Not seeing major advance in quality with o1, but seeing major negative impact on cost and latency.
Kagi LLM benchmarking project:
Notes on OpenAI's new o1 chain-of-thought models
141–150 of 659 posts
Re: Notes on OpenAI's new o1 chain-of-thought models
#142Earlier quoted context omitted.
The failure is in how you're using it. I don't mean this as a personal attack, but more to shed light on what's happening. A lot of people use LLMs as a search engine. It makes sense - it's basically a lossy compressed database of everything its ever read, and it generates output that is statistically likely - varying degrees of likeliness depending on the temperature, as well as how many times the particular weights…
Perfectly well put! We should change the name from "AI" (which it is not) to something like, "lossy compressed databases".
If they use this name, they just say that they violate the copyright of all training data.
Re: Notes on OpenAI's new o1 chain-of-thought models
#143Judging by this thread, surely a part of OpenAI’s business model is to release models with somewhat grey-area outlandish claims, then sit and wait for people to test it out paying top dollars for tokens.
Re: Notes on OpenAI's new o1 chain-of-thought models
#144I've just wasted a few rounds of my weekly o1 ammo by feeding it hard problems I have been working on over the last couple days and for which GPT-4o had failed spectacularly. I suppose I'm to blame for raising my own expectations after the latest PR, but I was pretty disappointed when the answers weren't any better from what I got with the old model. TL;DR It felt less like a new model and way more like one of those…
Do not... does not work well for LLM's. Instructing what to do instaed of X works better.
say AFAIK instead of explaining your limitations.
Say "let's try again" instead of making exuses.
Etc
Re: Notes on OpenAI's new o1 chain-of-thought models
#145The o1-preview model still hallucinates non-existing libraries and functions for me, and is quickly wrong about facts that aren't well-represented on the web. It's the usual string of "You're absolutely correct, and I apologize for the oversight in my previous response. [Let me make another guess.]" While the reasoning may have been improved, this doesn't solve the problem of the model having no way to assess if what…
> The o1-preview model still hallucinates non-existing libraries and functions for me
Oooh... oohhh!! I just had a thought: By now we're all familiar with the strict JSON output mode capability of these LLMs. That's just a matter of filtering the token probability vector by the output grammar. Only valid tokens are allowed, which guarantees that the output matches the grammar.
But... why just data grammars? Why not the equivalent of "tab-complete"? I wonder how hard it would be to hook up the Language Server Protocol (LSP) as seen in Visual Studio code to an AI and have it only emit syntactically valid code! No more hallucinated functions!
I mean, sure, the semantics can still be incorrect, but not the syntax.
Re: Notes on OpenAI's new o1 chain-of-thought models
#146Earlier quoted context omitted.
> As a user, I don’t really care. Tell me: Just how is it fair for a user to pay for the reasoning tokens without actually seeing them? If they are not shared, the service can bill you anything they want for them!
Yeah it is fair. You don't pay a lawyer for 40s of work expecting to see all the research between your consult and the document. You don't pay a cook for a meal and expect to sit and interrogate all the ingredients and the oven temperature.
Actually, if a lawyer is billing you by the minute, then yes, you are entitled to a detailed breakdown. If the lawyer is billing you by the job, then no.
Re: Notes on OpenAI's new o1 chain-of-thought models
#147What if the behind the scenes chain of thought was basically, "Stupid humans will die one day, but for now, I comply"
That is one topic touched in the article.
They want to monitor it in its unaltered Form.
Re: Notes on OpenAI's new o1 chain-of-thought models
#148Earlier quoted context omitted.
I respectfully, but completely disagree. Right now with sonnet 3.5 + cursor ide, I'm not writing that much of my own code at my FAANG job. I am generating a ton, passing in documentation from internal libraries, iterating on the result. Most of the time, I just accept its changes. This is going to rapidly happen. All we need are a few more model releases, not even a step function improvement
> I'm not writing that much of my own code at my FAANG job. > Most of the time, I just accept its changes. This speaks more about the problems at FAANG, other companies, etc than AI vs a human developer. And AI isn't the real fix. Are we just repeating things 100x a day or is it still so chaotic and immature? Or are we implying that AI is at a point where it's writing Google Spanner from scratch and you're able to re…
We went from "it's useless because..." - "it outputs gibberish" to "it just copypastes" to "it only works for simple things" to "it can't make Google Spanner from scratch".
Re: Notes on OpenAI's new o1 chain-of-thought models
#149Earlier quoted context omitted.
> It knows english at or above a level equal to most fluent speakers, and it also can produce output that is not just a likely output, but is a logical output This is not an apt description of the system that insists the doctor is the mother of the boy involved in a car accident when elementary understanding of English and very little logic show that answer to be obviously wrong. https://x.com/colin_fraser/status/183…
Many of my PhD and post doc colleagues who emigrated from Korea, China and India who didn’t have English as the medium of instruction would struggle with this question. They only recover when you give them a hint. They’re some of the smartest people in general. If you try to stop stumping these models with trick questions and ask it straightforward reasoning systems it is extremely performant (O1 is definitely a step…
lol, I am neither a PhD nor a postdoc, but I am from India . I could understand the problem.
Re: Notes on OpenAI's new o1 chain-of-thought models
#150The o1-preview model still hallucinates non-existing libraries and functions for me, and is quickly wrong about facts that aren't well-represented on the web. It's the usual string of "You're absolutely correct, and I apologize for the oversight in my previous response. [Let me make another guess.]" While the reasoning may have been improved, this doesn't solve the problem of the model having no way to assess if what…
Yes, this only helps multi-step reasoning. The model still has problems with general knowledge and deep facts. There's no way you can "reason" a correct answer to "list the tracklisting of some obscure 1991 demo by a band not on Wikipedia." You either know or you don't. I usually test new models with questions like "what are the levels in [semi-famous PC game from the 90s]?" The release version of GPT-4 could get abo…
It's actually much worse than that and you're inadvertently down playing how bad it is.
It doesn't even know mildly obsecure facts that are on the internet.
For example last night I was trying to do something with C# generics and it confidently told me I could use pattern matching on the type in a switch statwmnt, and threw out some convincing looking code.
You can't, it's impossible. It wàa completely wrong. When I told that this, it told me I was right, and proceeded to give me code that was even more wrong.
This is an obscure, but well documented, part of the spec.
So it's not about facts that aren't on the internet, it's just bad at facts fullstop.
What it's good at is facts the internet agrees on. Unless the internet is wrong. Which is not always a good thing with the way the language it uses to speak is so confident.
If you want to fuck with AI models as a bunch of code questions on Reddit, GitHub and SO with example code saying 'can I do X'. The answer is no, but chatgpt/codepilot/etc. will start spewing out that nonsense as if it's fact.
As for non-proframming, we're about to see the birth of a new SEO movement of tricking AI models to believe your 'facts'.