Lifeboat Foundation

Ray Kurzweil is a futurist, a director of engineering at Google and a co-founder of the Singularity University think tank at NASA Ames Research Center in Mountain View. He is a nonfiction author and creator of several inventions.

Kurzweil met with the Silicon Valley Business Journal to discuss how technology’s exponential progress is rapidly reshaping our future through seismic shifts in information technology and computing power, energy, nanotechnology, robotics, health and longevity.

Intel has planted some solid stakes in the ground for the future of deep learning over the last month with its acquisition of deep learning chip startup, Nervana Systems, and most recently, mobile and embedded machine learning company, Movidius.

These new pieces will snap into Intel’s still-forming puzzle for capturing the supposed billion-plus dollar market ahead for deep learning, which is complemented by its own Knights Mill effort and software optimization work on machine learning codes and tooling. At the same time, just down the coast, Nvidia is firming up the market for its own GPU training and inference chips as well as its own hardware outfitted with the latest Pascal GPUs and requisite deep learning libraries.

While Intel’s efforts have garnered significant headlines recently with that surprising pair of acquisitions, a move which is pushing Nvidia harder to demonstrate how GPU acceleration (thus far the dominant compute engine for model training), they still have some work to do to capture mindshare for this emerging market. Further complicating this is the fact that the last two years have brought a number of newcomers to the field—deep learning chip upstarts touting the idea that general purpose architectures (including GPUs) cannot compare to a low precision, fixed point, specialized approach. In fact, we could be moving into a “Cambrian explosion” for computer architecture–one that is brought about by the new requirements of deep learning. Assuming, of course, there are really enough applications and users in a short enough window that the chip startups don’t fall over waiting for their big bang.

Continue reading “The Next Wave of Deep Learning Architectures” »

http://www.unz.com/akarlin/sinotriumph/

Nothing illustrates China’s meteoric rise as some well chosen numbers.

By the end of the 1990s, China had come to dominate the mainstays of geopolitical power in the 20th century – coal and steel production. As a consequence, it leapt to the top of the Compositive Index of National Capability, which uses military expenditure, military personnel, energy consumption, iron and steel production, urban population, and total population as a proxy of national power. Still, one could legitimately argue that all of these factors are hardly relevant today. While Germany’s fourfold preponderance in steel production over Russia may have been a critical number in 1914, China’s eightfold advantage in steel production over the US by 2014 is all but meaningless in any relevant comparison of national power. The world has moved on.

Continue reading “China Overtakes US in Scientific Articles, Robots, Supercomputers” »

Geordie’s perspective of AI on QC…

By Piper McGowin

Continue reading “Quantum Computing: Artificial Intelligence Is Here” »

Mercedes-Benz Vans and drone tech startup Matternet have created a concept car, or as they’re calling it a Vision Van, that could change the way small packages are delivered across short distances.

The Vision Van’s rooftop serves as a launch and landing pad for Matternet’s new, Matternet M2 drones.

The Matternet M2 drones, which are autonomous, can pick up and carry a package of 4.4 pounds across 12 miles of sky on a single battery charge in real world conditions.

Continue reading “Mercedes-Benz and Matternet unveil vans that launch delivery drones” »

Let’s see what medical robots we inevitably work closely in the future. From surgical precision to taking blood samples, robotics in healthcare is coming.

These digestible “robots” can be packed into a pill casing and swallowed like any old aspirin.

Meet the future of medical robotics.

Silicon Valley, or the Greater Bay Area, is the 18^th largest economy in the world, more than half the size of Canada’s economy and bigger than Switzerland, Saudi Arabia or Turkey. This is because the region has become the world leader in research and development of emerging technologies such as artificial intelligence, robotics, software and virtual reality.

“Software is eating the world,” said Silicon Valley investor Marc Andreessen famously in 2011. It was controversial but prescient.

Five years later, software-driven machines and drones perform surgery, write news stories, compose music, translate, analyze, wage war, guard, listen, speak and entertain. The world’s biggest box office hits — animated films such as “Frozen” or special effects in Hollywood blockbusters like “Star Wars” — are made using software.

Continue reading “How robots, drones and artificial intelligence will change everything” »

A new technique uses the curious physical laws of the nano-scale itself to “program” nanobots. Welcome to the future of nanotechnology.

Nanorobotics has long been touted as one of the most promising “miracle technologies” of the future. But one of the fundamental problems with such extreme miniaturization is how to “program” nanobots—after all, you can’t very well shrink computer circuitry to fit within nanometer-scale technology.

Continue reading “These Nanobots Can Repair Circuits All by Themselves” »