[skrtskrt]

I mean even people that are "bad at catching things" are still getting ridiculously close to catching it - getting hands to the right area probably within well under a second of the right timing - without being taught anything in particular about how a ball moves through the air.

[taeric]

Uh.... have you been around kids? It will take several absurd misses before they even start to respond to a ball in flight.

[331c8c71]

I hope we still agree the kids learn extremely efficiently by ml standards.

[choilive]

Makes a lot of sense, there's massive evolutionary pressure to build brains that have both incredible learning rate and efficiency. Its literally a life or death optimization.

[Asraelite]

It's especially impressive when you consider that evolution hasn't had very long to produce these results.

Humans as an intelligent-ish species have been around for about 10 million years depending on where you define the cutoff. At 10 years per generation, that's 1 million generations for our brain to evolve.

1 million generations isn't much by machine learning standards.

[idiotsecant]

I think you're underestimating how much our time as pre-humans baked useful structure into our brains.

[notnaut]

Two rocks smashing together experience which one is bigger!

[roywiggins]

These sorts of motor skills are probably older than mammals.

[choilive]

Other than our large neocortex and frontal lobe (which exists in some capacity in mammals), the rest of the structures are evolutionarily ancient. Pre-mammalian in fact.

[onjectic]

Its much more than that if you count sexual reproduction.

[falcor84]

This isn't that obvious to me with current tech. If you give me a novel task requiring perception, pattern matching and reasoning, and I have the option of either starting to train an 8 year-old to do it, or to train an ML model, I would most likely go with the ML approach as my first choice. And I think it even makes sense financially, if we're comparing the "total cost of ownership" of a kid over that time period with the costs of developing and training the ML system.

[lovich]

> This isn't that obvious to me with current tech. If you give me a novel task requiring perception, pattern matching and reasoning,…

If that’s your criteria I think the kid will outperform the model every time since these models do not actually reason

[falcor84]

As I see it, "reasoning" is as fuzzy as "thinking", and saying that AI systems don't reason is similar to saying that airplanes don't fly. As a particular example, would you argue that game engines like AlphaZero aren't capable of reasoning about the next best move? If so, please just choose whatever verb you think is appropriate to what they're doing and use that instead of "reasoning" in my previous comment.

EDIT: Fixed typo

[lovich]

> . As a particular example, would you argue that game engines like AlphaZero aren't capable of reasoning about the next best move?

Yea, I probably wouldn’t classify that as “reasoning”. I’d probably be fine with saying these models are “thinking”, in a manner. That on its own is a pretty gigantic technology leap, but nothing I’ve seen suggests that these models are “reasoning”.

Also to be clear I don’t think most kids would end up doing any “reasoning” without training either, but they have the capability of doing so

[taneq]

Depends on the task. Anything involving physical interaction, social interaction, movement, navigation, or adaptability is going to go to the kid.

“Go grab the dish cloth, it’s somewhere in the sink, if it’s yucky then throw it out and get a new one.”

[Dylan16807]

It's more about efficiency in number of trials.

Would you pick the ML model if you could only do a hundred throws per hour?

[soulofmischief]

All we can say for sure at the moment is that humans have better encoded priors.

[saagarjha]

Stop missing and they will respond to the ball a lot sooner.