It’s happening for the first time in history, we’re seeing the successful development and demonstration of general purpose AI. Its name is AlphaGo made by Google’s Deepmind division. The AlphaGo AI algorithm beat a human at the world’s hardest game. This is a historic moment in computer science and artificial intelligence.
So, what exactly is Google Deepmind?
Where did it come from and what can the company’s artificial intelligence actually do?
Let’s find out, a computer program beat a human brain in the ancient Chinese board game “Go”. It is a triumph for artificial intelligence program equipped with human intuition to win over a human. In the ancient board game Go has sparked intrigue and in some cases concern, it shows that a machine has approximated human intuition and outsmarted the best human brain in the game. It’s something that scientists hadn’t expected to happen for at least another decade and it’s a giant leap for artificial intelligence showing that machines can learn on their own.
Right now, this was the WOW moment a computer called alpha go beat a master of the ancient Chinese game Go. It’s not the first time a Grand Master’s been humbled by a machine but what makes AlphaGo different is that it’s the first demonstration that machines can truly learn and think in a human way. AlphaGo’s victory shocked experts in the artificial intelligence community.
Many thought such an event was at least a decade away, so, firstly a few questions why is this important and what’s all the fuss?
AlphaGo shows that machines can really learn so well instead of using brute-force to calculate all the moves that can make like previous a is AlphaGo used reinforcement learning and neural networks. To mimic the learning process of a human brain, keep in mind that the ancient Chinese game Go has as many more possible moves than chess as there are atoms in the entire universe. So there’s no way of just calculating every possible move on the board that’s practically impossible. For this reason, Go game is the holy grail of AI and learning to do such a task from scratch is a huge feat.
Further to this, Deepmind’s creators say that the algorithm can learn many more things without alteration or guidance, in other words, the AI is general-purpose.
We always used to talk about what if we could eventually crack Go and have a program that could be the world champion then we must have invented some generic general-purpose algorithm. So maybe we’re on the cusp of all of them.
If you ask a great Go player, why they played a particular move? Sometimes they’ll just tell you it felt right. So you can the one way who can think of it because the Go is a much more intuitive game whereas chess is a much more logic based game.
So, what is google Deepmind?
Deepmind is a British artificial intelligence company that was founded in September of 2010 as Deepmind technologies. It was renamed when it was acquired by Google in 2014 for 500million dollars. Interestingly enough, this was just after Facebook had just finished negotiations with them in 2013 and another fun fact Elon Musk is actually an investor in the company just to keep an eye on them.
Deepmind received the company of the Year award by the Cambridge computer laboratory in 2014.
So, where to Deepmind come from?
Deepmind was the startup, co-founded by Demis Hassabis in 2010. Dennis was a child genius and went from being a chess prodigy and reaching the master level at age 13. He became the lead programmer of Lionhead Studios for groundbreaking games such as Black and White. After this, he went on to start his own gaming studio before leaving to complete some extra studies at the University College of London. This is where he met the future co-founders of Deepmind in 2010.
So, what is the goal of Deepmind?
According to the website, that goal of Deepmind is to solve intelligence. They are trying to achieve this by combining the best techniques from machine learning and systems neuroscience to build powerful general-purpose learning algorithms. In other words, they want to formalize intelligence to find out what it is and how it works.
The endgame is not just to implement this into machines but also understand the human brain.
Deepmind is attempting to distill intelligence into an algorithm to construct or may prove to be the best path to understanding some of the enduring mysteries of our minds.The key here is that AI machine is general-purpose and it is very important.
So, how does this all work?
The AI from Deepmind uses a technique called deep reinforcement learning which makes it very different from other AIs such as IBM’s Watson or the primitives Siri or Google. the things which I just mentioned were only developed for a predefined purpose and only function within their scope.
- Deepmind claims that their system is not pre-programmed and it learns from experience using only raw pixels as data input.
- So, Deepmind starts off training AlphaGo is by showing it a hundred thousand games that strong amateurs played which they’ve downloaded from the Internet. They initially get AlphaGo to mimic the human player but ultimately they would like AlphaGo to be stronger than human amateurs and compete with the top professionals.
- So, the way we do that is the first version. Deepmind researchers let AlphaGo mimic human play. Later, they allow it to play itself 30 million times on servers and using reinforcement learning.
- AlphaGo is the system learns to improve itself incrementally by avoiding its errors and improving its win rate against older versions of itself.
Technically, the reinforcement that Deepmind uses is model-free, meaning, it doesn’t need a structure or set of rules to learn according to MIT’s take on the Google algorithm.
Learning how to play break out and remember
The machine didn’t have any fore-knowledge as to what task it was going to complete. The AI had to figure out how to do everything only from its own experience. Deepmind is currently playing games from the 1970s and 80s to learn more strategies for human but work is currently being done on more complex 3D games such as doom which appeared in the early 90s.
Would the general-purpose AI be useful?
In a number of interviews, Denis has talked about numerous applications of general purpose AI in healthcare, smartphone assistance, and robotics. Some other applications of such AI include online customer service, computer vision, general computer science, news publishing, and writing.
General purpose AI actually could be huge, it can be thought of as another emerging science much like Newtonian physics which laid the groundwork for technologies such as rockets. A science founded on general-purpose digital neural networks that use reinforcement learning could lay the groundwork for unimaginable things in the near future.
Should we be worried by AI?
In the thousands of years of meaningful civilization, our modern existence is an anomaly. we’ve overcome the limits of nature with technology that helps us facilitate such a lifestyle. But artificial intelligence is different, the reason being AI is the first thing humans have created that tends to function in a way that we can’t predict. So should we worry?
My belief is that the fear of the unknown is mostly what drives the hysteria that arises from AI. There’s not enough time to go through all the theories of how things could turn out. But it’s an interesting topic within itself.
Stephen Hawking and Elon Musk have both shown their reservations towards AI but others like Paul Ellen co-founder of Microsoft have a different view.
If you can forget about the movie Terminator for a second, there is a possibility that AI could be man’s greatest aide fixing fundamental problems on our planet and allowing us to have technology and infrastructure that could have otherwise taken us centuries. But on the other hand, there is a possibility that AI could be malicious and would outwit us.
Well, at this stage we really just don’t know yet whether AI (Artificial Intelligence) will be good or bad for the world.