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Comment by TaupeRanger | Hacker News Reader

the best AI is much smarter at chess than any 4 year old

An AI is not "smarter at chess" than a 4 year old any more than a calculator is "smarter at arithmetic" than a 4 year old or a car is "smarter at moving fast" than a 4 year old. A modern AI program is simply a computational statistics program crunching some numbers. It has no "smarts" or "understanding" of the game in any meaningful sense. The fact that it can beat a 4 year old at the game of chess is unsurprising and not particularly meaningful.

We have no idea what it takes to get general intelligence and/or understanding. Until we do, comparing computational statistics programs to 4 year old children is rather a meaningless exercise, just as Turing and Djikstra told us decades ago:

"The question of whether Machines Can Think... is about as relevant as the question of whether Submarines Can Swim."

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I feel like that with that line of reasoning you could also say that a 34-year-old isn't smarter than a 4-year-old. The 34-year-old just has a bigger dataset.

A 4 year old has "general purpose intelligence". It's an "algorithm" that can learn (from) anything. Can the translating AI solve a simple puzzle? No, because it is only trained for a specific and narrow activity. The same for most other specialized AIs. Alpha Zero can beat anyone at chess. But ask it to identify LEGO toys and it will fail.

Most devices we use are far better at doing their job than a human, which is why we use them. But even if they learn and improve what they're doing they are still only able to do that one single thing.

Also I noticed above that the misconception still persists that autonomous driving today is safer than human driving although it has been proven wrong [0]. It will come at some point but we're not there yet.

[0] https://arstechnica.com/cars/2019/02/in-2017-the-feds-said-t...

The changes I've seen in the past year go far beyond what could be explained by a "bigger dataset" alone.

Her brain processing is changing on the most fundamental level. Her ability to focus on a task has improved massively. Far less random gibberish is coming out of her. She is now capable of thinking how others would feel in her shoes and now plans for the future. Her random output isn't a Markov chain with a better dataset. The input from our world is changing the wiring up there in a way that no ML model is changed by its data.

As someone who has learned a 2nd language as a child and a 3rd as an adult, I also know personally that it's far more than the dataset alone.

EDIT: updated comment after re-reading the chain.

I wasn't arguing that was the case but felt like the parent's logic would extend to that conclusion.

I have three young children and I have observed the same as you with your niece. However a lot of it is that as children learn cause and effect they are better able to optimize for their desired outcomes.

"smarter" is probably a poor choice of words. "more capable" at certain tasks then definitely. The sibling comment to this talks about identifying Legos. My four-year-old can do that because they now know Plato's form of the Lego because they observed me saying the word Lego while holding them to understand what that is. With enough observations I would think that a general purpose AI could identify the forms and then launch more specific AIs for the tasks.

The distinction is apples and oranges. A 4 year old is capable of creating explanatory knowledge about the world. A 34 year old is better at doing that. All current computational statistics programs are utterly incapable of anything even remotely approaching this capability.

See? That line of reasoning is exactly what I mean when I say we're moving the goalposts on what it means to be intelligent.

Ultimately our brains also fuzzy statistics and arithmetic on the signals going to our brains, but we create intelligent results from that. Is it suddenly not intelligent anymore once you know how the sausage is made?

Not at all. The goalposts are the same as they always were. If we want intelligent machines (the kind capable of creativity, that is, the ability to create new explanatory knowledge about reality), then we will need to see evidence of this creativity. So far no AI has even remotely approached this, because, among other things, no AI is capable of explaining anything at all.

No, the goalposts have definitely moved. Playing chess used to be a sign of intelligence, and for that reason, game playing has always been a big focus for AI research. Search algorithms in general have always been part of AI research.

They may not be self-learning, but not all AI is. And modern chess and go AI is self-learning and scarily good at it.

You don't even hear about the Turing test anymore. The orignal turing test was an AI algorithm fooling a human that it itself is human for ~5 minutes. One.

The reason you don't hear it anymore is that it's obvious that algorithms are doing this on the phone for commercial purposes constantly.

It's ridiculous how far the goalposts have moved.

The goalposts are exactly where I said they are. They have always been there for people that actually understand the nature of the problem. The fact that some people were spectacularly and obviously wrong about the nature of chess programs is irrelevant.

Now you're just trying to sound pompous in an attempt to seem authoritative, but you're really not saying anything meaningful here. Where are those goalposts according to you? Who are those "people that actually understand the nature of the problem"? Which people are "spectacularly and obviously wrong about the nature of chess programs"?

It is AI researchers themselves who decided that chess and game-playing in general were interesting to research. Everybody used to consider skill at chess a sign of intelligence. There have been many, many problems that have long been complex problems for AI to tackle, and that have only recently struck people as being not really about intelligence. Creativity was barely on the table for many decades, and has only recently come within reach of AI research.

I wonder if maybe you're only looking at the last 20 years, and ignore the half century before that.

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