[qyv]

> But those heuristics and hardcoded biases were developed through brute force optimization over the course of billions of years, a massive amount of energy input and many organisms being devoured.

This is true in the context of the universe as a whole, not by the organism itself.

[renjimen]

Except no organism is born a blank slate. Parent is correct in that our prior was massively expensive to construct

[dkersten]

So we can expect our ANN’s to yield AGI in a few million or billion years? That doesn’t sound like a good place to put our current efforts then.

[mannykannot]

That does not necessarily follow, as I imagine you well know.

[YeGoblynQueenne]

Why wouldn't it follow? Human intelligence evolved in the real world with all its vast information content. Deep learning systems are only trained on a few terrabytes of data of a single type (images, text, sound etc). Even if they can be trained faster than the rate at which animals evolved, their training data is so poor, compared to the "data" that "trained" animal intelligence that we'll be lucky if we can arrive at anything comparable to animal intelligence by deep learning in a billion years.

Or unlucky, as the case may be.

[mannykannot]

You elided the "necessarily".

One can rationally argue either way over the speculative proposition that reinforcement learning will yield AI in less than a few million years, but that it took evolution half a billion years is hardly conclusive, and certainly not grounds for stopping work.

[dkersten]

Not grounds for stopping work[1], but perhaps grounds to explore other avenues[2] to see if something else might yield faster results.

I’m no expert, but my personal opinion is that AGI will probably be some hybrid approach that uses some reinforcement learning mixed with other techniques. At the very least, I think an AGI will need to exist in an interactive environment rather than just trained on preset datasets. Prior context or not, a child doesn’t learn by being shown a lot of images, it learns by being able to poke at the world to see what happens. I think an AGI will likely require some aspect of that (and apply reinforcement learning that way).

But like I said, I’m no expert and that’s just my layperson opinion.

[1] if the goal is AGI, if it’s not then of course there’s no reason to stop

[2] some people are doing just that, of course

[YeGoblynQueenne]

>> You elided the "necessarily".

Well, if it follows, then it follows necessarily. But maybe that's just a deformation professionelle? I spend a lot of time working with automated theorem proving where there's no ifs and buts about conclusions following from premises.

[AlphaSite]

I think the point huh is being mad is that individual people (or models) dot learn that way. It’s not like models training models, all the way down.

[the8472]

Individual people are not trained from scratch. ML models often have to be (modulo fine-tuning) since the field is still young.

[mannykannot]

That's already changing. That we have only relatively recently moved beyond always starting from scratch might indicate that we are still in the Cambrian of AI, however...