It used to be that people would get into these fields thinking ML would need specifically human insights, deep thinking, and philosophical insights about the nature of consciousness.

You would get into natural language modelling because you had a deep love of language. Because you think you're close to figuring language out in a systematic way, with just a few years more study.

There's a certain sadness, I think, in the revelation that the robots don't need the expertise of humanity's greatest experts and masters, they just need us to click all the squares that contain a motorcycle.

This is 100% not why I am sad, see my other reply for information.

As an aside, it's wild how people put their own spin onto what I said.

Obviously I should have been clearer :shrug:.

Well, you have to forgive some for making assumptions based on your choice of username…

Fair, I'm just generally disgruntled to be fair, the PhD was just the name of my soon abandoned blog.

> It used to be that people would get into these fields thinking ML would need specifically human insights, deep thinking, and philosophical insights about the nature of consciousness.

What's sadder is coming into a field pre-deciding that the way you approach it "is the right way" and can't tolerate that different mindsets can also get results.

How do you know? We’re not there yet.

Because of the way it's presented, as if it's some vast new discovery that OpenAI have made, rather than common wisdom.

It makes me sad when people rediscover things (with massive compute in this case), that were already known.

It's very much spend a year in the lab to save an hour in the library.

Possibly because being in the business of trying to turn iq edge into money, not data edge into money.