https://github.com/mii-nipah/voxcpm-rs

--- Just to be clear, I'm not saying they don't make mistakes. In fact I constantly scream into the void with the sheer amount of absolute stupidity of those models, however I would never say, using them for what I use, that they can only be used for simple and small use cases.

If you expect the same level of quality as you would write by hand, then you probably is better off... not using those tools. I mean if I was rewriting 50% of the generations I get I would not be using them at all.

So I thought to myself: "can this be done by simply taking the already existing inline hints from most programming languages and just displaying them differently?", and well, the answer is yes!

To use simply install the extension in your vscode, then enable type hints in your favorite LSP, then disable the native vscode inlay hints in the menu, and done. You can also configure it if you want, it's very customizable.

It's open source: https://github.com/mii-nipah/type-lens.git

Comments URL: https://news.ycombinator.com/item?id=44493320

Points: 3

# Comments: 0

So on the edge, if he was not able to understand them at all, and this was not just a problem of grasping the problem, my point was that this would possibly indicate a neurological problem, or developmental, due to the nature of them. It's not a question of "you need to get all of them right", his point was that he was unable to understand them at all, that it confused them to an understanding level.

And it is true, those people did not got an iPhone and died, but this is also you saying this for them. You don't know all the specifics of history or all their motivations, the industrial revolution had a bloody story, but it's origins were also organic, it also had aspects of improvement. The world population grew almost 10x.

I don't think we are in a position to judge those past events to the lens you are posing.

Prove it.

Maybe because (and I'm quoting that article) it is still lacking in what it should have that you managed to accomplish this task in "few days" instead of "a few weeks, maybe months".

Maybe the bottleneck was not your typing speed, but the [specific knowledge] to build that system. Because if you know something well enough, you can build it way faster, like rebuilding something from scratch, you will be faster as you already know the paths. In which case, my question would be: would not be writing this as fast, or maybe at least more secure and reasonable, if you had the complete knowledge of the system first.

Because contrary to LLMs, humans can actually improve and learn when they do things, and they don't whey they don't do things. Not knowing the code to the full extent is worth the time "gained" by using the LLM to write it?

I think it's very hard to estimate those other aspects of the thing.

---

> Have you seen them or shown them to average people? I’m sure the people who write them understand them but if you show these problems to average people in the street they are completely clueless.

I can show them to people on my family, I'll do it today and come back with the answer, it's the best way of testing that out.

Either way, there's something fishy about this presentation, it says: "ARC-AGI-1 WAS EASILY BRUTE-FORCIBLE", but when o3 initially "solved" most of it the co-founder or ARC-PRIZE said: "Despite the significant cost per task, these numbers aren't just the result of applying brute force compute to the benchmark. OpenAI's new o3 model represents a significant leap forward in AI's ability to adapt to novel tasks. This is not merely incremental improvement, but a genuine breakthrough, marking a qualitative shift in AI capabilities compared to the prior limitations of LLMs. o3 is a system capable of adapting to tasks it has never encountered before, arguably approaching human-level performance in the ARC-AGI domain.", he was saying confidently that it would not be a result of brute-forcing the problems. And it was not the first time, "ARC-AGI-1 consists of 800 puzzle-like tasks, designed as grid-based visual reasoning problems. These tasks, trivial for humans but challenging for machines, typically provide only a small number of example input-output pairs (usually around three). This requires the test taker (human or AI) to deduce underlying rules through abstraction, inference, and prior knowledge rather than brute-force or extensive training."

Now they are saying ARC-AGI-2 is not bruteforcible, what is happening there? They didn't provided any reasoning for why one was bruteforcible and the other not, nor how they are so sure about that. They "recognized" that it could be brute-forced before, but in a way less expressive manner, by explicitly stating it would need "unlimited resources and time" to solve. And they are using the non-bruteforceability in this presentation as a point for it.

--- Also, I mentioned mammals because those problems are of an order that mammals and even other animals would need to solve in reality for a diversity of cases. I'm not saying that they would literally be able to take the test and solve it, nor to understand this is a test, but that they would need to solve problems of similar nature in reality. Naturally this point has it's own limits, but it's not easily discarded as you tried to do.

You are doing something wrong. I go line-by-line through my code like 7x faster than I would do it for someone's else code, because I know what I wrote, my own intentions, my flow of coding and all of those details. I can just look at it en passant, while with AI code I need to carefully review every single detail and the connection between them to approve it.

This is EXTREMELY false. When you write the code you [remember] it, it's fresh in your head, you [know] what it is doing and exactly what it's supposed to do. This is why debugging a codebase you didn't wrote is harder than one you wrote, if a bug happens you know exactly the spots it could be happening at and you can easily go and check them.

The normal o3 also managed to break 3 isolated installations of linux I was trying it with, a few days ago. The task was very simple, simply setup ubuntu with btrfs, timeshift and grub-btrfs and it managed to fail every single time (even when searching the web), so it was not impressive either.