Rather than follow the trend of the past 30 years of trying to crack games using computing power, DeepMind has reverted to mimicking human-like knowledge, albeit by training, rather than by being programmed, he says. The feat also shows the power of deep learning, which is going from success to success, says Coulom. “Deep learning is killing every problem in AI.”
Source: Google AI algorithm masters ancient game of Go : Nature News & Comment
In what has been claimed to be the first use of gene editing technique CRIPSR for replacement of a defective gene associated with a sensory disease, researchers have repaired a genetic defect that causes blindness.
Source: Researchers use CRISPR to repair genetic defect that causes blindness | Dispatch Tribunal
It will be a long time before anyone starts sending fully formed thoughts to a computer, he says—and even longer before anyone finds it really useful. Think about speech-recognition software, which has been around for decades, Schalk says. “It was probably 80 percent accurate in 1980 or something, and 80 percent is a pretty remarkable achievement in terms of engineering. But it’s useless in the real world,” he says. “I still don’t use Siri, because it’s not good enough.”
Source: The Neurologist Who Hacked His Brain—And Almost Lost His Mind | WIRED
This may sound like science fiction, or the plot of a Marvel movie, but AFP is reporting that scientists and arms experts in attendance at the World Economic Forum in Davos, Switzerland have issued a dire warning saying that robots with advanced artificial intelligence (or AI robots) could one day join wars and kill many people.
Source: Experts At Davos Say Weaponized Artificial Intelligence Robots Are Dangerous – STGIST
This is a moonshot challenge, akin to the Human Genome Project in scope. The scientific value of recording the activity of so many neurons and mapping their connections alone is enormous, but that is only the first half of the project. As we figure out the fundamental principles governing how the brain learns, it’s not hard to imagine that we’ll eventually be able to design computer systems that can match, or even outperform, humans.
Source: Harvard will take a close look at the brain to build better AIs
Corporations, it seems, may have amassed at least a good chunk of that $1.9 trillion in mysterious savings because the stock market is rewarding them for it.
Which leaves one last question: Why? The answer, perhaps, is that both the executives and the investors in these industries believe that something big is coming, but — this is crucial — they’re not sure what it will be. Through the 20th century, as we shifted from a horse-and-sun-powered agrarian economy to an electricity-and-motor-powered industrial economy to a silicon-based information economy, it was clear that every company had to invest in the new thing that was coming. These were big, expensive investments in buildings and machinery and computer technology. Today, though, value is created far more through new ideas and new ways of interaction. Ideas appear and spread much more quickly, and their worth is much harder to estimate. (Indeed, the impossibility of valuing the Internet is essentially what created the 2000 stock bubble.)
Source: Why Are Corporations Hoarding Trillions? – The New York Times
“These changes will not happen overnight, but they are inevitable. Though many doctors will see these changes as a threat, the chance for global good is unprecedented.
An X-ray taken in equatorial Africa could be read with the same reliability as one taken in an Australian centre of excellence. An infectious rash could be uploaded to a phone and the diagnosis given instantly. Many lives will be saved, and the cost of health care to the world’s poor can be minimal and, in many cases, free.”
Source: Digital Diagnosis: Intelligent Machines Do a Better Job Than Humans – Singularity HUB
Stack fallacy is the mistaken belief that it is trivial to build the layer above yours.
Source: Why Big Companies Keep Failing: The Stack Fallacy | TechCrunch
“Tech firms that offer lavish perks to their staff do not do so out of the goodness of their hearts. They offer them because they expect people to work so hard that they will not have time for such mundane things as buying lunch or popping to the dry-cleaners. As Gerald Ledford of the University of Southern California’s business school puts it, they are “golden handcuffs” to keep people at their desks. Some of the most extravagant perks are illusions: “take as much holiday as you like” may really mean “take as little as possible, and as much as you dare.” Some have vaguely sinister undertones: might the option for women to freeze their eggs end up becoming the expectation?”
