[BoiledCabbage]

Mind if I ask what decade your age is?

The appearance of LLMs has been the strangest phenomenon. If course not everyone agrees, but I feel like I'm watching the arrival of the automobile and am having people say to me "It's loud, it's slow and it breaks down often. There's nothing to see here. It's just a fad.".

Just about everyone in tech I know in person in their 40s and above, believe this will be the biggest thing since the internet. People who have been in tech long enough to actually see transformative technologies arrive - People who saw the rise of the web, and dotcom bubble, and open source, and mobile w/ app stores... They all are looking at this and saying this is gonna be huge.

And for the most part the people pushing how big it isn't going to be mostly seem to be in their 20s and 30s who haven't really lived through a tech revolution who are saying it's not much, and over hyped. People who have grown up during the hype bubble, where grifters have been hocking crypto or NFTs or rug pull du jour seem to be least excited. As one of the people in the older category, I'm starting to think another casualty of the hype bubble era is lots of technologists (especially younger) now have trouble recognizing revolutionary technology.

In the end, one of these two camps will be wrong. Each assumes it will be the other. It's just incredible to see the split in opinion.

---------

Note: The internet is large enough that there are obviously people who are outliers to the above categories on the internet, but the general trend seems to hold.

[ineedausername]

I'm in my thirties. I might fall into the category of having trouble recognizing revolutionary technology as you say.

> They all are looking at this and saying this is gonna be huge.

It's beyond me why would anyone assume an LLM that's already been trained in most relevant and available data will just keep becoming somehow way better and smarter. I get that it has it's uses, but what do they mean by huge anyway, theoretically it could end up a huge mess too.

[bredren]

> an LLM that's already been trained in most relevant and available data

Source? Are you referring to gpt 4?

What about private data sets / corporate IP?

What about my private data, such message and email history, contacts’ available or privately shareable data, my photo and video library, and health data?

Presuming all of this was included in an LLM directly or as some kind of additional LORAs.

It seems clear to me that the tooling and resource requirements prevent anything near full accessibility of the content that is there.

[pxmpxm]

Exact opposite experience on my end - impressionable gen-z kids, and people with minimal background on the topic,* are seeing it as the second coming of christ, where as all the math-and-adjacent PhDs, especially ML-focused, I work with are not buying the hype.

* There's really bizarre tendency of that group to woo-woo and anthropomorphize all those language models. I get answers like "oh it just knows" or "you should try it" when asking probing/hypothetical question.

[Terretta]

Today's AI(ML) is "just" big statistics. And so ...

The math-and-adjacent cohort you mention would like to avoid another "AI winter".

It's possible "you should try it" is a UX use case indicator that (perhaps akin to engineers who don't understand why normies buy iPhones) those telling you this feel you're missing something essential about the experience of this tech's utility: "You may be right, but this works for me, while whatever else you're on about ... doesn't."

As for woo woo, this is the first time the big statistics are indistinguishable from magic for them, passing the Turing Test en masse.

[survirtual]

Highly educated people spent a very long time creating a moat economically with their intelligence. Now, a being of intelligence can augment anyone without having to waste most of their lives learning, and most of professionally brain work is about to be obsolete.

Who has more to lose with the advent of such a tool?