The Bankwatch

Tracking the consumer evolution of financial services

Move 37 | Implications for progress on Artificial Intelligence

I watch and listed to Google I/O today. The stuff about the new communications app Allo and new emojis was a bit underwhelming but I sensed a deliberate shift under the guidance of SEO Pinchai towards commercialization with the likes of Google Home coming this year. This is going right after the Amazon Echo market, no doubt with a view to address and expand upon the earlier narrow view exemplified by the Nest purchase.

But one comment from Pinchai on “Move 37” came closer towards the end of I/O struck me as prescient with regard to Artificial Intelligence (AI) and that hooked me.

If you want to now more about the status and implication of AI, I recommend this two piece analysis at waitbutwhy. Tim Urban explains very clearly AI using a three level model. If you have any interest in AI, this is a must read. It is neither scary nor technical. It simply and carefully (for our human brains) explains the inevitability and implication of AI:

Artificial Narrow Intelligence (ANI): Sometimes referred to as Weak AI, Artificial Narrow Intelligence is AI that specializes in one area. There’s AI that can beat the world chess champion in chess, but that’s the only thing it does. Ask it to figure out a better way to store data on a hard drive, and it’ll look at you blankly.

AI Caliber 2) Artificial General Intelligence (AGI): Sometimes referred to as Strong AI, or Human-Level AI, Artificial General Intelligence refers to a computer that is as smart as a human across the board—a machine that can perform any intellectual task that a human being can. Creating AGI is a much harder task than creating ANI, and we’re yet to do it.


AI Caliber 3) Artificial Superintelligence (ASI): Oxford philosopher and leading AI thinker Nick Bostrom defines superintelligence as “an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills.” Artificial Superintelligence ranges from a computer that’s just a little smarter than a human to one that’s trillions of times smarter—across the board.


Let us return to Pinchai’s reference to

Move 37.

I had followed the AlphaGo vs Lee Sedol Go match series in which AlphaGo won 3 of 4 games. Go is generally accepted as the most complex board game with so many alternative moves as to be almost unlimited. Unlike chess it is not possible to program a series of moves and responses.

During Game 2, AlphaGo made a move at Move 37, that left all the observing experts aghast. So much so that Lee spent 15 minutes considering how to respond.

Move 37 was a move that no human would have considered. It turns out in this analysis at Wired, that AlphaGo had uncovered a move that no human would have considered because it had a 1/ 10,000 likelihood of being deployed, yet AlphaGo realized Move 37 had a high change of success.

It seems to me that in the Urban model AlphaGo may have jumped right over Level 2 AGI (which is yet to be created) and straight to level 3 ASI.

Here is an extract from the Wired Article which I recommend to all.

A One in Ten Thousand Probability

Following the game, in the control room, Silver could revisit the precise calculations AlphaGo made in choosing Move 37. Drawing on its extensive training with millions upon millions of human moves, the machine actually calculates the probability that a human will make a particular play in the midst of a game. “That’s how it guides the moves it considers,” Silver says. For Move 37, the probability was one in ten thousand. In other words, AlphaGo knew this was not a move that a professional Go player would make.

But, drawing on all its other training with millions of moves generated by games with itself, it came to view Move 37 in a different way. It came to realize that, although no professional would play it, the move would likely prove quite successful. “It discovered this for itself,” Silver says, “through its own process of introspection and analysis.”

Is introspection the right word? You can be the judge. But Fan Hui was right. The move was inhuman. But it was also beautiful.

Written by Colin Henderson

May 23, 2016 at 09:23

Posted in Uncategorized

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