3 ms·

>I think a lot of people would be very content if they never got smarter, and just kept getting even cheaper/faster. There's a lot of truth to this. I think we

>I think a lot of people would be very content if they never got smarter, and just kept getting even cheaper/faster. There's a lot of truth to this. I think we're starting to approach the point where increased intelligence has declining marginal returns, such that it might not even be worthwhile to improve models unless it can be done cheaply.

ColdStream 1mo ago
I have argued for a while that this was an S-curve it was just a case of figuring out which part of it we were in. I am more confident nowadays that we are heading towards the upper plateau but there might still be some head room on that.
insanitybit 1mo ago
I'm really not convinced that these models are even that much more intelligent, as opposed to simply being more token aggressive. I do not find Fable that much smarter than Opus 4.6, and no Opus model seems to have improved things much at all. Benchmarks seem gamed at this point, real world experience just doesn't match up.
someothherguyy 1mo ago
i wish i was experiencing these things that everyone else is. my experience is mostly frustration and rewrites of anything that requires more than what would take me an hour to do myself, unless it is pure translation / boiler plate work. the leaps are there at getting to more "shaped" code (code that is correct for linters, static checking, etc), but i don't see the models exhibiting much intelligence. i really can't think of a time using LLMs for building anything where they did something that would make me go, "wow, that is really impressive, i wonder how it came up with that." just brute force search and pattern matching still. even the interesting results in academic work seem to be more of a function of effort (proofs by exhaustion, fitting puzzle pieces in a search space, etc) than anything else. not to say people aren't using large language models to do impressive things, but the agents themselves do not seem very intelligent to me. it feels like some engineering teams are aware of this fact and are driving agents using strict rule checks (like hooks on steroids), so they can drive some shape of output that aligns with what they require.

ColdStream 1mo ago

I have argued for a while that this was an S-curve it was just a case of figuring out which part of it we were in. I am more confident nowadays that we are heading towards the upper plateau but there might still be some head room on that.

insanitybit 1mo ago

I'm really not convinced that these models are even that much more intelligent, as opposed to simply being more token aggressive. I do not find Fable that much smarter than Opus 4.6, and no Opus model seems to have improved things much at all. Benchmarks seem gamed at this point, real world experience just doesn't match up.

someothherguyy 1mo ago

i wish i was experiencing these things that everyone else is. my experience is mostly frustration and rewrites of anything that requires more than what would take me an hour to do myself, unless it is pure translation / boiler plate work. the leaps are there at getting to more "shaped" code (code that is correct for linters, static checking, etc), but i don't see the models exhibiting much intelligence. i really can't think of a time using LLMs for building anything where they did something that would make me go, "wow, that is really impressive, i wonder how it came up with that." just brute force search and pattern matching still. even the interesting results in academic work seem to be more of a function of effort (proofs by exhaustion, fitting puzzle pieces in a search space, etc) than anything else. not to say people aren't using large language models to do impressive things, but the agents themselves do not seem very intelligent to me. it feels like some engineering teams are aware of this fact and are driving agents using strict rule checks (like hooks on steroids), so they can drive some shape of output that aligns with what they require.