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AI is different

antirez.com

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Re: AI is different

#801
post #72

Earlier quoted context omitted.

> in that every software engineer now depends heavily on copilots That is maybe a bubble around the internet. Ime most programmers in my environment rarely use and certainly aren't dependent on it. They do also not only do code monkey-esque web programming so maybe this is sampling bias though it should be enough to refute this point.

Im on the core sql execution team at a database company and everyone on the team is using AI coding assistants. Certainly not doing any monkey-esque web programming.

> everyone on the team is using AI coding assistants.

Then the tool worked for you(r team). That's great to hear and maybe gives some hope for my projects.

It has just mostly been more of a time sink than an improvement ime though it appears to strongly vary by field/application.

> Certainly not doing any monkey-esque web programming

The point here was not to demean the user (or their usage) but rather to highlight how developers are not being dependent on LLMs as a tool. Your team presumably did the same type of work before without LLMs and won't become unable to do so if there were to become unavailable.

That likely was not properly expressed in the original comment by me, sorry.

Re: AI is different

#802
post #611

Earlier quoted context omitted.

Present the results of your exercises (in person) in front of someone. Or really anything in person. A big downer on the online/remote Initiatives for learning but actually an advantage for older Unis that already have existing physical facilities for students. This does however also have some problems similar to code interviews .

Sure but that's a solution to prevent students from using LLMs, not an example of something a professor can ask students that "LLMs can't do"...

The main challenge is that most (all?) types of submissions can be created with LLMs and multi-model solutions.

Written tasks are obvious, writing a paper, essay or answering questions is part of most LLMs advertised use-cases. The only other thing was recorded videos, effectively recorded presentations, thanks to video/audio/image generation that probably can be forged too.

So the simple solution to choose something that an "LLM can't do" is to choose something were an LLM can't be applied. So we move away from a digital solution to meatspace.

Assuming that the goal is to test your knowledge/understanding of a topic, it's the same with any other assistive technology. For example, if an examiner doesn't want you[1] to use a calculator to solve a certain equation, they could try to create an artificially hard problem or just exclude the calculator from the allowed tools. The first is vulnerable to more advanced technology (more compute etc.) the latter just takes the calculator out of the equation (pun intended).

[1]: Because it would relieve you of understanding how to evaluate the equation.

Re: AI is different

#803
post #22

Earlier quoted context omitted.

LLMs are limited because we want them to do jobs that are not clearly defined / have difficult to measure progress or success metrics / are not fully solved problems (open ended) / have poor grounding in an external reality. Robotics does not suffer from those maladies. There are other hurdles, but none are intractable. I think we might see AI being much, much more effective with embodiment.

What? Robotics will have far more ambiguity and nuance to deal with than language models, and they'll have to analyze realtime audio and video to do so. Jobs are not so clearly defined as you imagine in the real world. For example, explain to me what a plumber does, precisely and how you would train a robot to do so? How do you train it to navigate ANY type of buildings internal plumbing structure and safely repair o…

I don’t think robot plumbers are coming anytime soon lol. Robot warehouse workers, factory robots, cleaning robots, delivery robots, security robots, general services robots, sure.

Stuff you can give someone 0-20 hours of training and expect them to do 80% as well as someone who has been doing it for 5 years are the kinds of jobs that robots will be able to do, but perhaps with certain technical skills bolted on.

Plumbing a requires the effective understanding and application of engineering knowledge, and I don’t think unsupervised transformer models are going to do that well.

Trades like plumbing that take humans 10-20 years to truly master aren’t the low hanging fruit.

A robot that can pick up a few boxes of roofing at a time and carry it up the ladder is what we need.

Re: AI is different

#804

Earlier quoted context omitted.

There is another big and growing group: charlatans (influencers). People who don't know much but make bold statements, select 'proof' cases. Just to get attention. There are many of them on youtube. When you someone on thumbnail making faces this is most likely it.

> There are many of them on youtube. Not as many as on HN. "Influencers" have agendas and the stream of income, or other self-interest. HN always comes off as a monolith, on any subject. Counter-arguments get ignored and downvoted to oblivion.

If you type "AI" into the youtube search bar it's quite impressive. I think they win.

Re: AI is different

#805

Earlier quoted context omitted.

Indeed, but I think it renders your point obsolete, since deeply imperfect resource allocation isn't really resource allocation at all, it is (in this case) resource accumulation. Are you suggesting that compound interest serves to redistribute the wealth coming from extractive industries?

Are you suggesting that economics is primarily concerned with compounding interest?

no, i am suggesting that economics is primarily concerned with resource accumulation.

my point about compound interest is that it is a major mechanism that prevents equitable redistrubution of resources, and is thus a factor in making economics (as it stands) bad at resource allocation.

Re: AI is different

#806
post #22

Earlier quoted context omitted.

LLMs are limited because we want them to do jobs that are not clearly defined / have difficult to measure progress or success metrics / are not fully solved problems (open ended) / have poor grounding in an external reality. Robotics does not suffer from those maladies. There are other hurdles, but none are intractable. I think we might see AI being much, much more effective with embodiment.

do you know how undefined and difficult to measure it is to load silverware into a dishwasher?

As someone who actually has built robots to solve similar challenges, I’ve got a pretty good idea of that specific problem. Not too far from putting sticks in a cup, which is doable with a lot of situational variance.

Will it do as good a job a competent adult? Probably not. Will it do it as well as the average 6 year old kid? Yeah, probably.

But given enough properly loaded dishwashers to work from, I think you might be surprised how effective VLA/VLB models can be. We just need a few hundred thousand man hours of dishwasher loading for training data.

Re: AI is different

#807
post #771
post #761

Earlier quoted context omitted.

You asked earlier if you were being overly cynical, and I think the answer to that is "yes" We are indeed simulating what we find in nature when we create neural networks and transformers, and AI companies are indeed investing heavily in BCI research. ChatGPT can write an original essay better than most of my students. Its also artificial. Is that not artificial intelligence?

It is not intelligent. Hiding the training data behind gradient descent and then making attributions to the program that responds using this model is certainly artificial though. This analogy just isn't holding water.

Can't you judge on the results though rather than saying AI isn't intelligent because it uses gradient descent and biology is intelligent because it uses wet neurons?

Re: AI is different

#808

This is an accurate assessment. I do feel that there is a routine bias on HN to underplay AI. I think it's people not wanting to lose control or relative status in the world. AI is an existential threat to the unique utility of humans, which has been the last line of defense against absolute despotism (i.e. a tyrannical government will not kill all its citizens because it still needs them to perform jobs. If humans a…

> I do feel that there is a routine bias on HN to underplay AI It's always interesting to see this take because my perception is the exact opposite. I don't think there's ever been an issue for me personally with a bigger mismatch in perceptions than AI. It sometimes feels like the various sides live in different realities.

I have the impression a lot depends on people's past reading and knowledge of what's going on. If you've read the likes of Kurzweil, Moravec, maybe Turing, you're probably going to treat AGI/ASI as inevitable. For people who haven't they just see these chatbots and the like and think those won't change things much.

It's maybe a bit like the early days of covid when the likes of Trump were saying it's nothing, it'll be over by the spring while people who understood virology could see that a bigger thing was on the way.

Re: AI is different

#809

When I hear folks glazing some kinda impending jobless utopia , I think of the intervening years. I shudder. As they say, "An empty stomach knows no morality."

Assuming AI works well, I can't see any "empty stomach" stuff. It should produce abundance. People will probably have political arguments about how to divide it but it should be doable.

Re: AI is different

#810

I am just not having this experience of AI being terribly useful. I don’t program as much in my role but I’ve found it’s a giant time sink. I recognize that many people are finding it incredibly helpful but when I get deeper into a particular issue or topic, it falls very flat.

This is my view on it too. Antirez is a Torvalds-level legend as far as I'm concerned, when he speaks I listen - but he is clearly seeing something here that I am not. I can't help but feel like there is an information asymmetry problem more generally here, which I guess is the point of this piece, but I also don't think that's substantially different to any other hype cycle - "What do they know that I don't?" Usuall…

A lot of AI optimist views are driven more by Moore's law like advances in the hardware rather than LLM algorithms being that special. Indeed the algorithms need to change really so future AIs can think and learn rather than just be pretrained. If you read Moravec's paper written in 1989 predicting human level AI progress around now (mid 2020s) there's nothing about LLMs or specific algorithms - it's all Moore's law type stuff. But it's proved pretty accurate.
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