Games

And then, around 2012, mostly due to the advance of computing power within graphic cards, which enable programmers to make massively parallel linear algebra, we had a number of breakthroughs which now mean that computers have become better than humans at pattern recognition. But then came a new technology called'convolutional neural networks', around 2011, which showed incredibly accurate results: error rates lower than 1%. The ones that Tim showed IBM Watson Work Service's natural language processing. One of the fascinating developments of last year was the perfecting of Google Deep Mind's system to such a point that it could beat Lee Sedol, one of the best Go players in the world.

Men spent much more time analysing past games and practising anagrams - which gave them the winning edge in tournaments. 'The National Tournament divides players into six ranked divisions, and males dominate at the highest levels of performance', researchers wrote in the paper published in Psychological Research. 'In 2002, 86 per cent of competitors in the division with the best Scrabble players were male, while in the division with the lowest performance only 31 per cent of competitors were male. Men spent much more time analysing past games and practising anagrams - which gave them the winning edge in tournaments.

It will work in all aspects of health care, energy management, manufacturing, industrial process control, accounting, law, weather and climate prediction, drug discovery, toy design, and entertainment, ranging from responsive, real-time virtual reality to traditional game playing. It takes three major, difficult-to-achieve things: good data, smart analytics, and clear objectives. Smart analytics means having someone identify what patterns the AI system is looking for. For instance, you can't get an AI to assess a satellite photo of a farming region and determine whether the region is suffering from drought unless you can provide the analytical tools to tell it what that looks like.

About 80 players are taking part at the Nottingham Conference Centre, with some travelling from New Zealand, Pakistan and Sierra Leone.

The surprising insight of those tournaments is that the teams with the strongest human / machine partnership dominate even the strongest computer. So if a 7 minute consultation today, involves 6 minutes of activities that will be automated, can we please fight for a system that rewards compassion and other human values that are so desperately needed in the healthcare system and will hardly be replaced by robots or machines. It is time we start actively lead and design our future healthcare systems, so we also have time to redefine the value system healthcare is based on. Bart is involved in leading edge technologies leading the Digital Health Business for IBM DACH, he has been intimate involved as a mentor in the formation and growth of a dozen startups within the healthcare sector.

With the evolution of the gaming industry, programming techniques and processing power, games typically reserved for human beings -- such as checkers, chess, and backgammon -- have become increasingly challenging as single-player games. In an article published in 1950, American mathematician Claude Shannon -- one of the most important names in the History of Computer Science -- estimated that in a typical game of chess there are at least 10¹²⁰ (ten to the power of one hundred and twenty) possibilities for distinct configurations (this became known as the Shannon number). The number of simulations depends on the complexity of the program as well as the computing and storage power of the computer. Between 1996 and 1997, IBM's Deep Blue computer defeated then-world chess champion Garry Kasparov.

But even before Watson competed on Jeopardy!, AI systems also learned games, ranging from tic-tac-toe to chess. You may recall that in 1997, IBM's Deep Blue beat the world's chess champion Garry Kasparov. But teaching an AI system like Watson a game isn't just child's play, says Dr. Gerald Tesauro, principal research staff member at IBM's TJ Watson Research Center and an expert in using AI to play games. So playing games can also help AI systems learn strategy, negotiation, and, in particular, predicting what humans will do – all of which can be applied to business problems as well.

Garry Kasparov and DeepMind's CEO Demis Hassabis discuss Garry's new book "Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins ", his chess match with IBM Deep Blue and his thoughts on the future of AI in the world of chess. In May 1997, the world watched as Garry Kasparov, the greatest chess player in the world, was defeated for the first time by the IBM supercomputer Deep Blue. During the twenty years since playing Deep Blue, he's played both with and against machines, learning a great deal about our vital relationship with our most remarkable creations. It means you have to change certain habits and certain customs and what was important for me that's what I learned from my mother is that my game was not just about win it was also about making a difference and that's what helped me to make a transition later on in my life from playing chess being number one chess player for 20 years two other things that I'm doing now not pretending that I could be number one and repeat my outstanding achievements in the game of chess but still recognizing that I'm quite useful.

Garry Kasparov and DeepMind's CEO Demis Hassabis discuss Garry's new book "Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins ", his chess match with IBM Deep Blue and his thoughts on the future of AI in the world of chess. In May 1997, the world watched as Garry Kasparov, the greatest chess player in the world, was defeated for the first time by the IBM supercomputer Deep Blue. During the twenty years since playing Deep Blue, he's played both with and against machines, learning a great deal about our vital relationship with our most remarkable creations. It means you have to change certain habits and certain customs and what was important for me that's what I learned from my mother is that my game was not just about win it was also about making a difference and that's what helped me to make a transition later on in my life from playing chess being number one chess player for 20 years two other things that I'm doing now not pretending that I could be number one and repeat my outstanding achievements in the game of chess but still recognizing that I'm quite useful.

Garry Kasparov and DeepMind's CEO Demis Hassabis discuss Garry's new book "Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins ", his chess match with IBM Deep Blue and his thoughts on the future of AI in the world of chess. In May 1997, the world watched as Garry Kasparov, the greatest chess player in the world, was defeated for the first time by the IBM supercomputer Deep Blue. During the twenty years since playing Deep Blue, he's played both with and against machines, learning a great deal about our vital relationship with our most remarkable creations. It means you have to change certain habits and certain customs and what was important for me that's what I learned from my mother is that my game was not just about win it was also about making a difference and that's what helped me to make a transition later on in my life from playing chess being number one chess player for 20 years two other things that I'm doing now not pretending that I could be number one and repeat my outstanding achievements in the game of chess but still recognizing that I'm quite useful.