Hacker News Reader

Comment by jcoffland | Hacker News Reader

> Now I find it hard to hold on to the belief that I understand what is "A" and what is "B", while computer can only compute.

Humans being surprised by the computer should not be the yardstick for AI. A trained neural net can recognize the letter "A" and differentiate it from things that are not "A" but it does not know that "A" is part of the Latin alphabet and that there are other alphabets that form written human languages.

The day the computer spontaneously invents a new and usable alphabet without having been specifically designed to do so is the day I will concede we have hard AI. We have a long way to go. Until then it's just a bunch of hotdog/not hotdog classifiers.

View on HN

> The day the computer spontaneously invents a new and usable alphabet without having been specifically designed to do so is the day I will concede we have hard AI.

Most humans have not spontaneously invented new usable alphabets, so I suppose that means most humans haven't meet the bar for true intelligence either.

I still don't understand this obsession for trying to define "hard AI" or "true intelligence" in binary terms. Intelligence is a spectrum, and deep learning has advanced it forward, thus making machines more intelligent -- yes, we can use that word 'intelligent' for computers just as we do for biological machines. Don't freak out.

Is it really so hard to accept that intelligence isn't all-or-nothing?

Intelligence is a spectrum, although creativity is trickier to define. I would argue that most children grow up inventing their own methods of expression (usually pictorial), until they learn the existing mones well enough to communicate satisfyingly enough. The capacity and drive to create, perceive, and extend is innate.

but it does not know that "A" is part of the Latin alphabet and that there are other alphabets that form written human languages.

There is nothing preventing the computer for learning those connections however, so all you are doing is moving the abstraction layer. It's not a fundamental break point.

> The day the computer spontaneously invents a new and usable alphabet without having been specifically designed to do so is the day I will concede we have hard AI. We have a long way to go. Until then it's just a bunch of hotdog/not hotdog classifiers.

Happened already at Google and Facebook. Namely Neural Turing Machines have created an intermediate language, that's a more efficent encoding, without being designed to do so. See: https://techcrunch.com/2016/11/22/googles-ai-translation-too...

But that's really old news and DNCs are more capable, afaik.

I have subsystems in my brain processing he letter A that also do not know that it's part of the Latin Alphabet. It's a start but I agree we have a long long way to go to hard AI and I'd be surprised if I see it in my lifetime.

To me the recognizing of the letter is a whole lot more impressive than knowing facts about it (If we're talking about OCR).

In your example a computer could very easily learn those simple facts, just like you did. It's nothing to tell a program how to classify a piece of data. You didn't use some crazy learning when you attributed A to being part of a Latin alphabet, someone just told you that fact and you saved it and classified A into the Latin alphabet.

Reply on news.ycombinator.com