[ttt_]

I agree. While reading the article I can't help but, sort of, empathize with modern AI programs. Me and Watson are very similar, Watson can win Jeopardy but has no understanding why, I can recognize a handwritten 'a' and I too have no understanding why.

When I look at my daughter developing, from baby to infant to child. Hasn't that been a constant, intensive training? As she recognizes stuff, I give feedback. After a while she starts correlating stuff, and signals for me to give feedback. By the time she's an adult, she will have full control of her intelligence, but also no understanding.

Maybe what we are missing is just the algorithm for information storage and retrieval. If we can master Genetic Algorithms, why not Celular Databases? Or Chemical Procedures?

[loup-vaillant]

> Me and Watson are very similar, Watson can win Jeopardy but has no understanding why, I can recognize a handwritten 'a' and I too have no understanding why.

So, you and Watson are "very similar" just because both systems don't have a perfect understanding of themselves? You don't know that. Your premises look true, but your conclusion don't follow from them (or at all). Actually you probably know that no matter how you spin it, you and Watson are very different.

So don't say you aren't, it's misleading. Not only to others, but to yourself as well. Try to find a meaningful similarity instead.

[ehsanu1]

I find myself doing poor pattern recognition at times (eg always choosing the wrong key for a particular door), and realizing just after that a machine learning library could well make the mistake I just did. This isn't a new insight, but it still feels like an epiphany when you realize it as it happens.

[huherto]

I might miss understood you. But what your are describing sounds to me like some sort of supervised learning but not necessarily a genetic algorithm.