Humanity's got itself a problem. As Homo sapiens balloons as a species--to perhaps nearly 10 billion by 2050--the planet stubbornly stays the same size, meaning the same amount of land must support way, way more people. Add the volatility of global warming and consequent water shortages, and the human race is going to have some serious trouble feeding itself. Perhaps it's serendipitous, then, that the machines have finally arrived. Truly smart, truly impressive robots and machine learning algorithms that may help usher in a new Green Revolution to keep humans fed on an increasingly mercurial planet.

"Given an example of presence and absence of a specific concept, computers would use storage to memorize examples exactly as they appear from a shallow learning concept – classic memorization," Dreyer said. Humans adjust neural weighting to solve for current and future examples, so we don't have to see a future example to know what something is. If you show a computer a picture of a bunch of oranges and then show it an apple, the computer wouldn't know what the apple was because it hadn't seen it before. Humans exploit deep learning by classifying new objects, recognizing faces, and recognizing language, Dreyer said. We see examples every day of facial recognition technology (for example, used by Facebook and Twitter).

There is a difference between knowledge and understanding. Knowledge typically comes down to knowing facts while understanding is the application of knowledge to the mastery of systems. You can know a lot while understanding very little. Just as an example, IBM's Watson artificial intelligence system that defeated the TV Jeopardy champs a few years ago knew all there was to know about Jeopardy questions but didn't really understand anything. Ask Watson to apply to removing your appendix its knowledge of hundreds of medical questions and you'd be disappointed and probably dead.

The news was the big surprise saved for the end of a two-hour keynote at the search giant's annual Google IO event in the heart of Silicon Valley. "We have started building tensor processing units…TPUs are an order of magnitude higher performance per Watt than commercial FPGAs and GPUs, they powered the AlphaGo system," said Sundar Pichai, Google's chief executive, citing the Google computer that beat a human Go champion. The accelerators have been running in Google's data centers for more than a year, according to a blog by Norm Jouppi, a distinguished hardware engineer at Google. "TPUs already power many applications at Google, including RankBrain, used to improve the relevancy of search results and Street View, to improve the accuracy and quality of our maps and navigation," he said. The chips ride a module that plugs into a hard drive slot on server racks.

IMAGE: Dr. Ben Choi, associate professor of computer science at Louisiana Tech University, will present his research on a groundbreaking new technology that has the potential to revolutionize the computing industry... view more RUSTON, La. - Dr. Ben Choi, associate professor of computer science at Louisiana Tech University, will present his research on a groundbreaking new technology that has the potential to revolutionize the computing industry during a keynote speech next month at the International Conference on Measurement Instrumentation and Electronics. Choi will present on a foundational architecture for designing and building computers, which will utilize multiple values rather than binary as used by current computers. The many-valued logic computers should provide faster computation by increasing the speed of processing for microprocessors and the speed of data transfer between the processors and the memory as well as increasing the capacity of the memory. This technology has the potential to redefine the computing industry, which is constantly trying to increase the speed of computation and, in recent years, has run short of options. By providing a new hardware approach, the technology will push the speed limit of computing using a progressive approach which will move from two values to four values, then to eight values, then to 16 values, and so on. Future computers could be built using this many-valued approach.

Every day now there's a new announcement of a major media or technology player betting big on the future of chatbots powered by artificial intelligence, that will do everything from helping us book trips to controlling our ever-smarter homes. Our natural language is, well, the most natural way for humans to communicate. Getting what we want through a conversation with an intelligent agent is bound to feel simpler than using a click-based interface, especially in a world where mobile rules. It feels like a new horizon is opening up, but also like a bit of déjà vu. In the early 2000s I worked as a copywriter on one of the first IM-based chatbots, named VaVaVirgil, who was built to help the Virginia Tobacco Settlement Foundation educate teens on the dangers of smoking.

I write about search A LOT--about how to nail search engine marketing (SEM), the impact mobile has on consumers' search and purchasing habits and how RankBrain and artificial intelligence (AI) are changing the search game. Why do I write about this so much? That's easy: if you're a marketer and don't care about what's happening with search, it's impossible to do your job. The conversations about search so far, though, have always had one thing in common: We've been talking about text. Think for a moment about all the images and visual assets circulating the web.

Robots are taking over iPhone manufacturer Foxconn: the world's biggest contract fabricator has successfully replaced as many as 60,000 factory workers with sophisticated machines that use artificial intelligence to perform elaborate assembly work more efficiently than humans do, a government official told the South China Morning Post. One Foxconn plant has "reduced employee strength from 110,000 to 50,000 thanks to the introduction of robots" and "more companies are likely to follow suit," said Xu Yulian, head of publicity for the Kunshan region in the Jiangsu province, which is a manufacturing hub for the electronics industry. About 600 major companies in Kunshan are planning to tap artificial intelligence to replace workers with robots. Foxconn Technology Group confirmed to the BBC that it was automating "many of the manufacturing tasks associated with our operations." Still, Foxconn insists that using robots does not entail long-term job losses.

What do you think of when you hear the word "technology"? Do you think of jet planes and laboratory equipment and underwater farming? Or do you think of smartphones and machine-learning algorithms? When a grave-faced announcer on CNBC says "technology stocks are down today," we all know he means Facebook and Apple, not Boeing and Pfizer. To Thiel, this signals a deeper problem in the American economy, a shrinkage in our belief of what's possible, a pessimism about what is really likely to get better. Our definition of what technology is has narrowed, and he thinks that narrowing is no accident. "Technology gets defined as'that which is changing fast,'" he says. "If the other things are not defined as'technology,' we filter them out and we don't even look at them." He founded PayPal and Palantir, was one of the earliest investors in Facebook, and now sits atop a fortune estimated in the billions. We spoke in his sleek, floor-to-ceiling-windowed apartment overlooking Manhattan -- a palace built atop the riches of the IT revolution.

Recently esteemed M I T physicist, Max Tegmark, and science philosophy professor, from Oxford university, Nick Bostrom, joined forces to address the United Nations. They were there with the sole purpose of addressing their concerns over the dangers of Artificial Intelligence.