[peter_retief]

"So has generative AI been overhyped? Not exactly. Having generative models capable of delivering value is an exciting development. For the first time, people can interact with AI systems that don’t just automate but create an activity of which only humans were previously capable."

Good answer but I feel that most users/people do not understand the difference between generative and predictive machine learning and that will probably cause unpredictable failures and false flags. So yes it has been overhyped in my opinion

[kenjackson]

IMO, it has been underhyped. We're seeing things with LLMs that a decade ago I'd say was multiple decades out, if not more.

We're just years into generative approaches. And I think we'll more combinations of methods used in the future.

The goal of AI has never been to build an all knowing perfect system. It has also never been to replicate the way the human brain works. But its been to build an artificial system that can learn -- and AGI specifically to be able to give the appearance of human learning.

I feel like we've turned this corner where the question now is, "Can we build something that knows everything that has been documented and can also synthesize and infer all of that data at a level of a very smart human". The fact that this has become the new bar is IMO one of the biggest tech changes in history. Not the biggest, but up there.

[beepbooptheory]

Trying to imagine this stuff being even more hyped and I just don't think its possible. People around here are practically ready to sell their first born child to OpenAI/Microsoft at this point.

[PaulDavisThe1st]

> Can we build something that knows everything that has been documented and can also synthesize and infer all of that data at a level of a very smart human

The word "know" is doing some heavy lifting there, as is "synthesize" and "infer".

[kenjackson]

By "know" I meant has access to. This is a very "database" sense of the word "know".

Now "infer" and "synthesize" I meant the standard human definition of "synthesize" and "infer". In my interactions with relatively bright people, they really expect ChatGPT to be able to synthesize text at the level of a very sharp HS/college student. They don't want simple regurgitation of a text or a middel school analysis -- they want/expect ChatGPT to analyze nuance, and pull in its vast database to make connections to things that maybe aren't apparent at first glance.

The bar has raised so high so quickly -- it's crazy.

[peter_retief]

I am very excited about the possibilities of AI/ML but am concerned as to how it is been sold to the public.

[Xelynega]

I think the issue is more with people marketing/talking about them as "AI". When I think AI I think of something like Skynet. I would assume something like Skynet would be good at chess, able to generate new text, and synthesize new images. I think when shown novel algorithms that can do those things and told by the people selling the algorithms that they are "AI", it's hard to disagree since they quack like an AI so it's easy to accept that these are the same "artificial intelligence" concept in our brains which we previously only had examples of from fiction.

Basically I think it's overhyped by the use of the term "AI" and how easy we are to accept it generally. Some aspect of them being generative models could have been the term used to market/describe them, but instead a much broader term is used.