hellohello2

My 2 cents: AI has improved writing considerably for non-native english speakers (in particular China). Writing feels more standardized/boring but easier to read overall. I hit fewer papers that are a pain to read. The most problematic aspect I see are semi-bogus claims i.e. sentences that aren't false, but don't quite feel right either. YMMV.

Interesting. Framing it as 1x to infinity-x matches my experience too. I've have good success with it reproducing papers with existing code, but not such much with one-shotting new code. Do you have any particular setup for this i.e. special validation prompts or multi-agent stuff or do you just ask something like reproduce paper X until it gets results Y?

Surprisingly good answer from Claude here... Boringly so.

Apologies I misremembered and confused Pro with Plus.

Pro is 10$ a month. You get what you pay for lol.

Well, that statement wasn't meant to be taken literally. Maybe not the best wording, given the context...

"completely meaningless" "the only purpose"

There's some kernel of truth to what you are saying, but hyperboles like this just aren't accurate. All statistics lie but its better than being blind... What your post really says is that benchmarks only show an average over multiple tasks. Yes, obviously, the point of a statistic is to summarize.

I'm confused as well, could someone who knows how TUIs work explain what's the point of React-style diffing in this context? I thought you need to clean and full redraw if anything changs anyways?

Its completely pointless yet I still want it. IDK, its the status lights that look fun.

This feels mistaken; we develop abstract objects i.e. graphs based on real-world utility or whatever. As we try to improve our understanding of graphs, we value proofs that help us do so, or help other fields of mathematics. We assign 0 value to random proofs about stuff no one cares about... This conjecture had value, simply because some people found it interesting. It is not really different from music, in a sense.

I would assume/hope they had someone verify it before publishing

You seem to be suggesting that it is just as hard to understand an existing proof to a problem, than to solve it yourself? I don't follow your argument at all, what are you trying to say?

You had sudo on your PC. You just didn't know ;)

Just to share my perspective, I have not had this much fun programming as when I first learned to code. It's really something you have to try for yourself to actually understand. Its like a new form of programming, where code is "soft" instead of "hard"; on the whole feels similar, but also completely new.

The opinons on this site make me realize most people here are into programming for the money, rather than for the fun of building things. Which is completely fine, but it leads to most commenters being depressed rather than enthralled, which feels honestly confusing at times. Obviously socially things are looking pretty bleak but if you find coding fulfilling on its own, lets just say you can look forward to fulfillment lol

I wasn't clear enough, I was replying to "you'll be the one selected, out of millions laid off," in context I meant "mass layoff" as in "95% of everyone is out of a job permanently".

Current SOTA is far past "agressive autocomplete" at this point, more like ask for a PR for a small feature and its done... I guess for me the fun is you can build a lot yourself, without relying on others. I hear you for the social aspect though & thanks for sharing your pov.

Perhaps its the apprehension/anxiety that makes it feel bad then? I like coding (building things) and couldn't care less about businesses, and am having a great time. In the current state of AI, mass layoffs probably won't happen. But I guess its a bit scary that we don't know how much more it will improve...

I'm curious, have you tried working seriously with claude code or gpt codex and which part of it did you not enjoy? What makes you wish to write code like 2022?

"Have you personally used any of the latest batch of even smaller local models?"

No I have not, which is why I asked (it wasn't a rhetorical question). Do you have pointers on what the recent improvements are?

"It is almost guaranteed that a 60-90B model can outperform current SOTA in coding tasks within 2-3 years"

What insight do you have to make this claim?

No, chatbots are LLMs trained for question-answering through RLHF (its not just a prompt). But yes, if you just zero-shot prompt a bare LLM you can still "talk to it" & you are correct on everything else as far as I know.

They are chatbots trained for tool use, its not just a prompt.

Sorry but I don't really see how this contradicts what I said in context i.e. both our statements are compatible in the context of what I was replying to

I agree that the amount people pay for these services is very unlikely to decrease (i.e. Blinn's Law but for tokens). Still, the current level of "intelligence" will eventually become available for a very low price almost surely. Really I simply don't see how you can disagree with the parent's comment "There is no world in which AI is not used extensively in all employment going forward." Honestly I'd like to understand the mindset, is it mainly that you dislike working with these tools/hope they don't get imposed on you or did you actually find them harmful in your work in some way and think they are overvalued?

Computation halves in price every ~2 years so maybe in the short term but not in the long term

There can be some issues with shadowing yeah, especially if you render with splatting/rasterization, but its fine if you raytrace I think.

There are some works on doing this directly e.g. https://arxiv.org/abs/2601.23065 but getting accurate materials is a challenge for anything more than diffuse.

AI-based relighting will no doubt start working soon.

Thanks for your explanation, I find it much more intuitive than the paper's.

In your opinion, does a Calculus solver model certain aspects of the world?

The literal definition of a model is "an informative representation of an object, person, or system". I think you mean something else though, what are you trying to express exactly?

"Text generated by an LM is not grounded in communicative intent, any model of the world, or any model of the reader’s state of mind."

Modelling text describing the world is not modelling (some aspect) of the world?

Modelling the probability that a reader likes or dislike a piece of text is not modelling (some aspect) of a reader's state of mind?