The truth behind AI, machine learning, and bots

Artificial intelligence — in the guises of personal assistants, bots, self-driving cars, and machine learning — is hot again, dominating Silicon Valley conversations, tech media reports, and vendor trade shows.

AI is one of those technologies whose promise is resurrected periodically, but only slowly advances into the real world. I remember the dog-and-pony AI shows at IBM, MIT, Carnie-Melon, Thinking Machines, and the like in the mid-1980s, as well as the technohippie proponents like Jaron Lanier who often graced the covers of the era’s gee-whiz magazine like “Omni.”

AI is an area where much of the science is well established, but the implementation is still quite immature. It’s not that the emperor has no clothes — rather, the emperor is only now wearing underwear. There’s a lot more dressing to be done.

Thus, take all these intelligent machine/software promises with a big grain of salt. We’re decades away from a “Star Trek”-style conversational computer, much less the artificial intelligence of Stephen Spielberg’s “A.I.”

Still, there’s a lot happening in general AI. Smart developers and companies will focus on the specific areas that have real current potential and leave the rest to sci-fi writers and the gee-whiz press.

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For years, popular fiction has fused robots with artificial intelligence, from Gort of “The Day the Earth Stood Still” to the Cylons of “Battlestar Galactica,” from the pseudo-human robots of Isaac Asimov’s “I Robot” novel to Data of “Star Trek: The Next Generation.” However, robots are not silicon intelligences but machines that can perform mechanical tasks formerly handled by people — often more reliably, faster, and without demands for a living wage or benefits.

Robots are common in manufacturing and becoming used in hospitals for delivery and drug fulfillment (since they won’t steal drugs for personal use), but not so much in office buildings and homes.

There’ve been incredible advances lately in the field of bionics, largely driven by war veterans who’ve lost limbs in the several wars of the last two decades. We now see limbs that can respond to neural impulses and brain waves as if they were natural appendages, and it’s clear they soon won’t need all those wires and external computers to work.

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Maybe one day we’ll fuse AI with robots and end up slaves to the Cylons — or worse. But not for a very long while. In the meantime, some advances in AI will help robots work better, because their software can become more sophisticated.

Most of what is now positioned as the base of AI — product recommendations at Amazon, content recommendations at Facebook, voice recognition by Apple’s Siri, driving suggestions from Google Maps, and so on — is simply pattern matching. 

Thanks to the ongoing advances in data storage and computational capacity, boosted by cloud computing, more patterns can be stored, identified, and acted on then ever before. Much of what people do is based on pattern matching — to solve an issue, you first try to figure out what it is like that you already know, then try the solutions you already know. The faster the pattern matching to likeliest actions or outcomes, the more intelligent the system seems.

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But we’re still in early days. There are some cases, such as navigation, where systems have become very good, to the point where (some) people will now drive onto an airport tarmac, into a lake, or onto a snowed-in country road because their GPS told them to, contrary to all the signals the people themselves have to the contrary.

But mostly, these systems are dumb. That’s why when yo go to Amazon and look at products, many websites you visit feature those products in their ads. That’s especially silly if you bought the product or decided not to — but all these systems know is you looked at X product, so they’ll keep showing you more of the same. That’s anything but intelligent.

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