Lifeboat Foundation

True points and many that I have been sharing on Quantum around its own potential to change everything that we know about technology (devices, internet & networking in general, wireless and satellites, AI, advancements in biotech, security, big data, and singularity itself). The author also highlights many of the same concerns that I have shared around hackers on Quantum breaking through the older digitized platforms and networks; therefore, many companies and governments are exposed as well as consumers who have not adopted Quantum.

Although the author speculates we’re less than 10 yrs for Quantum to be seen in the everyday usage; I believe we’re within 7 yrs.

Within four years quantum computers will have the beating of conventional computers and that will produce a dramatic change in both the technology landscape and in business, according to Professor Jeremy O’Brien from Bristol University.

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Elon Musk, CEO of Space Exploration Technologies (SpaceX) and Tesla Motors, Inc, was at Startmeup Hong Kong and talked about what he thought were areas of technological opportunity.

At 37 minutes into this video Elon Musk talks about high potential technology like Hyperloop which he currently does not have time to address electric aircraftgenetics is thorny but is our best shot at many tough diseasesbrain computer interfaces at the neuron level has potential for intelligence augmentationNeural Lace was mentioned.

Scientists from China and the US have found a pioneering way to inject a tiny electronic mesh sensor into the brain that fully integrates with cerebral matter and enables computers to monitor brain activity.

Continue reading “Elon Musk identifies electric aircraft, genetics and neuron scale brain computer interfaces as high potential technologies” »

Could the FDA crush IoT opportunities in Healthcare?

The U.S. Food and Drug Administration last week took a step toward addressing the threat the Internet of Things poses to patients and their data by releasing some proposed guidelines for managing cybersecurity in medical devices.

“A growing number of medical devices are designed to be networked to facilitate patient care. Networked medical devices, like other networked computer systems, incorporate software that may be vulnerable to cybersecurity threats,” the FDA says in its proposal.

Continue reading “FDA Guidelines Target IoT Medical Device Security” »

The game of Go has long been viewed as the most challenging of classic games for artificial intelligence due to its enormous search space and the difficulty of evaluating board positions and moves.

Google DeepMind introduced a new approach to computer Go with their program, AlphaGo, that uses value networks to evaluate board positions and policy networks to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of state-of-the-art Monte-Carlo tree search programs that simulate thousands of random games of self-play. DeepMind also introduce a new search algorithm that combines Monte-Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.

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Researchers at Harvard are working to identify the brain processes that make humans so good at recognising patterns. Their ultimate goals is to develop biologically-inspired computer systems for smarter AI. Computers inspired by the human brain could be used to detect network invasions, read MRI images, and even drive cars.

Their ultimate goals is to develop biologically-inspired computer systems for smarter AI.

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An experiment by University of Washington researchers is setting the stage for advances in mind reading technology. Using brain implants and sophisticated software, researchers can now predict what their subjects are seeing with startling speed and accuracy.

The ability to view a two-dimensional image on a page or computer screen, and then transform that image into something our minds can immediately recognize, is a neurological process that remains mysterious to scientists. To learn more about how our brains perform this task—and to see if computers can collect and predict what a person is seeing in real time—a research team led by University of Washington neuroscientist Rajesh Rao and neurosurgeon Jeff Ojermann demonstrated that it’s possible to decode human brain signals at nearly the speed of perception. The details of their work can be found in a new paper in PLOS Computational Biology.

The team sought the assistance of seven patients undergoing treatment for epilepsy. Medications weren’t helping alleviate their seizures, so these patients were given temporary brain implants, and electrodes were used to pinpoint the focal points of their seizures. The UW researchers saw this as an opportunity to perform their experiment. “They were going to get the electrodes no matter what,” noted Ojermann in a UW NewsBeat article. “We were just giving them additional tasks to do during their hospital stay while they are otherwise just waiting around.”

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When the consumers (who happen to be your primary customer) of your product doesn’t seem to be fully aware of your product; then you have indeed a broken product marketing and launch awareness program. And, if industry is also part of that picture; you may have an even bigger challenge.

After our latest US consumer research in October 2015, we wanted to find out if the trends we were seeing in the survey data held for a larger, more international pool. In December, we surveyed over 1,000 respondents throughout the United Kingdom about their awareness of virtual reality, interest in purchasing headsets and trying applications, and their concerns.

With everyone from Facebook’s Mark Zuckerberg to analysts at Goldman Sachs boldly claiming VR as the next computing platform, we believe it is critical strategic decision makers — product managers, marketers, and investors alike — better understand the industry’s potential early adopters and what they really want from our industry.

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Finally, folks are getting the real picture around re-tooling and retraining folks for new jobs in an oncoming AI future. In my posts; I have highlighted the need for governments and businesses to retrain people as well as ensure that their is some level of funding established to assist displaced workers, and especially as we see the maturity of Quantum in the AI space this will definitely be a must.

“If every tool, when ordered, or even of its own accord, could do the work that befits it… then there would be no need either of apprentices for the master workers or of slaves for the lords.” – Aristotle.

Humans have such a love/hate relationship with technology that it’s almost comical. All of our own creation, once we’ve perfected amazing innovations, we often turn on them–when convenient. As the PC became common and marketed toward the masses in the 80s, a new world of automation, both good and bad, was predicted. As mad scientists tucked away in secret, underground labs began creating evil robots in a slew of sci-fi movies that we consumed greedily, along with becoming affectionate toward machines like C-3P0 and R2-D2 just birthed in what would be a continuing pop subculture with a momentum of its own, our imaginations ran wild. Fearmongers cited that automation would make many jobs obsolete; robots would begin doing what was left as an economic apocalypse ensued for the human race.

Continue reading “World Economic Forum Report: Existing Workforce Must Prepare, Re-Skill & Up-Skill for Impending Fourth Industrial Revolution” »

At this rate of making machines to behave and interact like humans; we may end up with a world with some really messed up robots.

A new database will gauge progress in artificial intelligence, as computers try to grasp what’s going on in scenes shown in photographs.

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