Computer manufacturer Atos has named its first customer for Bull sequana, a supercomputer design it hopes will reach exaflop levels of performance by 2020. Atos is building the computer for the French Alternative Energies and Atomic Energy Commission (CEA), it said Tuesday. By targeting 2020 for delivery of an exaflop supercomputer, Atos is entering a race in which China and Japan may already have a head-start. An exaflop is a billion billion floating-point operations per second (flops). That's way more than today's fastest machine can manage: China's Tianhe-2 has a maximum performance of 33.9 petaflops (millions of billions of flops), according to the November 2015 edition of the Top500 supercomputer rankings.

To the computer scientist Leslie Valiant, "machine learning" is redundant. In his opinion, a toddler fumbling with a rubber ball and a deep-learning network classifying cat photos are both learning; calling the latter system a "machine" is a distinction without a difference. Valiant, a computer scientist at Harvard University, is hardly the only scientist to assume a fundamental equivalence between the capabilities of brains and computers. But he was one of the first to formalize what that relationship might look like in practice: In 1984, his "probably approximately correct" (PAC) model mathematically defined the conditions under which a mechanistic system could be said to "learn" information. Valiant won the A.M. Turing Award -- often called the Nobel Prize of computing -- for this contribution, which helped spawn the field of computational learning theory. In a 2013 book, also entitled "Probably Approximately Correct," Valiant generalized his PAC learning framework to encompass biological evolution as well.

The simplest answer is a computer software program that is able to intelligently communicate with humans through artificial intelligence. Tech companies like Microsoft are placing big bets on the computer software, which is able to intelligently communicate with humans via AI. Microsoft recently launched its first attempt with a Twitter chatbot named "Tay"; however things didn't go quite according to plan when "Tay" started spewing racist comments to some user's questions. It's just "back to the drawing board," he said recently at the company's developer conference. Microsoft also announced that it will be launching new tools to help developers build their own chatbots into their apps.

Hong Kong's economy is likely to encounter quite serious challenges in the coming two or three years. A study released by the University of Hong Kong predicts the city's economy will grow 1.5 percent this year. I think the real GDP growth rate may be close to zero, or even fall below zero. The situation in the second half may even be worse. Currently, Hong Kong's economy has four pillars: trade and logistics, tourism, finance and professional services.

We've compiled a list of the hottest events and conferences from the world of Data Science and Machine Learning this year that we think you should know about! Image Processing, Computer Vision and Machine Learning based on Optimization and PDE.(Oslo, Norway) 29th August https://ivlopde2016.wordpress.com/

Looking at the performance of IBM shares over the past five years, it is clear that a change in strategy is needed. IBM's share price is down approximately 9% since 2011 compared to a 54% gain in the S&P 500. The goal of this article is to develop a strategy for IBM to leverage the power of IBM Watson artificial intelligence to stage a comeback. The proliferation of cloud, social and mobile technologies have led to the most successful and innovative companies becoming increasingly concerned with the ability to successfully build a digital platform. Apple, Google, Facebook and Amazon each created platforms that co-create value by connecting to other business who can build products and services on their platforms.

Computers have long been good at carrying out assigned tasks but terrible at learning things on their own. Thus all the excitement around "neural networks," a breakthrough artificial intelligence technique that mimics the structure of the human brain and allows machines to learn things independently. Tech giants are using neural networks to do some pretty impressive things. Microsoft is using them to make instant translation real for Skype. Google's artificial intelligence learned Atari video games and then mastered the ancient game of Go, with its AlphaGo program beating the human champion Lee Sedol 4 to 1.

It takes at least a master's degree to fully understand synthetic biology, but grasping its importance requires far less. Like, say, a museum exhibit. The Bio Design Studio, a permanent exhibit at the Tech Museum in San Jose, California, explores the basics of synthetic biology through interactive installations. The multi-part exhibit, designed by Local Projects and The Extrapolation Factory, guides visitors through the fundamental building blocks of organic biology before leading them to a future where synthetic organisms are common. The goal, says Local Projects founder Jake Barton, is not just making synthetic biology accessible to everyone, but presenting the field objectively.

The robots are coming -- to help run your life or sell you stuff -- at an online texting service near you. In coming months, users of Facebook's Messenger app, Microsoft's Skype and Canada's Kik can expect to find new automated assistants offering information and services at a variety of businesses. These messaging "chatbots" are basically software that can conduct human-like conversation and do simple jobs once reserved for people. Google and other companies are reportedly working on similar ideas. In Asia, software butlers are already part of the landscape.

Google DeepMind, the search giant's artificial intelligence company in London, has officially announced its first big push into medical technology. The research-intensive startup launched a new division called DeepMind Health and acquired a university spinout company with a healthcare app called Hark. It has also built an app with the NHS called "Streams." DeepMind Health, announced on the DeepMind website on Wednesday, will be led by Mustafa Suleyman, cofounder and head of applied AI at Google DeepMind. He will oversee a team of approximately 15 people, according to Bloomberg, aiming to develop digital tools that improve patient care.