What are people talking about when they say AI? What’s the difference between AI, machine learning, and deep learning?
Hollywood aside, today we aren’t anywhere close to strong AI. Right now, all AI is weak AI, and most researchers in the field agree that the techniques we’ve come up with to make really great weak AIs probably won’t get us to Strong AI. So AI currently represents more of a marketing term than a technical one.
How do I remember what I’ve learned? On a computer, how do I store and represent the relationships and rules I’ve extracted from the example data?
How do I do the learning? How do I modify the representation I’ve stored in response to new examples and get better?
The kind of model you use has huge effects: it determines how your AI learns, what kind of data it can learn from, and what kind of questions you can ask of it.
Say we’re shopping for figs at the grocery store, and we want to make a machine learning AI that tells us when they’re ripe.
Our baby AI doesn’t know anything about sugar content or how fruits ripen, but it can predict how sweet a fruit will be by squeezing it.
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