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Comment by weeksie | Hacker News Reader

The conspicuously missing tech in the rundown he gave is ML, which actually seems to be meeting up to a lot of the hype and I think will be pretty revolutionary, though not as revolutionary as a lot of the enthusiasts believe.

Even if ML models hit an unexpected scaling problem, they're still very very useful. Extremely disruptive, too. Then again, it could be ages before we figure out how to put them to the best use.

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Do feel free to write your own blog post about ML.

But, if you want my take on it, there's a lot of hype and not much substance there.

There's a good article at https://garymarcus.substack.com/p/did-googleai-just-snooker-...

A guy who can look at stable diffusion and audio LM and go bah, It's not all that great and it's certainly not AI... has definitively passed the inflection point.

I'm on team "What a time to be alive".

Agreed. AI over the last few years is so far ahead of what I thought would be possible it's dizzying. Progress is so often not in the place, or delivered in the manner, that you're expecting. Maybe the one human constant?

It is remarkable but I do think people are missing the forest for the trees.

Stunning trees in isolation are impressive and awe-inspiring, but note that the rest of the trees in the forest are made up of just the same stuff and composed in extremely similar ways!

ML shows not that computers can be smart, but that smarts is just a matter of statistics + abstraction. In this way no "intelligent" being is any more impressive, just more complex and fine-tuned.

Ah a fellow doktorkaroljohlnarnihfahèr connoisseur

I've read a few of Gary Marcus' posts and I like him. My position is much more that the capabilities of current models are good enough for a lot uses. I certainly don't think language models are "real intelligence" or that we're anywhere near achieving that, just that excellent search and mashup engines (current language models) are proving to be extremely useful.

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