Terrifying season’s greetings from our future robot overlords and their makers
By Rachel Feltman December 23, 2015
Boston Dynamics [owned, of course, by Google ( http://www.bostondynamics.com/bd_about.html )] wants you to have a happy holiday. Boston Dynamics wants you to meet their robots. Boston Dynamics doesn't care if you never sleep again.
Welcome to the future. We've just met the robotic soldiers fighting the war on Christmas.
Did Boston Dynamics realize that their holiday greeting was, um, a little off-putting? Probably. They probably know that. Assuming there are still humans in charge over there. But we have to applaud the team on creating a video that will be spread far and wide and inspire fear in the hearts of many while also spreading the good news about the latest innovations in robotics.
Go is an ancient Chinese board game, often viewed as the game computers could never play. Now researchers from Google-owned company DeepMind have proven the naysayers wrong, creating an artificial intelligence - called AlphaGo – which has beaten a professional Go player for the first time. In this Nature Video, we go behind the scenes to learn about the game, the programme and what this means for the future of AI.
related source article: Google AI algorithm masters ancient game of Go Deep-learning software defeats human professional for first time. 27 January 2016 http://www.nature.com/news/google-ai-algorithm-masters-ancient-game-of-go-1.19234 [with non-YouTube version of this YouTube and separate audio embedded, links to further related articles, and comments]
Alphabet Program Beats the European Human Go Champion
Demis Hassabis, a former child chess prodigy, is vice president of engineering at Alphabet’s DeepMind and leads Alphabet’s general A.I. efforts. Credit Alphabet
By John Markoff January 27, 2016 2:28 pm
Artificial intelligence researchers are closing in on a new benchmark for comparing the human mind and a machine. On Wednesday, DeepMind, a research organization that operates under the umbrella of Alphabet, reported that a program combining two separate algorithms had soundly defeated a high-ranking professional Go player in a series of five matches.
Go is seen as a good test for artificial intelligence researchers because it is more complex than chess, with a far larger range of possible positions. This makes strategy and reasoning in the game more challenging.
Go is played with round black and white stones, and two players alternately place pieces on a square grid with the goal of occupying the most territory. Until recently, software programs had not been able to do better than beat amateur Go players. In the Nature paper, engineers at DeepMind described a program, AlphaGo, that had achieved a 99.8 percent winning rate against other Go programs. It also swept five games from the European Go champion, Fan Hui [ http://www.nature.com/news/go-players-react-to-computer-defeat-1.19255 ].
The match between the AlphaGo program and Fan Hui was in October, and the DeepMind program has continued to train since then, said Demis Hassabis, a researcher who founded DeepMind Technologies, which was acquired by Google in 2014. Google changed its name to Alphabet last year, though the company’s traditional ad-based businesses still operate under the Google label. “The machine has continued to get better. We haven’t hit any kind of ceiling yet on performance,” he said.
The Alphabet approach relies on the newest so-called deep learning approach combined with a more traditional type of algorithm known as a Monte Carlo, which is designed to exhaustively explore large numbers of possible combinations of moves. The researchers said they had also trained their program using input from expert human Go players.
The research and the game have created a rivalry among the public relations departments of companies like Alphabet, Microsoft and Facebook.
The day before the Alphabet paper was published, Facebook republished an earlier paper the company had posted on the arXiv.org website. At the same time, Facebook issued blog posts [ https://www.facebook.com/yann.lecun/posts/10153340479982143 ] from Yann LeCun, one of its artificial intelligence researchers, and one from the company’s chief executive, Mark Zuckerberg.
The statement [ https://www.facebook.com/zuck/videos/vb.4/10102619979032811/?type=2&theater ] by Mr. Zuckerberg resulted in a swift response from one Facebook user that may express a deeper human concern than the narrow results of the research: “Why don’t you leave that ancient game alone and let it be without any artificial players? Do we really need an A.I. in everything?” wrote Konstantinos Karakasidis.
Wednesday morning, Alphabet stated that, in an effort to reprise the winning IBM Deep Blue chess playing program that defeated the chess champion Garry Kasparov in 1996, Alphabet will match its AlphaGo program against Lee Sedol, the current Go champion, for a five-game match in March.
There will be a $1 million prize for the winner, and Mr. Hassabis said that Alphabet would donate the prize to charity if AlphaGo won. The match will be streamed live on YouTube.
Mr. Hassabis, who is a skilled chess player and has been a professional gamer as well, said that Go was a beautiful game, but that “building an A.I. is also a human endeavor and a kind of ingenious one, too. The reason games are used as a testing ground is that they’re kind of like a microcosm of the real world.”
A computer program that can outplay humans in the abstract game of Go will redefine our relationship with machines.
Editorial 27 January 2016
Napoleon had it and so did Charles Darwin. Tennis champion Roger Federer has it in spades. The dictionary defines intuition as knowledge obtained without conscious reasoning. It is decision-making based on apparently instinctual responses; thinking without thinking.
Intuition is a very human skill, or so we like to think. Or, more accurately, so we liked to think. In what could prove to be a landmark moment for artificial intelligence, scientists announce this week that they have created an intuitive computer. The machine acts according to its programming, but it also chooses what to do on the basis of something — knowledge, experience or a combination of the two — that its programmers cannot predict or fully explain. And, in the limited tests carried out so far, the computer has proved that it can make these intuitive decisions much more effectively than the most skilled humans can. The machines are not just on the rise, they have nudged ahead.
Experts in ethics, computer science and artificial intelligence routinely debate whether clever machines in the future will use their powers for good or evil. This latest example of digital discovery puts neural networks to work on a problem that is almost as old: how to win at the board game Go.
Outside business-management seminars, Go is not well known in the West, but it is older, more complex and harder to master than chess. Yet it is simpler to learn and play: two players take it in turns to place black or white counters on a grid. When a counter (called a stone) is surrounded by rivals, it is removed from the board. Winning — like so much in life and war — is about controlling the most territory. The game is wildly popular across countries in east Asia, and players from Japan, China and South Korea routinely compete in televised professional tournaments.
Computers mastered chess two decades ago, when IBM’s Deep Blue machine won against then-world-champion Garry Kasparov in 1997, but Go was thought to be safe from artificial conquest. That is partly because all of the possible moves in Go, as well as the resulting combinations of stones on the board, are much too numerous for any computer to crunch through and compare to select one manoeuvre. (The same goes for chess, but the diversity in the value of chess pieces enables some short cuts.) In Go, all stones are worth the same and their influences can be felt through vast distances across the board.
AlphaGo cannot explain how it chooses its moves, but its programmers are more open than Deep Blue’s in publishing how it is built. Previous Go computer programs explore moves at random, but the new technology relies on a suite of deep neural networks. These were trained to mimic the moves of the best human players, to reward wins and, using a probability distribution, to limit the outcomes for any board position to a single verdict: win or lose. Working together, these machine-learning strategies can massively reduce the number of possible moves the program evaluates and chooses from — in a seemingly intuitive way.
As shown by its results, the moves that AlphaGo selects are invariably correct. But the interplay of its neural networks means that a human can hardly check its working, or verify its decisions before they are followed through. As the use of deep neural network systems spreads into everyday life — they are already used to analyse and recommend financial transactions — it raises an interesting concept for humans and their relationships with machines. The machine becomes an oracle; its pronouncements have to be believed.
When a conventional computer tells an engineer to place a rivet or a weld in a specific place on an aircraft wing, the engineer — if he or she wishes — can lift the machine’s lid and examine the assumptions and calculations inside. That is why the rest of us are happy to fly. Intuitive machines will need more than trust: they will demand faith.
Google apps can now understand and pronounce Australian place names and colloquialisms
Screenshot of Australian voice recognition on Android phone Google's search app now knows about drop bears
Screenshot of Google search app recognising 'when's the next game of footy in Brissy' Google has added Australian colloquialisms to its Android search app, and now understands "When's the next game of footy in Brissy?"
Posted January 28, 2016 21:31:39
Google has released a version of Geoff Mack's geographical song I've Been Everywhere to demonstrate that their mobile search app can now understand and pronounce Australian place names and colloquialisms.
The song, written in 1959, has four verses listing Australian place names including Murwillumbah, Cunnamulla, Tuggerawong and Indooroopilly.
Google's update, released for both the search app and maps, follows after an Australian accent was introduced to the app's voice in the past week.
"People are starting to talk to their mobile devices more regularly - in fact, mobile voice searches have more than doubled in the past year alone," a Google spokesperson said.
"We wanted to make sure that Aussies were hearing an Australian voice speak back to them."
In order to hear the Australian accent, the language setting must be set to "English [Australia]".
Google said they worked with a team of Australian linguists to help get the Australian pronunciation and intonation just right.
Google's voice recognition has also added several Australian colloquialisms, including footy, servo, Brissy, and drop bear as well as business names Maccas and Woolies.
In testing by the ABC, the app successfully recognised all these terms but did not have an answer to "what is the best protection against drop bears?"
The search app on rival Apple's iPhone proved less reliable in interpreting colloquialisms and was unable to answer "When's the next game of footy in Brissy?"
American company Google, which began as an internet search engine and now manages a suite of online and mobile software including the Android operating system for smartphones, has a long history in Australia.
In 2004, they purchased a mapping company called Where 2 Technologies, which had been developed by Sydney-based brothers Lars and Jens Rasmussen, who has moved from California's Silicon Valley.
The brothers joined Google but stayed in Australia to turn their software into Google Maps.
In 2010, the Rasmussens were named New South Wales' Entrepreneurs of the Year in the information and communications technology (ICT) field.
Quantum physics has never made much sense. Einstein never liked the idea that separated particles could influence each other - ‘spooky action at a distance’ - but a new variation on a famous experiment may have proved its existence once and for all. Nature Video dives into a world where quantum entanglement and quantum superposition seem to defy all laws of common sense.
Does quantum entanglement make faster-than-light communication possible?
First, I know this video is not easy to understand. Thank you for taking the time to attempt to understand it. I've been working on this for over six months over which time my understanding has improved. Quantum entanglement and spooky action at a distance are still debated by professors of quantum physics (I know because I discussed this topic with two of them).
Does hidden information (called hidden variables by physicists) exist? If it does, the experiment violating Bell inequalities indicates that hidden variables must update faster than light - they would be considered 'non-local'. On the other hand if you don't consider the spins before you make the measurement then you could simply say hidden variables don't exist and whenever you measure spins in the same direction you always get opposite results, which makes sense since angular momentum must be conserved in the universe.
Everyone agrees that quantum entanglement does not allow information to be transmitted faster that light. There is no action either detector operator could take to signal the other one - regardless of the choice of measurement direction, the measured spins are random with 50/50 probability of up/down.
All creatures great and small: Elizabeth Blackburn
Published on Sep 30, 2015 by nature video
From jellyfish to ants, all life is beautiful in the eyes of Elizabeth Blackburn, co-winner of the 2009 Nobel Prize in physiology or medicine. She talks about her fascination with living things and the discovery of telomerase and telomeres.
A sponsor message from Mars, Incorporated – partner of the Lindau Nobel Laureate Meetings – follows the credits.
When you’re a plant, it’s not easy to make sure your seeds are spread far and wide and safely buried. Unless you can trick a dung beetle into doing it for you…
What can we learn from chimps swinging their hips? In this Nature Video, we investigate the walking style of our primate cousins, and see what they can teach us about our ambling ancestors.
Archaeologists uncover the remains of a community brutally murdered, ten thousand years ago. The bones of men, women and children have emerged from the bed of an ancient lake, providing evidence of a violent massacre in prehistoric Kenya.
Special Thanks to: Prof Stephen Bartlett, Prof Phil Moriarty, Prof Andrea Morello, Prof Tim Bedding, Prof Michio Kaku, A/Prof Alex Argyros, Henry Reich, Vanessa Hill, Dianna Cowern, George Ruiz and Mystery Cat. Views expressed in this video are not necessarily those of the amazing experts listed above but their advice was invaluable in making this video.
If God has a plan, then why would you pray for anything/anyone?
Royalty-free music used: "Moon Waltz" by Zero Project "Box up" by Hlamidas "Bomb Alert" by Gregoire Lourme "Evacuation" by Gregoire Lourme "A Tribute" by Gregoire Lourme "S1M3 2014" by Daniel Bautista
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