Technology

I agree that the author didn't do a great job explaining, but they are right about a few things.

Primarily, LLMs are not truth machines. That just flatly and plainly not what they are. No researcher, not even OpenAI makes such a claim.

The problem is the public perception that they are. Or that they almost are. Because a lot of time, they're right. They might even be right more frequently than some people's dumber friends. And even when they're wrong, they sound right. Even when it's wrong, it still sounds smarter than most peoples smartest friends.

So, I think that the point is that there is a perception gap between what LLMs are, and what people THINK that they are.

As long as the perception is more optimistic than the reality, a bubble of some kind will exist. But just because there is a "reckoning" somewhere in the future doesn't imply it will crash to nothing. It just means the investment will align more closely to realistic expectations as the clarity of what realistic expectations even are become more clear.

LLMs are going to revolutionize and also destroy many industries. It will absolutely fundamentally change the way we interact with technology. No doubt...but for applications which strictly demand correctness, they are not appropriate tools. And investors don't really understand that yet.

OpenAI’s algorithm like all LLM’s is designed to give you the next most likely word in a sentence based on what most frequently came next in its training data. Their main strategy has actually been to use a older and simpler transformer algorithm, and to just vastly increase the scrapped text content and recently bias with each new release.

I would argue that any system that works by stringing sudorandom words together based on how often they appear in its input sources is not going to be able to do anything but generate bullshit, albeit bullshit that may happen to be correct by pure accident when it’s near directly quoting said input sources.

The article makes several claims and insinuations without backing them up so I find it hard to follow any of the reasoning.

"Article". I'm going to call it what it is: a blog post that should have moderated away. If people here are going to post "tech news", make sure it has actual journalism.

Postel’s law IMHO is a big mistake - it’s what gave us Internet Explorer and arbitrary unpredictable interpretation of HTML, leading to decades of browser incompatibility problems. But the law is not even applicable here. Unlike the Internet, we want the AI to appear to think for itself rather than being predictable.

It's almost like Isaac Asimov wrote a famous book about robotic laws and a bunch of different short stories on how easy it was to circumvent them.

Today's AI is way worst then when ChatGPT was first released.... it is way to censored.

You might need to reconsider that position. There are plenty of uncensored models available, that you can run on your local machine, that match or beat GPT-3 and beat the everliving shit out of GPT-2 and other older models. Just running them locally would have been unthinkable when GPT-3 released, let alone on CPU at reasonable speed. The fact that open source models do so well on such meager resources is pretty astounding.

I agree that it's not AGI though. There might be some "sparks" of AGI in there (as some researchers probably put it), but I don't think there's much evidence of self-awareness yet.

But either way, I never considered LLMs to be A.I. even if they have the possibility to be great.

It doesn't matter what you consider, they are absolutely a form of AI. In both definition and practice.

*too

Anything we've had before now wasn't AI.

This claim doesn't work simply due to the fact AI is a very vague term which nobody agrees on. The broadest and most literal (and possibly oldest) definition is simply any inorganic emulation of intelligence. This includes if statements and even purely mechanical devices. The narrowest definition is a computer with human-like intelligence, which is why some people claim LLMs are not AI.

Saying LLMs work differently from older AI approaches is fair, saying older approaches are not AI but the latest one is is questionable.