“Can This Man Make AI More Human?”(MIT Technology Review),
Nowadays almost everyone else trying to commercialize AI, from Google to Baidu, is focused on algorithms that roughly model the way neurons and synapses in the brain change as they are exposed to new information and experiences. This approach, known as deep learning, has produced some astonishing results in recent years, especially as more data and more powerful computer hardware have allowed the underlying calculations to grow in scale.
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But is deep learning based on a model of the brain that is too simple?
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Researchers who are trying to develop machines capable of conversing naturally with people are doing it by giving their systems countless transcripts of previous conversations. This might well produce something capable of simple conversation, but cognitive science suggests it is not how the human mind acquires language.
In contrast, a two-year-old’s ability to learn by extrapolating and generalizing—albeit imperfectly—is far more sophisticated. Clearly the brain is capable of more than just recognizing patterns in large amounts of data: it has a way to acquire deeper abstractions from relatively little data.