Hello world, welcome to Sirajology! Lets talk about 4 reason AlphaGo is huge deal.
AlphaGo is an AI created by a team of researchers at Google designed to play the ancient Chinese game of Go
In Go, 2 players take turns placing black or white stones on a board. Trying to capture the opponents stones or
surround empty space to make points of territory. The first reason is that it beat the best human player in the
world at a game that is orders of magnitude more complex than Chess. Think of solving chess like painting
a line and solving Go like painting the Mona Lisa. One is just way more complex than the other.
Remember when IBM's Deep Blue beat world champion Gary Kasparov at Chess in the 90s?
At the time that was a huge deal because no program had ever done that before. What Deep Blue did
was it would examine all possible moves and all the possible counter moves and all the possible counter
counter moves until it had searched every single possible play and then picked the best one.
This is called a brute force search and it worked. But that method wouldn't work for Go because in Go there
are more possible plays than there are atoms in the universe.Crazy right? So alphago cant just try all
possible plays it has to use intuition like a human player would. What it felt would likely be a good play
To do this, AlphaGo uses something called a neural network. A neural network is an algorithm that tries
to mimic how the brain works, roughly. You have a bunch of neurons that are connected to each other in layers
you have an input layer, middle layers, and an output layer. Each neuron performs some preset calculation
on the data and then outputs the result to all the connected neurons. This process continues until the
data goes all the way from the input layer to the output layer. So if you input photos of Trump
which really just breaks down to a bunch of 1s and 0s if you think about it like all data.
and feed it into the input layer what its doing is recording commonalities across all the photos.
This is called training in machine learning. So given enough Trump photos eventually it can start recognizing
Trump when it sees a novel photo. Outputting data that means yes this is trump, or no this is not trump
The team created a neural network and input 30 million expert moves from Go until it could output yes this
is an expert move when it saw it. Then they had it play against itself countless times until it got better and
better through trial and error. This is called reinforcement learning. We do it too whenever we
practice shooting hoops or playing an instrument . Practice makes perfect. This gave alphago a sense of
reflection when evaluating a move it could look back on simulated results. But they also wanted to give it a
sense of intuition. So they created another neural network that observed the moves from the simulations
So by combining these 2 networks together, AlphaGo was able to give an estimate of how good a move is by
using a mixture of reflection and intuition. So in a live game alphago uses this move evaluator on a bunch of
possible moves before deciding on the best one and playing it. Its not a full on brute force search but a more
educated and smaller search. Its called a Monte Carlo Tree Search. So cool! The second reason is that this took
1 year instead of 10 years to build. Leading AI experts thought it would take a decade to build a machine
capable of beating the best human player in the world at Go. It only took one year. This is just another sign of the
exponential progress of technology. Think about all the trends in computing that this upholds. Moore's law
Moore's law states that computing power will double every 2 years. The law of accelerating returns by Director
of Engineering at Google Ray Kurzweil states that technological progress in general is exponential, not
linear. 80% of the world's data was created in the last year. And we are all creating off of each other's data at
and exponential rate. The third reason is that this created a new field; AI psychology. In the second game
against Lee Seedol. Alpha played a move no human has ever played before. Move 37. That move represents the
promise of AI. When AlphaGo played it, Lee Sedol was completely baffled. Fan Hui, the other Go master said
its not a human move, I've never seen a human play this move before. and later kept calling it 'beautiful,
so beautiful' AlphaGo thinks better than the best of our species at this task. Even the creators don't understand
how it happened. Thats the beauty of machine learning. Programmers don't code every single rule, they give
it the building blocks to learn by itself and unleash it on massive amounts of data.
We can study AlphaGo and learn new ways of thinking.
The fourth reason is that this technology hasn't yet been applied to other fields. Think about the recent
breakthroughs in quantum computing. Google proved first of all that a quantum computer was possible
and second of all that it solved a specific algorithm 100 million times faster than a classical computer.
Now think of how smart AlphaGo would be if it ran on a quantum computer. Robotics, genetics, physics, climate
change. Economics. This is just the beginning of new breakthrough discoveries in these fields.
Scientists have tons of data that no human could possible sift through. CERN probably has a new particle
somewhere in its dataset. We just don't have the intelligence necessary to sift through the noise and find
the meaningful bit. AlphaGo and the promise of AI is going to help us solve some of the world's biggest
problems. And we should all keep a very close eye on this space. For more info about AlphaGo or AI in general
check out the links in the description below. And as always, thanks for watching.