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.

We live in an era of accelerating change, when scientific and technological advancements are arriving rapidly. As a result, we are developing a new language to describe our civilization as it evolves. Here are 20 terms and concepts that you'll need to navigate our future. Back in 2007 I put together a list of terms every self-respecting futurist should be familiar with. I reached out to several futurists, asking them which terms or phrases have emerged or gained relevance since that time. These forward-looking thinkers provided me with some fascinating and provocative suggestions -- some familiar to me, others completely new, and some a refinement of earlier conceptions.

Philosopher John Danaher's new paper "Will life be worth living in a world without work? Technological Unemployment and the Meaning of Life" assumes that after the robots take all our jobs, and after the economic justice of figuring out how to share the productivity games can be equitably shared among the robot-owning investor class and the robot-displaced 99%, there will still be a burning question: what will give our life meaning? The paper covers a lot of familiar territory, but gets going on page 16, with section 4, "How Technological Advance could undermine the Good Life." That's the meat of the argument, where Danaher starts looking at different prevailing theories of life satisfaction and its relationship to work, and whether fully automated leisure communism could give its inhabitants something to live for, amid all the ludic playfulness and lack of fear of starvation or poverty: I argued that if meaning and fulfillment are at least partly determined by how our individual activities join up with the external world, then there is something to worry about if automating technologies takeover most domains of human activity. They could sever the necessary links between what we do and what happens in the world.

Researchers at Oxford University are setting Google's artificial intelligence DeepMind loose on analyzing Hearthstone and Magic: The Gathering playing cards. According to Kotaku, the AI analyzes card data such as resource cost and damage, and turns it into code that a machine can read. Here's the abstract from the paper titled'Latent Predictor Networks for Code Generation': "Many language generation tasks require the production of text conditioned on both structured and unstructured inputs. We present a novel neural network architecture which generates an output sequence conditioned on an arbitrary number of input functions. Crucially, our approach allows both the choice of conditioning context and the granularity of generation, for example characters or tokens, to be marginalised, thus permitting scalable and effective training. "Using this framework, we address the problem of generating programming code from a mixed natural language and structured specification.

McCann Erickson Japan is taking artificial intelligence to the next level, creating and appointing the world's first robot creative director. The robot, called AI-CD?, will be assigned as a creative director to client accounts and will provide creative direction for commercials. It will also evaluate and gain learnings from results after commercials have aired to ensure it improves for future projects. AI-CD? was developed through a new taskforce in the agency, McCann Millennials, a group of staff members born between 1980 and 2000 who apparently care not for the future of their own careers, or the possible rising of the machines à la The Matrix. The robot is able to give creative direction for commercials, drawing from a database of tagged and analysed TV commercials from the past 10 years of winners of the All Japan Radio & Television Commercial Confederation's annual CM Festival (ACC CM Festival).

Artificial Intelligence is the discipline of thinking machines. It has been a field of growing interest since 1955 when John McCarthy first coined the term, defining it as "the science and engineering of making intelligent machines." The largest players in technology today, including Google, Facebook, Amazon, Microsoft and Apple, are all investing heavily in Artificial Intelligence. So are most of the technology focused Venture Capital firms. All indications are this hot field is about to accelerate dramatic capabilities into every corner of our economy.

Artificial intelligence systems based on neural networks have had quite a string of recent successes: One beat human masters at the game of Go, another made up beer reviews, and another made psychedelic art. But taking these supremely complex and power-hungry systems out into the real world and installing them in portable devices is no easy feat. This February, however, at the IEEE International Solid-State Circuits Conference in San Francisco, teams from MIT, Nvidia, and the Korea Advanced Institute of Science and Technology (KAIST) brought that goal closer. They showed off prototypes of low-power chips that are designed to run artificial neural networks that could, among other things, give smartphones a bit of a clue about what they are seeing and allow self-driving cars to predict pedestrians' movements. Until now, neural networks--learning systems that operate analogously to networks of connected brain cells--have been much too energy intensive to run on the mobile devices that would most benefit from artificial intelligence, like smartphones, small robots, and drones.

What shore knows not our maps? Most of them, it turns out. While satellites map much of the globe on a daily basis, there are parts of the planet so small and changing that they're tricky to pin down exactly. NOAA, America's National Oceanic and Atmospheric Administration, makes maps that anyone who navigates the sea can use, and to get the fine details on little inlets right, they turn to… "Autonomous Surface Vehicles," also known as sea drones and (at least at Popular Science) as Roboats. While much of NOAA's sea plotting is done by ships, the smaller robots can swim to shallow inlets and areas, capturing parts of the ocean otherwise unknown.

The robots were supposedly coming for our jobs. Not just the blue collar jobs, but also the highly trained and exceptionally well-paid jobs of anesthesiologists. These doctors help patients walk the dangerously thin line between pain-free unconsciousness and death, and for that their services can cost 2,000 per procedure. A robot named Sedasys could do the same job for more like 200 … except that nobody wants to buy it. Several outlets are reporting that Johnson & Johnson will stop selling Sedasys because of poor sales.

Both R & Python should be measured based on their effectiveness in advanced analytics & data science. Initially, as a new comer in data science field we spend good amount of time to understand the pros and cons of these two. I too carried out this study solely for "self" to decide which tool should i pick to get in depth of data science. Eventually, i have started realizing that both (R & Python) has its space of mastery along with their broad support to data science. Now, when you start getting into space of predictive modeling, machine learning and mathematical modeling, Python can give a easy hand.