This is what has happened with Bitcoin mining (mostly in Tibet/China) since cost-differentiation between miners is no longer about who is using specialized hardware, but about who uses them most cheaply.

In the broadest definition, a sensor is a device whose purpose is to detect changes in the environment, and then generate a signal or data based on those changes. All living organisms contain biological sensors. Most of these are specialized cells that are sensitive to light, motion, temperature, magnetic fields, gravity, humidity, moisture, vibration, pressure, electrical fields, or sound, to name just a few. Over the years, many thousands of mechanical sensors have been developed to detect changes in their environments. Besides pressure, sensors have also been developed to measure changes in sound, vibration, chemical composition, electric current, electric potential, magnetic force, radio waves, flow, fluid velocity, ionizing radiation, subatomic particles, navigation instruments, position, angle, displacement, distance, speed, acceleration, optical, light, imaging, photon, force, density, level, thermal, heat, temperature, proximity and presence, again to name a few.

The speed of technological change is exponential. What was yesterday's hot ticket quickly becomes tomorrow's old news. We are living in the midst of a huge surge of interest and research in Artificial Intelligence (AI). It seems like every week there is a new breakthrough in the field and a new record is set in some task previously done by humans. If you don't already know what IoT, AI, VR, AR, and bots mean, you better get up to speed immediately because these technologies are changing the way data is created, collected, interpreted, and communicated.

Google's artificial intelligence (AI) technology, already proven capable of contending with human problem-solving, may soon be able to think creatively. Google AI continues to make strides in its development, this year being legally considered a driver of the tech giant's autonomous cars, beating people in geotagging and location recognition, and even learning to understand words and events taking place around it in the real world. Its practical applications are constantly expanding, but with its new Google Magenta project, the company hopes AI can become artistic as well. "The question Magenta asks is, 'Can machines make music and art? If not, why not?'" Google machine-learning research scientist Douglas Eck wrote in a blog post on the project.

We're proud to be supporting the new developer survey run by our friends at VisionMobile. This is the 11th developer survey and it's entitled Developer Tools Benchmarking – as you can understand, the focus is on developer tools. The survey features questions on topics like programming languages, platforms, app categories, tool categories, revenue models, IoT verticals. This year, they have included specific survey questions on Machine Learning tools such as BigML as a new area to explore. It's a survey made by developers, for developers – so the questions are very relevant. Whether you're looking to share your thoughts with the dev community, find out something new, contribute to the leading developer research – or win a great prize – this is the survey for you.

Artificial intelligence has come a long way since the term was coined in the 1950s, but computers still don't think and feel in quite the same way humans do. Yet rapid progress has the federal government, and others, thinking about new legal and policy issues. Artificial intelligence has been around for decades. Think airplanes that fly on auto-pilot. Today, that technology is developing quickly, thanks to breakthroughs in computer science.

It is not only Google, Microsoft or Facebook that can afford such a system. It pays off to have an internal platform at hand where the engineer(s) can quickly test new hypothesis, try out or implement new algorithms, run anything from simple Bayesian classifiers to the more time consuming deep learning. And as we focus on narrow domains here, Andrew Ng, the chief scientist at Baidu recently said: "Most of the value of deep learning today is in narrow domains where you can get a lot of data."

When the artificial intelligence program AlphaGo defeated champion Go player Lee Sedol earlier this year, everyone praised its advanced software brain. But the program, developed by Google's DeepMind research team, also had some serious hardware brawn standing behind it. The program was running on custom accelerators that Google's hardware engineers had spent years building in secret, the company said. With the new accelerators plugged into the AlphaGo servers, the program could recognize patterns in its vast library of game data faster than it could with standard processors. The increased speed helped AlphaGo make the kind of quick, intuitive judgments that define how humans approach the game.

Earlier this year, the Institute of Electrical and Electronics Engineering's (IEEE) published "AI's 10 to Watch" – a list of 10 people who are doing phenomenal work in the field of artificial intelligence. A Pakistani researcher Haris Aziz, who had graduated from LUMS, had his name published in this prestigious list for his work in the field related to computational social choice, an intersection between artificial intelligence and economics. Its seems that was just the beginning of the road for Haris Aziz, who is now back in the news for solving an'unsolvable' mathematical situation. Who will get the larger share of the profit from a business? Shall it be equally allocated or otherwise? Perhaps its your child's birthday and its time to cut and divide the cake in a way that none of the children gets sad by his/her share?

Sixty years ago this summer, four computer science professors established a summer project aimed at creating "artificial intelligence"--the first time this phrase was ever used. The hope was to figure out how to make machines use language and perform abstract thought. "We think that a significant advance can be made if a carefully selected group of scientists work on it together for a summer," the now famous project proposal said. In retrospect that was almost hubristically optimistic. We still don't have software that can talk or write as we do, or perform abstract reasoning.