It was a result that sent (1)shockwaves through the Go community. AlphaGo,
the computer created by DeepMind, the Artificial Intelligence (AI) arm of
Google, (2)thrashed European Go champion Fan Hui 5-0 – the first time a
computer program has beaten a professional player of the ancient Chinese game.
Played on a board with a 19x19 grid of black lines, Go is such a complex
game that enthusiasts hoped it would be years, or perhaps decades, before
machines would be able to (3)triumph over the best human players.
But now that time scale is shortening and AlphaGo is scheduled to play the
world’s top player, Lee Sedol, over five games in March.
Mr. Lee is a much stronger player than Mr. Fan and for now remains
confident. “This is the first time that a computer has challenged a top human
pro in an even game,” he said. “I have heard that Google DeepMind’s AI is
surprisingly strong and getting stronger, but I am confident that I can win, at
least this time.” It’s the “at least” that’s significant here. The parallels
with chess are ominous. IBM’s Deep Blue lost 4-2 to Gary Kasparov the first
time they played in Philadelphia in 1996, but
triumphed 3.5-2.5 a year
later in New York .
Mr. Lee may not (4)succumb the first or even the second time, but in the end he
or a successor will and another bastion will have fallen.
Go is such a complicated game that until recently the programs could
defeat only amateurs and the Google team had to use a new approach. It now
looks ahead by playing out the rest of the game in its imagination, many times
over.
The program involves two neural networks, software that mimics the
structure of the human brain. It was trained by observing millions of games of
Go and evolved to predict expert moves 57 per cent of the time. The network was
then set to play against itself, learning from its victories and losses as it
carried out more than a million individual games over the course of a day.
This is only possible, of course, due to the huge improvements in
computing power in recent decades. And the bottom line is that the machines
are, or will soon be, able to defeat the best humans at most games.
We in the chess community have had to deal with this for nearly two
decades now, and the solution has been to accept that they will beat us in
single combat but work around it.
We know that as human beings we will make small mistakes, however well we
play. Chess playing computers (“engines”) are uniquely well placed to exploit
these and once they have a material advantage are almost totally unplayable.
But we can console ourselves that they still don’t create that much themselves
and rather than banging our heads against a brick wall, we can use them as
superb training agents.
We use “engines” extensively in preparing for games – training in which
the crucial element is that the human must lead the machine rather than
following.
Structure
of the Lead:
WHO-AlpthGo
and Lee Sedol
WHEN- Mar 2016
WHAT- The
competition with an AI robot
WHY- Proof
the ability about people and AI robots
WHERE- Unknown
HOW- The
AI robot win the four fifths of competitions
Keywords:
(1) shockwave衝擊波
(2) thrash鞭打
(3) triumph勝利
(4) succumb屈服於