Divergent Microfactories made a name for itself this week with a twin announcement of its supercar prototype and the business platform underlying the car. It's all about 3D printing and the claims are impressive.
This is scooped because of the innovative business model !
One potential way to combat ongoing climate change, eliminate air pollution mortality, create jobs and stabilize energy prices involves converting the world's entire energy infrastructure to run on clean, renewable energy.
Big data—and big processing power—is a big deal for science. By crunching massive amounts of data billions of times faster than could be done by hand, computers have allowed scientists to discover faraway planets, unravel our genetic code, and even find the subatomic particle responsible for gravity. But imagine a future in which computers don't just use their awesome power to help scientists. Imagine a future in which computer can come up with useful scientific ideas and hypotheses all on their own.
Well, that just happened. As they report in the science journal PLOS, Michael Levin and Daniel Lobo, two computer scientists/biologists at Tufts University, have programed a computer that independently created its own scientific theory. It's one that may solve a 120-year-old mystery in biology that has eluded even our best explanations: exactly how the genes of a sliced-up flatworm conduct its symphony of cells when they regenerate into new organisms.
Considering machines that think is a nice step forward in the AI debate as it departs from our own human-based concerns, and accords machines otherness in a productive way. It causes us to consider the other entity’s frame of reference. However, even more importantly this questioning suggests a large future possibility space for intelligence.
There have been and will continue to be multiple big technology revolutions, but the most impactful on human society may be the one that finally builds systems with judgment and decision-making capability more sophisticated and nuanced than trained human judgment. Machine learning, sometimes called big data or artificial intelligence, is [...]
Researchers have mimicked the way the human brain processes information with the development of an electronic long-term memory cell, which mirrors the brain’s ability to simultaneously process and store multiple strands of information. The development brings them closer to imitating key electronic aspects of the human brain — a vital step toward creating a bionic brain and unlocking treatments for Alzheimer’s and Parkinson’s diseases.
Science fiction has a long tradition of pitting artificial intelligence against humanity in a struggle for dominance. Ray Kurzweil, a noted futurist and inventor, envisions a more co-operative future. He says the human brain will soon merge with computer networks to form a hybrid artificial intelligence.
Synthetic bodies, mediated selves. What themes become relevant in a technoprogressive world – as objects proliferate, what do the inundated people talk about? You are alone, at a computer. You talk to people but they are not around.
Late last year, I took a road trip with my partner from our home in New Orleans, Louisiana to Orlando, Florida and as we drove by town after town, we got to talking about the potential effects self-driving vehicle technology would have not only on truckers themselves, but on all the local economies dependent on trucker salaries. Once one starts wondering about this kind of one-two punch to America’s gut, one sees the prospects aren’t pretty.
Could sudden shifts in technology soon be coming over here and taking jobs?
"Last September, Dr Carl Benedikt Frey and Michael Osborne, two researchers at the Martin School in Oxford, published the results of a major study of the susceptibility of jobs to this new kind of automation. Their report, The Future of Employment: How Susceptible Are Jobs to Computerisation?, makes for a pretty sobering read. Frey and Osborne used machine-learning techniques to estimate the probability of computerisation for 702 detailed occupations, based on US government classifications of those occupations. Their conclusion? About 47% of total US employment is at risk from technologies now operational in laboratories and in the field."
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