What’s up guys, my name is Selim Chehimi and today
we’re going to discuss how the neuroscientist inspired AI company Deep Mind is going to solve Artificial Intelligence.
Demis Hassabis is the co-founder and CEO of Deep Mind which has been acquired by Google in
2014. Deep Mind is often described as a kind of Apollo program for AI because it gathers the best
scientists and engineers to make quick progress in this domain. Let’s look at how they are planning to solve intelligence.
One of the major events in AI was when IBM’s supercomputer Deep Blue beats the world chess champion Gary Kasparov in
1997.
But Deep Blue is a Narrow AI which means it can do only one specific task
so in this case playing chess. It can’t do anything else and from an AI point of view, this is very
frustrating because you wonder where is the intelligence. Most AI Systems today are Narrow AI. Deep Mind wants to create an Artificial
Intelligence that carries out most human professions at least as well as a human. The progress being made by the company are really incredible.
For example, they have created
AlphaGo, the first computer program to defeat the Go world champion Lee Sedol four games to one. In the game of Go, there are more possible moves
than atoms in the entire universe. In other words, there is no way of calculating all possible moves
so Alpha Go needs some sort of human intuition. As you can imagine, AlphaGo’s success has shocked the Go Community
and is considered to be the most significant in AI due to the complexity of Go.
But, again, AlphaGo is a Narrow AI: all it can do is playing Go.
Deep Mind wants to go beyond that Narrow AI level so they came up with a new technique called Deep Reinforcement Learning.
It combines two AI techniques: Deep Learning and Reinforcement Learning.
Deep Learning is used to allow the AI to perceive the world around them through neural networks and
Reinforcement Learning consists of selecting the right action from the sets of available options that will best get the AI towards its goal.
Deep Mind is already using this technique in virtual environments – they use computer games for developing and testing out AI
algorithms. Virtual environments and computer games are much more efficient to test the capabilities of AI systems than robotics which are slower,
messier and more expensive.
With computer games, it’s much easier because you can have a feedback of the progress of your AI systems with
information like the score etc. Here is a video showing this new technique in action:
Another important aspect of research at DeepMind is systems
neuroscience. The company gets their inspiration not only from mathematics and machine learning but also from how the brain works.
Again, their goal is to solve intelligence and to do that, they want to build a kind of Artificial Hippocampus
which is responsible for memory, imagination, attention, navigation and planning.
To Demis Hassabis, “This isn’t about man competing with machines, but rather using them as tools to explore and discover new knowledge together”
Deep Mind is getting closer to solve Artificial Intelligence, once they succeed, they will use it to solve real-world problems like healthcare and climate change.
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