It started off slow and as the system got better, it sped up its own development, basically exponentially.

Sometimes it got a bit weird, where I would be improving the protocol the LLM uses to save edits, but it would assume the changes that it was actively sending were already in place.

Sure there is. Intelligence doesn't give us our selfish motivations, natural selection does. We have similar motivations to C elegans, that has all of 302 neurons. Stay alive and have sex.

Honeybees don't though. They are about halfway between humans and C elegans when it comes to cognitive power. But they are not selfish because they don't reproduce directly (I'm talking about the worker bees). So they will sting even though it kills them. All their behavior is consistant with this.

It seems odd to complain about a AI coding tool being coded with AI. That's just eating your own dog food. In my opinion it makes it better, because the tool is very well tested.

Anyway, are you speaking of the harness? The harness on mine isn't AI, so speed just isn't an issue.

I'm also not sure what you mean by "we aren't there yet." Where?

Sorry, not trying to be difficult or dense, I'm just not sure what you are referring to.

> mostly because most of the focus is on exploding the context and parameters.

Large context allows a surprising amount of "learning" to happen at inference time rather than training time. I think that is relatively unexplored. As long as the model itself has passed a certain threshold of smarts, and the context is large enough (Gemini and its million token context being WAY past that point) you are not really limited by the model, you are only limited by how good the stuff you feed into that context is.

That's what happened when, nearly a year ago, I saw a major leap in capabilities that happened entirely on my end.... not in the AI, but in code written by the AI. I found it genuinely frighting to be honest. I think OpenClaw tapped into something similar, which seemed to surprise a lot of people. There were latent capabilities in the AI that were unknown until brought out by a clever harness.

recursi.dev

Seriously, I'm looking for collaborators.

There's upwards of 80,000 lines of code in the editor system, a lot to it to make sure that even newbies don't get stuck.... so that's kind of proof the system works since it doesn't break down when the codebase grows large.

There's a ton of other tricks to it, but mostly keeping the protocol simple for the AI so it can concentrate on coding logic and not stuff like managing BS boilerplate, dependencies, etc. (for instance I make extensive use of things like abstract syntax tree library to help with surgical edits from the LLM)

That said, I would be very open to collaborating with someone who builds such small models, I don't think the system strictly needs it, but it also could have some extra power if it had it.

I always was fascinated (obsessed?) by robots that build robots, or even things like this that can contribute a lot to making the next version of itself: https://buildyourcnc.com/products/cnc-machine-blacktoe-v4-2x... (cnc router that cuts plywood, and is made out of cnc-router cut plywood)

This is my own effort at an AI assisted coding environment optimized for building itself: https://recursi.dev/ (just launching it, hope its ok to mention it, it is free/open source.... here is the HN link that has gotten no love yet: https://news.ycombinator.com/item?id=48401022 )

Personally I think harnesses are as important as the AI itself, and have this crazytheory that even if the models stopped improving today we could still have massive advances in the harnesses alone.

Comments URL: https://news.ycombinator.com/item?id=48401022

Points: 6

# Comments: 3

If AI and robots are able to do all the jobs, being idle isn't the negative it has always been.

All through history, you needed lots of non-idle people to do all the work that needed to be done. This is a new situation we are coming upon.

So much for that plan.

What skills won't be replaced? The only ones I can think of either have a large physical component, or are only doable by a tiny fraction of the current workforce.

As for the ones with a physical component (plumbers being the most cited), the cognitive parts of the job (the "skilled" part of skilled labor) can be replaced while having the person just following directions demonstrated onscreen for them. And of course, the robots aren't far behind, since the main hard part of making a capable robot is the AI part.

You may be right about humans biasing toward easiest to obtain information, but that doesn't say "don't use AI assistance", it says "use care when using AI assistance".

Also, Cliff wasn't saying the information was easier to use, since in his case, it was actually harder to use than just looking it up in a printed encyclopedia or the like. But none of the problems he mentioned were inherent problems with the internet, they were because it was a brand new medium still working out its kinks. AI may well be harder to use for coding right now, at least for many use cases. However, a look at the bigger picture strongly suggests it is the future, just as a look at the bigger picture in 1995 would have suggested that the internet was the future, at least for answering questions like "when was the battle of Trafalgar?"

This is consistent with my horse/car analogy: the car wasn't the problem, the problem was people who assumed cars were going to keep themselves on the road like a horse would naturally do. You can get a huge gain, but you have to be smart about how you use it.

From my perspective, your perspective is like a horse and buggy driver feeling vindicated when a "horseless carriage" driver accidentally drives one into a tree. The cars will get easier to drive and safer in crashes, and the drivers will learn to pay attention in certain ways they previously didn't have to.

Will there still be occasional problems? Sure, but that doesn't mean that tying your career to horses would have been a wise move. Same here.

(Also, this article is about "poisoned ChatGPT-like tools." Which says very little about using the tools that most developers are using)

I'm always reminded of this: "Logged onto the World Wide Web, I hunt for the date of the Battle of Trafalgar. Hundreds of files show up, and it takes 15 minutes to unravel them—one's a biography written by an eighth grader, the second is a computer game that doesn't work and the third is an image of a London monument. None answers my question, and my search is periodically interrupted by messages like, "Too many connections, try again later."" -- Cliff Stoll, 1995

This is different and has a lot of complications that are basically things we've never seen before, but still, just giving the 60 million back doesn't make any sense at all. They would've never achieved what they've achieved without his 60 million.

That isn't the case here. If some well meaning person discovers a way that you can create a pandemic causing superbug, they can't just "fix" the AI to make that impossible. Not if it is open source. Very different thing.