[ExI] DeepMind wins Game1 in Go championship Match
spike66 at att.net
Thu Mar 10 01:22:36 UTC 2016
From: extropy-chat [mailto:extropy-chat-bounces at lists.extropy.org] On Behalf Of Dave Sill
Sent: Wednesday, March 09, 2016 12:13 PM
To: ExI chat list <extropy-chat at lists.extropy.org>
Subject: Re: [ExI] DeepMind wins Game1 in Go championship Match
On Wed, Mar 9, 2016 at 2:39 PM, spike <spike66 at att.net <mailto:spike66 at att.net> > wrote:
I see this as encouraging however. It indicates to me that everything we think of as intelligence has some kind of algorithm behind it, and that the algorithm can be discovered. If not, something that works in place of whatever our brains are doing is discoverable.
>…If all you want is a system that can play chess or go, that's clearly doable. But these are more simulated intelligence than artificial intelligence…
Ja. Any task transitions from intelligence to simulated intelligence the minute we figure out the algorithm to do it.
>… Produce a system that can be taught any game the way a human learns it, and can learn to play it well via playing and studying the game, and *that* will be AI…-Dave
On the contrary sir, for this has been done, first with tic-tac-toe and later with checkers. I haven’t checked on later progress, but I think the algorithms never get all that good just by looking at games.
We have learning chess programs, and very simple versions of a learning program: ones which only track which openings they used and how the game came out. I don’t know this for sure, but I think most of the modern chess programs choose lines in their human-derived opening book based on how well it works. This is a form of learning.
Siri is already smarter and a better conversationalist than most teenagers, most of whom seem to communicate using a lookup table. The point is we *still* don’t have a working definition for what is machine intelligence, for we insist on constantly moving the goalposts.
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