Only if you believe in it. Many CEOs do. They're very good in magical thinking.

Magic as in street magician, not magic as in wizard. Lots of the things that people claim AI can do are like a magic show, it's amazing if you look at it from the right angle, and with the right skill you can hide the strings holding it up, but if you try to use it in the real world it falls apart.

Everything is magic if you don't understand how the thing works.

The masses have been treating it like actual magic since the early stages and are only slowly warming up to the idea it‘s calculations. Calculations of things that are often more than the sum of it‘s parts as people start to realize. Well some people anyway.

Sam Altman will make a big pile of investor money disappear before your very eyes.

Conversely, there are way too many people who think that humans are magic and that it's impossible for AI to ever do .

I've long believed that there's a smooth spectrum between not-intelligent and human-intelligent. It's not a binary yes/no sort of thing. There's basic inert rocks at one end, and humans at the other, and everything else gets scattered at various points in between. So I think it's fine to discuss where exactly on that scale LLMs fall, and accept the possibility that they're moving in our direction.

I really only use for "oh damn, I known there's a great one-liner to do that in Python" sort of thing. It's usually right and of it isn't it'll be immediacy obvious and you can move on with your day. For anything more complex the gas lighting and subtle errors make it unusable.

ChatGPT is great for helping with specific problems. Google search for example gives fairly general answers, or may have information that doesn't apply to your specific situation. But if you give ChatGPT a very specific description of the issue you're running into it will generally give some very useful recommendations. And it's an iterative process, you just need to treat it like a conversation.

Also interesting is that most people don't understand the advances it makes possible so when they hear people saying it's amazing and then try it of course they're going to think it's not lived upto hype.

The big things are going to completely change things like how we use computers especially being able to describe how you want it to lay out ui and create custom tools on the fly.

I think a big obstacle to meaningfully using AI is going to be public perception. Understanding the difference between CHAT-GPT and open source models means that people like us will probably continue to find ways of using AI as it continues to improve, but what I keep seeing is botched applications, where neither the consumers nor the investors who are pushing AI really understand what it is or what it's useful for. It's like trying to dig a grave with a fork - people are going to throw away the fork and say it's useless, not realising that that's not how it's meant to be used.

I'm concerned about the way the hype behaves because I wouldn't be surprised if people got so sick of hearing about AI at all, let alone broken AI nonsense, that it hastens the next AI winter. I worry that legitimate development may be held back by all the nonsense.

Lol. It doesn't do video generation. It just takes existing video and makes it look weird. Image generation is about the same: they just take existing works and smash them together, often in an incoherent way. Half the text generation shit is just fine by underpaid people in Kenya Ave and similar places.

There are a few areas where llm could be useful, things like trawling large data sets, etc, but every bit of the stuff that is being hyped as "AI" is just spam generators.

I don't know much about LLMs but latent diffusion models already have "meaning" encoded into the model. The whole concept of the u-net is that as it reduces the spacial resolution of the image, it increases the semantic resolution by adding extra dimensions of information. It came from medical image analysis where the idea of labelling something as a tumor would be really useful.

This is why you get body dysmorphic results on earlier (and even current) models. It's identified something as a human limb, but isn't quite sure on where the hand is, so it adds one on to what we know is a leg.

I agree 100%, and I think Zuckerberg's attempt at a massive 340,000 of Nvidia’s H100 GPUs AI based on LLM with the aim to create a generel AI sounds stupid. Unless there's a lot more to their attempt, it's doomed to fail.

I suppose the idea is something about achieving critical mass, but it's pretty obvious, that that is far from the only factor missing to achieve general AI.

I still think it's impressive what they can do with LLM. And it seems to be a pretty huge step forward. But It's taken about 40 years from we had decent "pattern recognition" to get here, the next step could be another 40 years?

It's pretty useful if you know exactly what you want and how to work within it's limitations.

Coworkers around me already use ChatGPT to generate code snippets for Python, Excel VBA, etc. to good success.

Well, natural language processing is placed in the trough of disillusionment and projected to stay there for years. ChatGPT was released in November 2022...