@MoonL88537 >still working on getting it into words people will understand
a tangent, but i've been experimenting with visualisations to accompany words when making abstract arguments. this sort of thing:
https://t.co/zPhDk0oipA
@MoonL88537 I don't think one has to be a reductionist to believe that there is a number, albeit a large and difficult one to calculate. Even figuring out the bounds on that number seems interesting, even if overly enthusiastic.
@lefthanddraft They can be bad. Also get it to cut the fluff with:
"Comments should explain non-obvious behaviour. If the comment doesn't help an LLM in a fresh context window understand the code, cut it."
GLM 5.2 excels at "puzzlely" programming challenges, but struggles with real ones. It lacks common sense & fails to follow basic instructions. To use it successfully requires too much finnicky skilling & tooling. It costs me more than Opus 4.8 to code with, if you factor in time.
That's based on a bunch of ad-hoc A/B tests comparing GLM 5.2 to Opus 4.8.
It's also terribly sycophantic. Added to benchmark here:
https://t.co/V18LzkG2Qb
@JohnBryBry@dioscuri Anyone who studies philosophy of mind quickly realises something *MUST* be wrong with our intuitions. The speculation is downstream of arguments that are harder to dismiss than the intuitions in question.
@inductionheads * It's not binary, it's a 99.x% challenge
* Avoiding false positives makes it much harder
* Humans aren't perfect at it either
* LLMs can recognize the frame and comply anyway
@kanair An animated explainer for the interactivity-impasse of non-computational theories of consciousness:
https://t.co/zPhDk0oipA
I wrote this with Fable before they were locked up.