While much of the conversation around AI and jobs is focused on widespread job losses in sectors like trucking, venture capitalist and Sun Microsystems cofounder Vinod Khosla thinks that there’s a high-paying job on the chopping block: oncology.
This report analyzes key drivers that will reshape the landscape of work and identifies key work skills needed in the next 10 years. It does not consider what will be the jobs of the future. Many studies have tried to predict specific job categories and labor requirements.
Consistently over the years, however, it has been shown that such predictions are difficult and many of the past predictions have been proven wrong. Rather than focusing on future jobs, this report looks at future work skills—proficiencies and abilities required across different jobs and work settings.
Music and other live performance art has always been at the cutting edge of technology so it’s no surprise that artificial intelligence and machine learning are pushing its boundaries.
As AI’s ability to manage key elements of the creative process continue to evolve, should artists be worried about the machines taking over? Probably not, says Douglas Eck, research scientist at Google’s Magenta.
“We are on the edge of change comparable to the rise of human life on Earth.” -Vernor Vinge
If you’re like me, you used to think Artificial Intelligence was a silly sci-fi concept, but lately you’ve been hearing it mentioned by serious people, and you don’t really quite get it. Here’s why it’s so incredibly important.
There’s a revolution happening in biology, and its name is CRISPR.
CRISPR (pronounced “crisper”) is a powerful technique for editing DNA. It has received an enormous amount of attention in the scientific and popular press, largely based on the promise of what this powerful gene editing technology will someday do.
In today’s world, a terabyte is a rather routine size of information. However, when we get to petabyte, we talking serious volumes of data.
Companies like DigitalGlobe are creating more petabytes than they can upload to the cloud. That’s why Jeff Bezos has a service for shipping huge amounts of data via traditional roadways.
“Code is law,” as described in Lawrence Lessig’s book ‘Code and Other Laws of Cyberspace’, refers to the idea that computer code has progressively established itself as a predominant way to regulate behavior to the same degree as legal code.
With the advent of blockchain technology, code is assuming an even stronger role in regulating people’s interactions.
However, while computer code can enforce rules more efficiently than legal code, it also comes with a series of limitations.
When “little green men” invaded Crimea in early 2014, they left a data trail that went largely unnoticed by the U.S. Intelligence Community (IC). Distracted by a large Russian exercise to the west, the IC did not connect the digital dots that indicated the impending invasion. In the Information Age, the “dots” are more plentiful and glaring as everyone now leaves a data trail. Given that, how can intelligence analysts better gather, share, organize, and view data to reveal intent, more accurately predict behavior, and make better decisions with limited resources?
The first day of the Brains vs. AI poker tournament is in the books, and the Libratus bot from Carnegie Mellon University emerged as the clear winner, collecting $81,716 to the humans $7,228. Both the players and Libratus’ creators cautioned that it was still too early to make a judgement call about who might win the 20-day tournament. But it’s clear that this year’s AI has made some major improvements on the 2015 system, Claudico, which ended up losing to humanity.
In a sound-proofed hangar on an RAF airbase just north of Cambridge, UK, Chris Mitchell and his colleagues are busy using sledgehammers to teach their computers a lesson. The team has gathered thousands of window panes and doors, all of different shapes and sizes, which they then smash, one by one, recording the distinctive shattering sound of each type of glass. Sometimes they swing sledgehammers or garden spades, sometimes they throw bricks. “We completely underestimated the mess it would make,” says Mitchell. “And how tiring it would be.”
There’s a big temptation for businesses to use artificial intelligence to shave off time and money wherever they can. According to experts, that’s not the smartest use of the technology.
2016 was a banner year for artificial intelligence. Alpha Go’s victory over Lee Sedol was perhaps one of the most important, but we saw advancements in self-driving cars, the continued embrace of bots and personal assistants for retail, adoption and competition around in-house assistants like Amazon Echo, along with frequent, sometimes weekly, breakthroughs on the academic side, mainly relating to machine learning. With the biggest tech companies in the world–Google, Facebook, Amazon, Microsoft, and others–devoting more and more resources to AI, the momentum is going to increase.