Category: information science – Page 311
IBM and MIT partner on artificial intelligence research
BOSTON (AP) — IBM is planning to spend $240 million over the next decade to create an artificial intelligence research lab at MIT.
Massachusetts Institute of Technology on Thursday announced the formation of the new MIT-IBM Watson AI Lab. It will support joint research by IBM and MIT scientists.
Its mission will include advancing the hardware, software and algorithms used for artificial intelligence. It also will tackle some of the economic and ethical implications of intelligent machines and look at its commercial application for industries ranging from health care to cybersecurity.
Artificial Intelligence and Smart Journalism
How is Artificial Intelligence actually thinking? Even their creators often don’t really fully understand. But if AI becomes more and more important you should at least have an idea of how algorithms get to results. And they think totally different to how human beings do, says Sara M. Watson, tech critic and writer at the Digital Asia Hub, Hong Kong. How can literature and journalism help to find a new perspective on AI?
“The biggest problem AI has is that even the engineers can’t really explain certain outcomes or certain decisions that go through an artificially intelligent system.”
Scientists Finally Prove Strange Quantum Physics Idea Einstein Hated
The equations of physics are things that we humans created to understand the Universe, and it can be hard to disentangle them from the Universe’s innate properties. It turns out that one of the weirdest things scientists have come up with, what Albert Einstein derisively called “spooky action at a distance,” is more than just math: It’s a fact of reality.
That concept is also known as entanglement, and it’s what allows particles that have once interacted to share a connection regardless of the separation between them. A team of physicists in the United Kingdom used some dense mathematics to come to their Einstein-angering conclusion, taking an important step towards proving whether quantum mechanics’ weirdness is just the math talking, or whether it speaks to innate physical requirements. Their mathematical proof’s main assumption is that any new physics theory should be backward-compatible with the physics you learned in high school.
AI Will Make Fake News Video — and Fight It As Well
Just weeks after one research team appeared to put words in a leader’s mouth, here comes a new tool that can check questionable video for a pulse.
A recent demonstration showing how easy it is to spoof video of a world leader recently made headlines, foretelling a future where robot-created videos cause political and financial havoc. But now comes word of an antidote. On Monday, a group of computer scientists from Carnegie Mellon University’s Software Engineering Institute published new research showing how algorithms can tell whether the person on-screen has a human heartbeat. The technique will help future intelligence analysts, journalists, or just scared television viewers detect the difference between spoofed video and the real thing.
In case you missed the original news about AI –created fake video, last month a team of researchers at the University of Washington revealed a tool that can change footage of someone’s face to match an audio clip, making it look like the person is saying things they aren’t.
Scientists discover nature’s algorithm for intelligence
But if there is some kind of unifying computational principle governing our grey matter, what is it? Dr. Tsien has studied this for over a decade, and he believes he’s found the answer in something called the Theory of Connectivity.
“Many people have long speculated that there has to be a basic design principle from which intelligence originates and the brain evolves, like how the double helix of DNA and genetic codes are universal for every organism,” Tsien said. “We present evidence that the brain may operate on an amazingly simple mathematical logic.”
The Theory of Connectivity holds that a simple algorithm, called a power-of-two-based permutation taking the form of n=2i-1 can be used to explain the circuitry of the brain. To unpack the formula, let’s define a few key concepts from the theory of connectivity, specifically the idea of a neuronal clique. A neuronal clique is a group of neurons which “fire together” and cluster into functional connectivity motifs, or FCMs, which the brain uses to recognize specific patterns or ideas. One can liken it to branches on a tree, with the neuronal clique being the smallest unit of connectivity, a mere twig, which when combined with other cliques, link up to form an FCM. The more complex the idea being represented in the brain, the more convoluted the FCM. The n in n=2i-1 specifies the number of neuronal cliques that will fire in response to a given input, i.
Google’s machine learning algorithm gets human help in quest for fusion power
Hot on the heels of last month’s nuclear fusion breakthrough comes the first results from a multi-year partnership between Google and Tri Alpha Energy, the world’s largest private fusion company. The two organizations joined forces in 2014 in the hopes that Google’s machine learning algorithms could advance plasma research and bring us closer to the dream of fusion power.