The biggest hardware and software arrival since the iPad in 2010 has been Amazon's Echo voice-controlled intelligent speaker, powered by its Alexa software assistant. But just because you're not seeing amazing new consumer tech products on Amazon, in the app stores, or at the Apple Store or Best Buy, that doesn't mean the tech revolution is stuck, or stopped. They are: artificial intelligence / machine learning, augmented reality, virtual reality, robotics and drones, smart homes, self-driving cars, and digital health / wearables. Google has changed its entire corporate mission to be "AI first" and, with Google Home and Google Assistant, to perform tasks via voice commands and eventually hold real, unstructured conversations.
To figure out whether random AI can help people coordinate, Hirokazu Shirado, a sociologist and systems engineer, and Nicholas Christakis, a sociologist and physician, both at Yale University, asked volunteers to play a simple online game. In some networks, every 1.5 seconds the bots picked whatever color differed from the greatest number of neighbors--generally a good strategy among people playing the game. The noise level of bots influenced the noise level in people--even those several nodes away, suggesting a ripple effect. If you see a neighbor (bot or human) change color frequently, you might decide to do so, too.
There are 2 billion active Android devices, 800 million Google Drive users, and 500 million Google photos users who upload 1.2 billion photos every day. Whenever I spend time with a team and think about neural nets building neural nets, it reminds me of one of my favorite movies, Inception. Fei Fei Li, Chief Scientist of Google Cloud and AI and head of Stanford's AI Lab, had a number of announcements that underscore the breadth of Alphabet's aspiration to become the world's AI platform. It's built specifically to support Google's open source machine learning language, Tensorflow.
In this series, we will discuss the deep learning technology, available frameworks/tools, and how to scale deep learning using big data architecture. Neural Networks–or as they are more appropriately called, Artificial Neural Networks (ANN)–were invented in 1940 by McCulloch, Pitts, and Hebbian. The difference between shallow neural networks vs. deep neural networks is the number of hidden layers (i.e., in shallow neural networks, the number of hidden layers are few, while in deep neural networks, it is high). Recently, TensorFrames ( i.e., TensorFlow DataFrames) was proposed, a seemingly great workaround, but in its current state, it is still in development mode, and migrating current TensorFlow projects to TensorFrames framework demands significant efforts.
AlphaGo has again defeated Ke Jie, the world's number one Go player, in their second game, meaning the AI has secured victory in the three-part match. "For the first 100 moves it was the closest we've ever seen anyone play against the Master version of AlphaGo," DeepMind CEO Demis Hassabis said in the post-game press conference. Until AlphaGo beat Lee, solving the ancient Chinese board game of Go had long been a north star for computer scientists due to its unparalleled complexity and huge number of potential moves. The final game will be on Saturday, while Friday will see AlphaGo further put to the test in two stipulation matches; one where it acts as a teammate to two Chinese pros playing each other, and another where it takes on five Chinese pros all at once.
"Maybe that's the weakest part of human beings," he added. AlphaGo's victory on Thursday simply reinforced the progress and power of artificial intelligence to handle specific but highly complex tasks. Because of the sheer number of possible moves in Go, computer scientists thought until recently that it would be a decade before a machine could play better than a human master. "For human beings," he added, "our understanding of this game is only very limited."
Google's Go-playing AI has won its second game against the world's best player of the ancient Asian board game, Chinese 19-year-old Ke Jie, taking the three-game match in the process. "Ke Jie pushed AlphaGo right to the limit," Hassabis added on Twitter. As well as the third game between the pair, held on Saturday, Google is also putting AlphaGo through a pair of exhibition matches designed to test the limits of its performance: in one, the AI will be acting as team-mate to a pair of professionals playing against each other, taking every other turn in an effort to see how the AI and humans adapt to each other's style of play; in the other, it will take on five professionals working in concert to try and outfox it. Even though the matches are being held in China, Chinese residents won't be able to watch them live.
Google's AlphaGo AI has won over world champion and number one ranked Go player Ke Jie for the second time in a row. SEE ALSO: Google's AlphaGo beats world's best Go player According to DeepMind founder and CEO Demis Hassabis, the AI assessed that Ke Jie played perfectly at some points in the game. According to #AlphaGo evaluations Ke Jie is playing perfectly at the moment. AlphaGo made headlines when it won against legendary Go player and multiple world champion Lee Sedol (currently ranked number 7) in 2016, with a score of 4:1.
A Go match between the world's top player, Ke Jie, and Google's AlphaGo that took place this week was censored by authorities, reports Quartz. Three journalists have reported receiving verbal directives barring their news organisations from broadcasting the match -- as well as the Go and AI summit held in Wuzhen, east China. One journalist reported being barred from even mentioning Google's name while reporting on the event, while another said that while they could mention Google, they were barred from writing about Google's products. A leaked copy of a government directive was also posted on California-based China Digital Times, a website that monitors censorship in China.