AlphaGo

The AlphaGo program not only continues to beat the best Go players in the world, but it is also influencing how the game is being played. Talking with some Go playing friends, they were amazed at how AlphaGo was demonstrating ideas and concepts that had been considered bad, were in fact playable. As a result, top level professional players are reassessing how the game is being played.
It seems that this effect may be even more profound than the effect computers had on chess. While computers probably taught the modern generation the increased importance of tactical calculation, and probably helped resurrect some openings that had been considered less than optimal.  the underlying strategic concepts did not really change. Computers did the same things that humans did, just faster and better. With AlphaGo, it seems that its learning method of recognising good and bad moves based on patterns and previous games has not only come up with better moves, but also enabled it to recognise better structures.
AlphaGo has just completed a series of matches in China, against some of the worlds leading players. At the end of the match the AlphaGo developers have released a set of 50 games which AlphaGo played against itself, to show some of the new ideas it has learned. You can play through all 50 games here.

Another human activity taken down

While I was overseas I kept up with events outside the chess world, including the Human v AI Poker Match. The Libratus Poker bot, developed at Carnegie-Mellon played 4 poker pros in heads up no limit holdem, and beat all 4 of them. As with most AI v Human matches, this was a rematch after an earlier version of the program lost to human players a few years back.
Reading about the match, and the approach the bot used, there was one significant factor which I recognised from earlier Chess/Checkers/Go matches. While there was plenty of smarts built into each of these engines, it was the lack of emotional attachment to decisions that seems to be a big difference. Humans may decide that a certain move or choice is the 'smart play', but then decide not to play it due to other factors (tiredness, intuition, emotion). Bot's on the other hand will make a decision and then execute it. In chess this is often manifested by a change of plan depending on the previous move, which humans are slower to try. According to the authors of Libratus, in certain situations Libratus was 'fearless', which gave it an advantage.
While the win for the bot is significant I'll withhold judgement on whether it will change poker in the same way that engines changed chess. There may be a reassessment of how certain hands should be played, but overall I think the 'game space' is small enough that humans already have most of it covered.

A 1950's Brain

When I was a kid (in the 1970's), the Sydney Museum of Applied Arts and Sciences was a cool place to visit. One of the best exhibits was a machine that played Tic-Tac-Toe. Given that this was in the days before the PC, it was a pretty impressive piece of equipment, especially as it couldn't be beaten.
It turns out that building an unbeatable Tic-Tac-Toe machine was even possible in the 1950's, and all you needed was some light bulbs, a torch battery, some rotary switches and some wire. A 1959 book 'Braniacs' had the design of such a machine, as well as some other fabulous 'small electronic brain machines'*. The trick with the Tic-Tac-Toe machine was that (a) it always went first and (b) and it always occupied the centre square. With these two conditions it is possible to reduce the solution space to something that can be wired together fairly simply. Now I can't remember if the machine at the Applied Arts and Sciences Museum had the same conditions, but I suspect the design principles would be fairly similar.

*My favourite 'Brain' in the book is the Masculine-Feminine Testing Machine. It starts off asking whether you prefer Marilyn Monroe or Liberace(!), and goes on to discuss whether men make better drivers as they 'are more skilled'. 1950's thinking at its best!