[eladgil]

Definitely not my intention to forgot or denigrate the past. Obviously all this exists due to deep learning and prior architectures. What I have been running into is many people and companies are interpreting this as "just more of the same" for prior ML waves, when really this is an entirely new capability set.

To the (bad) analogy on cars versus planes - both have wheels and can drive on the ground, but planes open up an entirely new dimension / capability set that can transform transportation, logistics, defense and other areas that cars were important, but different enough in.

[simonw]

I'm finding the comparison to the previous wave of ML absolutely fascinating.

I tinkered with ML for a few years, and it took a LOT of work to get anything useful out of it at all.

Now with LLMs I can literally type out a problem in English and there's a reasonably good chance I'll get a useful result!

It really does feel like an entirely new set of capabilities to me.

[andy99]

That's the big difference in this round. Before you had to have the ML expertise and the expertise to understand the implication of say a MNIST classifier example. Now anyone can "get" it because you're prompting and getting inference back in English. Underneath the fundamentals aren't all that different though, it has the same novelty factor and the same limitations apply.

[hulitu]

The only "entirely new dimension / capability set" that i saw at this new AI hype is its use in propaganda.

Microsoft is not capable of basic testing of its software so i don't see what AI will bring to the table besides more bugs.