White House technology official Michael Kratsios addresses scores of executives, experts and officials at a White House summit focusing on artificial intelligence in 2018. (White House OSTP Photo / Erik Jacobs)
The Trump administration is updating the Obama administration’s strategy for artificial intelligence to put more emphasis on public-private partnerships like the one forged this year by Amazon and the National Science Foundation.
Three years after the initial strategic plan for AI research and development was released, the update was issued online overnight. It makes tweaks in the seven policy priorities that were laid out in the waning days of the Obama White House, and adds public-private partnerships as an eighth priority.
Rohit Prasad, Amazon’s vice president and head scientist for Alexa, explains how the virtual assistant can plan different activities for a night out. (GeekWire Photo / Alan Boyle)
LAS VEGAS — Amazon’s Alexa virtual assistant will soon get savvier about juggling its thousands of skills — starting with arranging all the elements for a night out.
Cross-skill action prediction is one of the upgrades for Alexa announced here today at Amazon’s re:MARS conference.
Rohit Prasad, Amazon’s vice president and head scientist for Alexa, laid out a scenario where a user of Echo Show could engage in a seamless dialogue to choose a showing of “Dark Phoenix,” reserve seats through Atom Tickets, find a nice Chinese restaurant nearby, make a dinner reservation through Open Table, set up an Uber ride and watch a movie trailer.
“We’ll be bringing this experience to our customers soon,” Prasad said during today’s morning keynote.
Amazon CEO Jeff Bezos raises his arms (and the robotic arms they’re linked to) at the re:MARS conference in Las Vegas. (GeekWire Photo / Alan Boyle)
LAS VEGAS — Amazon CEO Jeff Bezos’ handshake is at least as firm as a robotic hand’s grip.
I found that out for myself today at Amazon’s inaugural re:MARS conference, when Bezos tried out the touch-sensitive, dexterous robotic arm set up in an exhibit hall at the Aria Resort and Casino here in Las Vegas.
Like the annual invitation-only MARS conference, re:MARS is designed to focus on the frontiers of Machine learning, Automation, Robotics and Space. And robots were the stars of the show when Bezos popped in.
Brad Porter, vice president of robotics at Amazon, introduces new breeds of robots at the re:MARS conference in Las Vegas. (GeekWire Photo / Alan Boyle)
LAS VEGAS — Amazon says there are now 200,000 robots working alongside 300,000 people at its distribution facilities around the world, and there’s more to come.
Brad Porter, vice president of robotics at Amazon, took the virtual wraps off two new types of robots during today’s keynote session at the first-ever re:MARS conference here in Las Vegas.
Erez Barak, senior director of product for Microsoft’s AI Division, speaks at the Global Artificial Intelligence Conference in Seattle. (GeekWire Photo / Alan Boyle)
Artificial intelligence can work wonders, but often it works in mysterious ways.
Machine learning is based on the principle that a software program can analyze a huge set of data and fine-tune its algorithms to detect patterns and come up with solutions that humans may miss. That’s how Google DeepMind’s Alpha Go AI agent learned to play the ancient game of Go (and other games) well enough to beat expert players.
But if programmers and users can’t figure out how AI algorithms came up with their results, that black-box behavior can be a cause for concern. It may become impossible to judge whether AI agents have picked up unjustified biases or racial profiling from their data sets.
That’s why terms such as transparency, explainability and interpretability are playing an increasing role in the AI ethics debate.
Transparency figures in Microsoft CEO Satya Nadella’s “10 Laws of AI” as well — and Erez Barak, senior director of product for Microsoft’s AI Division, addressed the issue head-on today at the Global Artificial Intelligence Conference in Seattle.
“We believe that transparency is a key,” he said. “How many features did we consider? Did we consider just these five? Or did we consider 5,000 and choose these five?”
Boston Dynamics’ Handle robot picks up and stacks boxes. (Boston Dynamics via YouTube)
Boston Dynamics’ latest robo-creature may be cuter than its creepy robot dogs, but its potential application could nevertheless make warehouse workers wary.
The Handle robot, demonstrated in a YouTube video posted on March 28, is a long-necked robot that looks a lot like a two-wheeled mechanical ostrich. The robot’s “head” features an arrangement of suction cups that can pick up boxes from a pallet, and then release them to make a neat stack.
Harry Shum is Microsoft’s executive vice president for AI and research. (GeekWire Photo)
Microsoft will “one day very soon” add an ethics review focusing on artificial-intelligence issues to its standard checklist of audits that precede the release of new products, according to Harry Shum, a top executive leading the company’s AI efforts.
Shum, who is executive vice president of Microsoft’s AI and Research group, said companies involved in AI development “need to engineer responsibility into the very fabric of the technology.”
White House tech adviser Michael Kratsios addresses scores of executives, experts and officials at a White House summit focusing on artificial intelligence in May 2018. (OSTP via Twitter)
For months, the White House has been talking up artificial intelligence as one of America’s most important tech frontiers. Now we’re starting to see some of the dollar signs behind the talk.
In newly released budget documents, the Trump administration says it wants to split $850 million in civilian federal spending on AI research and development between the National Science Foundation, the National Institutes of Health, the National Institute of Standards and Technology and the Energy Department.
Seattle University’s Tracy Kosa, the University of Maryland’s Ben Shneiderman and Rice University’s Moshe Vardi take questions during an AI policy workshop at the Allen Institute for Artificial Intelligence, moderated by AI2 CEO Oren Etzioni. (GeekWire Photo / Alan Boyle)
Do we need a National Algorithm Safety Board? How about licensing the software developers who work on critical artificial intelligence platforms? Who should take the lead when it comes to regulating AI? Or does AI need regulation at all?
The future of AI and automation, and the policies governing how far those technologies go, took center stage today during a policy workshop presented by Seattle’s Allen Institute for Artificial Intelligence, or AI2. And the experts who spoke agreed on at least one thing: Something needs to be done, policy-wise.
“Technology is driving the future — the question is, who is doing the steering?” said Moshe Vardi, a Rice University professor who focuses on computational engineering and the social impact of automation.
Oren Etzioni, CEO of the Allen Institute for Artificial Intelligence, answers questions during a chat moderated by Mike Grabham, director of the Seattle chapter of Startup Grind. (GeekWire Photo / Alan Boyle)
It may seem as if everyone’s already on the bandwagon for artificial intelligence and machine learning, with players ranging from giants like Amazon and Microsoft to startups like Xnor.ai and Canotic — but the head of Seattle’s Allen Institute for Artificial Intelligence, or AI2, says there’s still plenty of room to climb aboard.
“Let me assure you, if you have a machine learning-based startup in mind … you’re not late to the party,” AI2’s CEO, Oren Etzioni, told more than 70 people who gathered Feb. 26 at Create33 in downtown Seattle for a Startup Grind event.
Etzioni had a hand in getting the party started back in 2004, with the launch of a startup called Farecast that used artificial intelligence to predict whether airline fares would rise or fall. The company was acquired by Microsoft in 2008 for $115 million and has since faded into the ether. But Etzioni said the basic approach, which involves analyzing huge amounts of data to identify patterns and solve problems, is just hitting its stride.
The potential applications range from spam detection and voice recognition to health care, construction and self-driving cars.
“It’s really a versatile technology, and we’re going to see more and more startups based on machine learning,” Etzioni said.
