Lifeboat Foundation

Imagine a five-year-old watching Mum talking to Siri, and Dad talking to Alexa, on a daily basis — what must she think of such interactions? Children nowadays witness computers that seem like they have a mind of their own — and even a personality with which to engage. It can be taken for granted that their perception of machines, and thus of the world itself, differs a lot from our own.

Artificial intelligence is one of the most promising areas of tech today, if not even the one that is likely to entail the most striking changes in our way of living, the way our economy works and how society functions. Thanks to enormous amounts of data, coupled with compute power to analyze it, technology companies are making strides in AI that resembles something of a gold rush.

New approaches, including use of deep neural networks, have led to groundbreaking achievements in AI, some of which weren’t predicted to happen for another decade. Google defeating the world champion at the ancient game of Go is just one prominent example. Many more are to be expected, including advances in deep learning combined with reasoning and planning — or even emulating creativity and artwork.

A computer’s victory over a human go master this past March reminds us of the pending “singularity” — the rapidly approaching moment in time when artificial intelligence overtakes human intelligence. Machines will learn, and we won’t be their teachers. Are we prepared for it? Can we prepare for it?

We’d better. Many futurists declare it inevitable, probably within a generation, maybe less. Shukan Shincho magazine discusses some hypothetical implications in its Aug. 25 edition. Even the least of them are shocking. For example, in 2045 a computer with the combined intellectual power of the entire human race would cost $100. In short, it’ll be no big deal. What will be a big deal? Should we shudder at the thought, or rejoice?

Francis Bacon (1561−1626) is generally acknowledged as the grandfather of modern science. “Nature, to be commanded, must be obeyed,” he wrote. His fictional “New Atlantis” was a utopia ruled by scientists who, having admitted their ignorance and purged themselves of illusory knowledge, experimented, observed and slowly built up from scratch an ever-expanding store of “true” knowledge — armed with which they “commanded” nature to outgrow her destructive caprices and ease mankind’s lot.

Continue reading “Building a stairway to the singularity” »

Written by ROLAND BENEDIKTER, KATJA SIEPMANN, ALEXANDER REYMANN

ABSTRACT. This article discusses the philosophical implications and potential social consequences of two experimental – and at the present moment still widely speculative – topics at the intersection between scientific and medical advances, the human body, the human mind, and the globalized health care sector. Head-Transplanting is a chirurgical endeavor envisaged by the HEAVEN project announced to be practically implemented around 2017 and to be available for routine-use around the mid-2020s by a group of internationally as prominent as disputed transplant surgeons. Mind-Uploading is a procedure currently in the first stages of development to create artificial representations of the human brain and its processes in computers and on the internet.

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.

Electric bus that recharges in 15 seconds!

It takes these electric buses less time to recharge than it does to pick up passengers thanks to flash charging technology developed by ABB.

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” »

Keep in mind as you plan your hardware purchases — AMD CPUs, APUs, and Intel CPUs are all Windows 10-only from this point forward. AMD GPUs will continue to support Windows 7 and 8 for now, though we don’t know when the company will terminate this.

In an attempt to bring the next generation of computers to life, teams around the globe have been working with carbon nanotubes — one of the most conductive materials ever discovered. Now, for the first time ever, scientists made a transistor using carbon nanotubes that beats silicon.

For the first time, scientists have built a transistor out of carbon nanotubes that can run almost twice as fast as its silicon counterparts.

Continue reading “For First Time Ever, Carbon Nanotube Transistors Have Outperformed Silicon” »

No shock to me.

Diamandis claimed that we are gearing towards a future possible of “interface mind-machine, where in human brain’s consciousness could be uploaded to computer and then transferred to a new body—probably a cultured in the lab. He estimates that it will just take 20–30 years to be realized.

The reality of extended life longevity to almost immortality is actually not too hard to believe these days. After all science and technology never failed to amuse us to make the once impossible possible.

Continue reading “We Might Be Getting Closer To ‘Immortality’ Through Medical Nanotechnology” »