A robot manipulated by a glove & it only cost them $150 USD.
Computer engineering students Mohammad Zyoud, Mohammad Atiyyeh and Suhaib Tawafsheh spent eight months working on the self-funded project which cost them around 150 USD.”
Category: robotics/AI – Page 2458
Interesting article in how folks are trying to do more work on personalizing robots to people’s moods; etc.
How you look at a robot and how it looks at you can make you more comfortable.
Definitely, we’re already seeing the research releases on microbots.
A famed futurist who foresees a day when and human and artificial intelligence merge and nanobots battle disease spoke to CBC’s Duncan McCue about what lies ahead.
Self driving cars to reach a $4bil revenue target within 10 yrs.
The White House wants to spend nearly $4 billion on self-driving cars, a move some experts say could help put extra horsepower behind autonomous vehicles and have them cruising America’s streets within the next 10 years.
“That is a serious amount of money,” Wendy Ju, executive director of Stanford’s Center for Design Research, told NBC News.
If those dollars make it into the budget, the money would be used for “pilot programs to test connected vehicle systems in designated corridors throughout the country,” according to the Department of Transportation.
Artificial intelligence researchers at Google DeepMind are celebrating after reaching a major breakthrough that’s been pursued for more than 20 years: The team taught a computer program the ancient game of Go, which has long been considered the most challenging game for an an artificial intelligence to learn. Not only can the team’s program play Go, it’s actually very good at it.
The computer program AlphaGo was developed by Google DeepMind specifically with the task of beating professional human players in the ancient game. The group challenged the three-time European Go Champion Fan Hui to a series of matches, and for the first time ever, the software was able to beat a professional player in all five of the games played on a full-sized board. The team announced the breakthrough in a Nature article published today.
Google has achieved one of the long-standing “grand challenges” of AI, building a computer capable of beating expert players of the board game Go.
Google DeepMind
Posted in entertainment, robotics/AI
The list of uniquely human achievements has just become shorter: Google’s AI has defeated the reigning 3-time European Go champion.
DeepMind’s program AlphaGo, masters the ancient game of Go. First ever program to defeat a human professional player!
In a paper published in Nature on 28th January 2016, we describe a new approach to computer Go. This is the first time ever that a computer program “AlphaGo” has defeated a human professional player.
The game of Go is widely viewed as an unsolved “grand challenge” for artificial intelligence. Games are a great testing ground for inventing smarter, more flexible algorithms that have the ability to tackle problems in ways similar to humans. The first classic game mastered by a computer was noughts and crosses (also known as tic-tac-toe) in 1952. But until now, one game has thwarted A.I. researchers: the ancient game of Go.
Despite decades of work, the strongest computer Go programs only played at the level of human amateurs. AlphaGo has won over 99% of games against the strongest other computer Go programs. It also defeated the human European champion by 5–0 in tournament games, a feat previously believed to be at least a decade away. In March 2016, AlphaGo will face its ultimate challenge: a 5-game challenge match in Seoul against the legendary Lee Sedol—the top Go player in the world over the past decade.
This video tells the story so far…
As recently as this month, top AI experts outside Google questioned whether such a victory could be achieved anytime soon.
Wise Autoresponse for your Customer Support Call Center needs — I do know that one of the large financial institutions in NYC announced in Dec. that they were replacing their tier 1 & tier 2 support with AI this summer.
BERKELEY, CA — (Marketwired) — 01/27/16 — Wise.io, which delivers machine learning applications to help enterprises provide a better customer experience, today announced the availability of Wise Auto Response, the first intelligent auto reply functionality for customer support organizations. Using machine learning to understand the intent of an incoming ticket and determine the best available response, Wise Auto Response automatically selects and applies the appropriate reply to address the customer issue without ever involving an agent. By helping customer service teams answer common questions faster, Wise Auto Response removes a high percentage of tickets from the queue, freeing up agents’ time to focus on more complex tickets and drive higher levels of customer satisfaction.
“Wise Auto Response has dramatically eased the burden on our support agents, allowing us to reply to half of all tickets automatically,” said Francesca Noli, VP of Marketing at Product Madness. “Now we are able to focus agent attention on more complex, customer-facing issues like payment problems, which have a direct impact on our bottom line. Wise gives us the best of both worlds: it has the power of an artificial intelligence system like Watson, along with the lightweight integration we need to successfully apply machine learning to our service operations quickly, easily and cost effectively.”
Wise Auto Response identifies common customer inquiries that can be responded to with a high level of confidence — such as password resets and basic product functionality, or standard “thank you” email templates that don’t require hands-on follow up — and automatically responds without the need for any manually written business rules. The new functionality complements the current suite of predictive applications offered by Wise.io, including Wise Routing, which automates the support ticket triage process, and Wise Recommended Response, which provides a ranked shortlist of appropriate macros and templates for each new customer inquiry.