Elon Musk's artificial intelligence company created virtual robots that can sumo wrestle and play soccer. Following is a transcript of the video. These AI robots are getting physical. They may look goofy but they're smarter than you think. OpenAI's bots can teach themselves how to sumo wrestle and play soccer.

Artificial intelligence has historically over-promised and under-delivered. That routine leads to spurts of what those in the field call "hype"--outsized excitement about the potential of a core technology--followed after a few years and several million (or billion) dollars by crashing disappointment. In the end, we still don't have the flying cars or realistic robot dogs we were promised. But DeepMind's AlphaGo, a star pupil in a time we'll likely look back on as a golden age of AI research, has made a habit of blowing away experts' notions of what's possible. When DeepMind announced that the AI system could play Go on a professional level, masters of the game said it was too complex for any machine.

It's time to add "AI research" to the list of things that machines can do better than humans. Google's Alpha Go, the computer that beat the world's greatest human go player, just lost to a version of itself that's never had a single human lesson. Google is making progress in the field of machine learning at a startling rate. The company's AutoML recently dropped jaws with its ability to self-replicate, and DeepMind is now able to teach itself better than the humans who created it can. DeepMind is the machine behind both versions of Alpha Go, with the latest evolution dubbed Alpha Go Zero -- which sounds like the prequel to a manga.

It's been a long time worry that when AI gains a certain level of autonomy it will see no use for humans or even perceive them as a threat. A new study by Google's DeepMind lab may or may not ease those fears. There are two unmistakable sides to the debate concerning the future of artificial intelligence. The researchers at DeepMind have been working with two games to test whether neural networks are more likely to understand motivations to compete or cooperate. They hope that this research could lead to AI being better at working with other AI in situations that contain imperfect information.

It happened with Chess and Go, and it finally happened with eSports. Elon Musk-backed Artificial Intelligence company "OpenAI" just used a bot to wallop the best DOTA2 players in the world. To be honest, it wasn't even close. Instead of trying to program the perfect bot, OpenAI just created a bot that learned through trial and error. Over the course of playing thousands of games against itself, the bot kept the behaviors that lead to victory and shed the ones that got it killed.

Google has developed a computer program that teaches itself. The company's AI division, DeepMind, has unveiled AlphaGo Zero, an extremely advanced system that managed to accumulate thousands of years of human knowledge within days. DeepMind says it's the most powerful program it has created, because it isn't "constrained by the limits of human knowledge". AlphaGo Zero is the latest evolution of AlphaGo, the first computer program to ever defeat a world champion at the ancient Chinese game of Go. Unlike previous versions of AlphaGo, however, Zero was only provided with the rules of the game. It had to learn how to play all by itself, whereas the others were trained using data from thousands of games played by humans.

We've written before about how Google is one of the most prominent tech companies leading the way when it comes to the development of artificial intelligence. As each month passes, its AI division, DeepMind, continues to reveal increasingly advanced AI capabilities, especially when it comes to AlphaGo. This particular AI is most well-known for mastering the ancient Chinese game of Go…and subsequently defeating 18-time world champion Lee Se-dol, which happened just last year. Since then, DeepMind has started adding imagination to its AI, and they also used gaming to teach the AI how to better manage tasks. AlphaGo even went on to defeat another top go player, Ke Jie, once again showing off its (potentially) unlimited potential to learn.

LONDON – DeepMind, the London-based artificial intelligence company owned by Alphabet Inc., is planning to let its software learn how to fold proteins, an important problem for drug discovery. The company is best known for AlphaGo, software that beat the world's top human players at the ancient strategy game go. But now it has created software based on a different design, called AlphaGo Zero, which can beat all previous versions of AlphaGo. Unlike earlier versions, AlphaGo Zero learned completely from scratch, with no knowledge of how humans play the game, DeepMind chief executive Demis Hassabis said at a news conference held ahead of the publication of the new research in the scientific journal Nature on Wednesday. DeepMind's latest project shows how its studies could be of increasing practical importance to its parent company.

Artificial intelligence systems are starting to think "like humans" rather than just calculating potential options, but might their full exploitation trigger some liability risks? As anticipated, IoTItaly, the Italian Association on the Internet of Things of which I am one of the founders, ran an event in collaboration with STMicroelectronics named "Creativity and technology at the time of Industry 4.0" on 30 May 2017. I found fascinating the video below that tries to explain Google's DeepMind system. As mentioned in the video, the "symbolic" event which is considered the moment when machines started to be "intuitive" is the victory of the AlphaGo artificial intelligence system against a master of the ancient Chinese game Go. DeepMind is the evolution of such approach.

Google's AI subsidiary DeepMind is getting serious about ethics. The UK-based company, which Google bought in 2014, today announced the formation of a new research group dedicated to the thorniest issues in artificial intelligence. These include the problems of managing AI bias; the coming economic impact of automation; and the need to ensure that any intelligent systems we develop share our ethical and moral values. DeepMind Ethics & Society (or DMES, as the new team has been christened) will publish research on these topics and others starting early 2018. The group has eight full-time staffers at the moment, but DeepMind wants to grow this to around 25 in a year's time.