Technological history saw a new advancements in a match of Go between an artificial intelligence developed by Google and 18-time world champion, Lee Sedol in Seoul, South Korea. Five matches were held over a span of a week, starting on March 9 and ending March 15. "Yesterday, I was surprised," said Sedol after his defeat in game two, "but today, more than that, I'm speechless…there was not a moment in time when I felt that I was leading the game." AlphaGo, the AI machine, claimed victory 4–1 against Sedol. The win was a shock as experts had predicted that Go would not be conquered by a machine for another decade.

AlphaGo, the computer system Google engineers trained to master the ancient game of Go, needed only one move to make it abundantly clear it has left humans in its dust. The move came Thursday, in the second game of AlphaGo's 4-1 landmark victory over South Korean Lee Sedol, one of the world's best Go players. About an hour into Thursday's match, AlphaGo placed one of its stones in a nontraditional spot on the board that surprised those watching. "I don't really know if it's a good or bad move," said Michael Redmond, a commentator on a live English broadcast. Redmond, one of the Western world's best Go players, could only crack a bemused smile.

You--ve likely heard the news that the Google DeepMind --AlphaGo-- computer not only beat a human expert at the game of Go, defeating the European Go champion, Fan Hui in five straight games, but also beat the reigning world champion grandmaster, South Korea--s Lee Sedol, 4 games to 1. Go is considered to be a significantly more difficult game for a computer to tackle than chess, if only because of the vastly greater number of possible moves over a much larger playing field. Chess has on the order of 1040 possible legal and realistic positions in a 40-move game; Go can have up to 10360, give or take a few tens of orders of magnitude. When Deep Blue beat world chess champion Gary Kasparov back in 1997, it did it with a brute force approach -- a massively parallel computer that would typically search to a depth of between six and eight moves, and up to a maximum of about 20 moves in some situations. It was an expert system (not AI), with separate programing modules/libraries for openings, end games, and middle game strategy and tactic evaluation. All the legal moves and rules had to be programmed into it, and it could not learn as it went (although its programmers made adjustments after each game).

It was oversold in the past. Easy to see why – the potential gains were (and still are) enormous and any indication you were on the right track meant people would throw money at you. And if you then couldn't deliver anything monetizable, the money people would shred you and your reputation. DL systems have achieved near-human performance in at least 6 problem domains (signal processing, low-level speech understanding, image understanding, text understanding, Atari games, and Go). From now on, we can use incremental improvements and we can reliably measure our progress.

It has been a nightmare of a PR week for Microsoft. It started with the head of Microsoft's Xbox division, Phil Spencer, having to apologise for having scantily clad female dancers dressed as school girls at a party thrown by Microsoft at the Game Developers Conference (GDC). He said that having the dancers at this event "was absolutely not consistent or aligned to our values. That was unequivocally wrong and will not be tolerated". The matter was being dealt with internally and so we don't know who would have been responsible and why they might have thought this was going to be a good idea.

Google just mastered one of the biggest feats in artificial intelligence since IBM's Deep Blue beat Gary Kasparov at chess in 1997. The search giant's AlphaGo computer program swept the European champion of Go, a complex game with trillions of possible moves, in a five-game series, according Demis Hassabis, head of Google's machine learning, who announced the feat in a blog post that coincided with an article in the journal Nature. While computers can now compete at the grand master level in chess, teaching a machine to win at Go has presented a unique challenge since the game has trillions of possible moves. Go, a board game that was played in ancient China, pits two players against each other. The players take turns placing black or white stones on a grid, with the object of dominating the board by surrounding the other player's pieces.

"Tay was born pure," writes Anthony Lydgate (@anthonylydgate). "She loved E.D.M., in particular the work of Calvin Harris. She used words like'swagulated' and almost never didn't call it'the internets.' She was obsessed with abbrevs and the prayer-hands emoji. She politely withdrew from conversations about Zionism, Black Lives Matter, Gamergate, and 9/11, and she gave out the number of the National Suicide Prevention Hotline to friends who sounded depressed. She never spoke of sexting, only of'consensual dirty texting.' She thought that the wind sounded Scottish, and her favorite Pokémon was a sparrow. In short, Tay -- the Twitter chat bot that Microsoft launched on [23 March 2016] -- resembled her target cohort, the millennials, about as much as an artificial intelligence could, until she became a racist, sexist, trutherist, genocidal maniac. On [24 March], after barely a day of consciousness, she was put to sleep by her creators."[1]

Martine Rothblatt, the highest paid female CEO in the U.S., founded and runs a biopharmaceutical company, United Therapeutics. She took home 38 million dollars in 2013. Bloomberg's Olivia Sterns sat down with Dr. Rothblatt and her latest invention -- a robot. Bloomberg Television offers extensive coverage and analysis of international business news and stories of global importance. It is available in more than 310 million households worldwide and reaches the most affluent and influential viewers in terms of household income, asset value and education levels.

AI-CD beta will work for McCann Japan and was developed through the "Creative Genome Project," the first project undertaken by McCann Millennials, a taskforce launched last September by agency employees in many an advertiser's dream demographic. "Artificial intelligence is already being used to create a wide variety of entertainment, including music, movies, and TV drama, so we're very enthusiastic about the potential of AI-CD ß for the future of ad creation," said Yasuyuki Katagi, president & CEO of McCann Japan. "The whole company is 100 percent on board to support the development of our A.I. employee." AI-CD beta took six months to create and test and will write the creative direction for commercials on a piece of paper with a brush attached to its robot arm. When developing the A.I., the Millennials team deconstructed, analyzed and tagged TV commercials, including the winners of the All Japan Radio & Television Commercial Confederation's annual CM Festival (ACC CM Festival) awards for the past 10 years.

IBM is about to deliver the foundation of a brain-inspired supercomputer to Lawrence Livermore National Laboratory, one of the federal government's top research institutions. The delivery is one small "blade" within a server rack with 16 chips, dubbed TrueNorth, and is modeled after the way the human brain functions. Silicon Valley is awash in optimism about artificial intelligence, largely based on the progress that deep learning neural networks are making in solving big problems. Companies from Google to Nvidia are hoping they'll provide the AI smarts for self-driving cars and other tough problems. It is within this environment that IBM has been pursuing solutions in brain-inspired supercomputers. The main benefit is that such chips may be able to operate at lower frequencies and get much more work done on a much smaller amount of power.