel components, please?" DuckDuckG…
> fireworks, cannons, jellyfish squeezing water out to accelerate, no sudies of orbits from moons and planets, no chemistry experiments, no inspiration from thousands of years of flamethrowers Fireworks, cannons, chemistry experiments and flamethrowers are all human inventions And yes, exactly! We studied orbits of moons and planets. We studied animals like Jellyfish. We choose to observe the world , we extracted dat…
Re: Recent AI model progress feels mostly like bullshit
#476Earlier quoted context omitted.
This is less an LLM thing than an information retrieval question. If you choose a model and tell it to “Search,” you find citation based analysis that discusses that he indeed had problems with alcohol. I do find it interesting it quibbles whether he was an alcoholic or not - it seems pretty clear from the rest that he was - but regardless. This is indicative of something crucial when placing LLMs into a toolkit. The…
I realise your answer wasn't assertive, but if I heard this from someone actively defending AI it would be a copout. If the selling point is that you can ask these AIs anything then one can't retroactively go "oh but not that" when a particular query doesn't pan out.
The abilities of LLM alone to do astounding natural language processing beyond the ability of anything prior by unthinkable Turing test passing miles. The fact it can reason abductively, which computing techniques to date have been unable to is amazing. The fact you can mix it with multimodal regimes - images, motion, virtually anything that can be semantically linked via language, is breathtaking. The fact it can be augmented with prior computing techniques - IR, optimization, deductive solvers, and literally everything we’ve achieved to date should give anyone knowledgeable of such things shivers for what the future holds.
But I would never hold that generative AI techniques are replacements for known optimal techniques. But the ensemble is probably the solution to nearly every challenge we face. When we hit the limits of LLMs today, I think, well, at least we already have grand master beating chess solvers and it’s irrelevant the LLM can’t directly. The LLM and other generative AI techniques in my mind are like gasses that fill through learned approximation the things we’ve not been able to solve directly, including the assembly of those solutions ad hoc. This is why since the first time BERT came along I knew agent based techniques were the future.
Right now we live at time like early hypertext with respect to AI. Toolchains suck, LLMs are basically geocities pages with “under construction” signs. We will go through an explosive exploration, some stunning insights that’ll change the basic nature of our shared reality (some wonderful some insidious), then if we aren’t careful - and we rarely are - enshitification at scale unseen before.
Re: Recent AI model progress feels mostly like bullshit
#477Earlier quoted context omitted.
This is less an LLM thing than an information retrieval question. If you choose a model and tell it to “Search,” you find citation based analysis that discusses that he indeed had problems with alcohol. I do find it interesting it quibbles whether he was an alcoholic or not - it seems pretty clear from the rest that he was - but regardless. This is indicative of something crucial when placing LLMs into a toolkit. The…
lotta words here to say AI can't do basic search right