Hacker News Reader

Comment by shanebellone | Hacker News Reader

ChatGPT is nothing more than long-form autocomplete. The specifics of approach are irrelevant.

I knew something changed after AlphaGo. Compute could do what we thought only true intelligence can do. So I agree, LLMs are not a black swan. It will change everything, nevertheless.

I keep reading these opinions that LLMs are just doing some advanced form of copy paste. Actually, we don't know what they are doing. Are they actually doing some form of modelling and abstraction? Seems likely to me.

AlphaGo is basically the same as image recognition, not sure why you thought AlphaGo was special compared to detecting faces. AlphaGo works the same way but maps game structures on a Go board instead of mapping facial structures and comparing those to known people.

It was able to beat the top GO player. What does it matter if that technology is also used in image recognition. I'd say that if its 'brain' can play games and recognize people, or in case of ChatGPT4, can talk and play chess, this is all starting to sound pretty 'General' to me.

That's exactly the kind of attitude I am talking about. You can rationalise pretty much everything and keep moving the goal post. I've seen AI do something nobody thought was possible. If that doesn't influence how you think about AI I cannot help you.

Nobody?

Well, maybe the self-driving car people thought it was possible. But I don't take them seriously.

"I keep reading these opinions that LLMs are just doing some advanced form of copy paste. Actually, we don't know what they are doing. Are they actually doing some form of modelling and abstraction? Seems likely to me."

This is exactly the problem with AI. For business or government, the answer is as important as the methodology employed. A black box does not work for the majority of use cases.

Until it can show its work, it's a sideshow.

Humans are also "black boxes" we don't fully understand. It's worked pretty well.

This is a shallow counterargument that entirely misses the point.

This is not even an argument, only a disagreement.

"This is not even an argument, only a disagreement."

It's a straw man.

The need for transparency in process is known, documented, and undisputed. Your comment has no relevance. My brain might be a black box, but I can still communicate and/or document the specifics of a process.

Can [insert your preferred model] do that? Didn't think so.

Given the changes in health over the past century and a half as we've adopted "science" into food, I'm not sure that I agree.

Yes, in many situations it is important that we get AIs to explain how they came up with a result, and that we are confident in the correctness of the explanation. That is probably the most interesting thing you can work on now. Is that a sideshow? I don't think so, although I wouldn't mind that at all.

next bit prediction, or long-form autocomplete, may lead to general intelligence. http://mattmahoney.net/dc/rationale.html

A human brain is nothing more than long-form autocomplete. The specifics of approach are irrelevant.

Exactly. All the people saying LLM's aren't important because it is just auto-complete, really don't connect the dots that humans are also just auto-complete.

What on earth are you talking about?

Our brain excels at pattern matching. We attribute a lot of human abilities to “intelligence”, but the line between that and pattern-matching (or “autocomplete” ad it’s being referred as here) is being challenged by these latest LLMs.

If it can look at a picture, explain what’s in it, and hypothesize about physics inside the picture’s environment, is it “just pattern matching”?

"If it can look at a picture, explain what’s in it, and hypothesize about physics inside the picture’s environment, is it “just pattern matching”?"

That's extrapolation via approximation. Computers synthesize a specification. The difference is nuanced and entirely contextual.

Those are way too broad terms for this conversation to go anywhere. The point is, what's to say the LLM is not doing "extrapolation via approximation" or some process that is analog to how we think? We barely understand how the brain works to start with.

But the human brain is a much more mature product (although I will concede there are still a ton of bugs to work out that we really have no idea how to repair because the product is extremely complex and still pretty fragile).

Everyone likes to say this, but no one seems to provide evidence. I don't believe it.

Why do you think that?

Reply on news.ycombinator.com