The research was commissioned by Liam Byrne, the former Labour cabinet minister, as part of a gathering of MPs, academics, business leaders, trade unions and civil society leaders focused on addressing the problem.
World leaders urged to act as anger over inequality reaches a ‘tipping point’
Michael Savage Policy editor.
Sat 7 Apr 2018 08.08 EDT Last modified on Sat 7 Apr 2018 18.10 EDT.
Above all, the government needs to understand what AI is and what it will do. Since artificial intelligence is such a complex and fast-moving field, it is especially important for experts to be brought in to brief policymakers and the administration. Without technical acumen, it will be a challenge to act effectively in any area relevant to AI.
Government indifference toward AI could let the US lose ground to rival countries. But what would a good AI plan actually look like?
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Houston-based Orion Span hopes to launch the “first luxury hotel in space” — the 35-by-14-foot Aurora Station — by late 2021 and bring guests on board the following year.
Why does everyone assume that the AI revolution will either lead to a fiery apocalypse or a glorious utopia, and not something in between? Of course, part of this is down to the fact that you get more attention by saying “The end is nigh!” or “Utopia is coming!”
But part of it is down to how humans think about change, especially unprecedented change. Millenarianism doesn’t have anything to do with being a “millennial,” being born in the 90s and remembering Buffy the Vampire Slayer. It is a way of thinking about the future that involves a deeply ingrained sense of destiny. A definition might be: “Millenarianism is the expectation that the world as it is will be destroyed and replaced with a perfect world, that a redeemer will come to cast down the evil and raise up the righteous.”
Millenarian beliefs, then, intimately link together the ideas of destruction and creation. They involve the idea of a huge, apocalyptic, seismic shift that will destroy the fabric of the old world and create something entirely new. Similar belief systems exist in many of the world’s major religions, and also the unspoken religion of some atheists and agnostics, which is a belief in technology.
AUSTIN — At SXSW 2018, artificial intelligence (AI) was everywhere, even in the sessions that were not specifically about the subject. AI has captured the attention of people well outside the technology space, and the implications of the technology are far-reaching, changing industries, eliminating many human jobs, and changing the nature of work for most of us going forward. I expect that an AI bot could write this article within 10 years — and likely much sooner — simply by ingesting all the information from the sessions I attended, coupled with an ability to research related information on the internet much better than I could.
Interestingly enough, as Ray Kurzweil pointed out in his talk here, the term “artificial intelligence” was coined at a summer workshop at Dartmouth in 1956 attended by computing pioneers such as Marvin Minsky and Claude Shannon, at a time when computers still ran on vacuum tubes and computers in the world numbered in the hundreds.
While we have a handle on what constitutes artificial intelligence in computers today, what constitutes intelligence in humans is still not completely agreed upon. We have some 100 billion neurons in our brains, and those neurons can make 100 trillion connections, which certainly outstrip any computer today. Those connections allow us to identify things, make decisions, use and understand language, and many other things that a computer has a hard time doing – for now.
“Although smartphones and tablets are ubiquitous, many of the companies that make our everyday consumer products still rely on paper trails and manually updated spreadsheets to keep track of their production processes and delivery schedules,” says Leyuan Shi, a professor of industrial and systems engineering at the University of Wisconsin-Madison.
That’s what she hopes to change with a research idea she first published almost two decades ago.
During the past 16 years, Shi has visited more than 400 manufacturing companies in the United States, China, Europe, and Japan to personally observe their production processes. “And I have used that insight to develop tools that can make these processes run much more smoothly,” she says.
