31–40 of 204 posts
I've been getting flagged by high-on-their-own-supply AI boosters for identifying that LLM benchmarks have been obvious bullshit for at least the last year and a half. What changed to make "the inevitable AI bubble" the dominant narrative in last week or so?
> "For example, if a benchmark reuses questions from a calculator-free exam such as AIME," the study says, "numbers in each problem will have been chosen to facilitate basic arithmetic. Testing only on these problems would not predict performance on larger numbers, where LLMs struggle." When models figure out how to exploit an effect that every clever college student does, that should count as a win. That’s a much mo…
> "For example, if a benchmark reuses questions from a calculator-free exam such as AIME," the study says, "numbers in each problem will have been chosen to facilitate basic arithmetic. Testing only on these problems would not predict performance on larger numbers, where LLMs struggle." When models figure out how to exploit an effect that every clever college student does, that should count as a win. That’s a much mo…
I don’t think the fact that LLMs can handle small numbers more reliably has anything to do with their reasoning ability. To the contrary, reasoning ability should enable them to handle numbers of arbitrary size, just as it enables humans to do so, given some pencil and paper. However: > Testing only on these problems would not predict performance on larger numbers, where LLMs struggle. Since performance on large numb…
Earlier quoted context omitted.
I don’t think the fact that LLMs can handle small numbers more reliably has anything to do with their reasoning ability. To the contrary, reasoning ability should enable them to handle numbers of arbitrary size, just as it enables humans to do so, given some pencil and paper. However: > Testing only on these problems would not predict performance on larger numbers, where LLMs struggle. Since performance on large numb…
Pencil and paper is just testing with tools enabled.
Personally, I’d say that such tool use is more akin to a human using a calculator.
Earlier quoted context omitted.
I don’t think the fact that LLMs can handle small numbers more reliably has anything to do with their reasoning ability. To the contrary, reasoning ability should enable them to handle numbers of arbitrary size, just as it enables humans to do so, given some pencil and paper. However: > Testing only on these problems would not predict performance on larger numbers, where LLMs struggle. Since performance on large numb…
Pencil and paper is just testing with tools enabled.
Earlier quoted context omitted.
Pencil and paper is just testing with tools enabled.
You seem to be addressing an argument that wasn’t made. Personally, I’d say that such tool use is more akin to a human using a calculator.
I work on LLM benchmarks and human evals for a living in a research lab (as opposed to product). I can say: it’s pretty much the Wild West and a total disaster. No one really has a good solution, and researchers are also in a huge rush and don’t want to end up making their whole job benchmarking. Even if you could, and even if you have the right background you can do benchmarks full time and they still would be a mes…
For what it's worth, I work on platforms infra at a hyperscaler and benchmarks are a complete fucking joke in my field too lol. Ultimately we are measuring extremely measurable things that have an objective ground truth. And yet: - we completely fail at statistics (the MAJORITY of analysis is literally just "here's the delta in the mean of these two samples". If I ever do see people gesturing at actual proper analysi…
> "For example, if a benchmark reuses questions from a calculator-free exam such as AIME," the study says, "numbers in each problem will have been chosen to facilitate basic arithmetic. Testing only on these problems would not predict performance on larger numbers, where LLMs struggle." When models figure out how to exploit an effect that every clever college student does, that should count as a win. That’s a much mo…
I don’t think the fact that LLMs can handle small numbers more reliably has anything to do with their reasoning ability. To the contrary, reasoning ability should enable them to handle numbers of arbitrary size, just as it enables humans to do so, given some pencil and paper. However: > Testing only on these problems would not predict performance on larger numbers, where LLMs struggle. Since performance on large numb…
Or given a calculator. Which it's running on. Which it in some sense is. There's something deeply ironic about the fact that we have an "AI" running on the most technologically advanced calculator in the history of mankind and...it can't do basic math.
Earlier quoted context omitted.
You seem to be addressing an argument that wasn’t made. Personally, I’d say that such tool use is more akin to a human using a calculator.
I'm not addressing an argument, just stating that's already a form of LLM testing done today for people wanting to look at the difference in results the same as the human analogy.