Facebook on Monday began using artificial intelligence to help people with visual impairments enjoy photos posted at the leading social network. Facebook introduced machine learning technology trained to recognize objects in pictures and then describe photos aloud. "As Facebook becomes an increasingly visual experience, we hope our new automatic alternative text technology will help the blind community experience Facebook the same way others enjoy it," said accessibility specialist Matt King. The feature was being tested on mobile devices powered by Apple iOS software and which have screen readers set to English. Facebook planned to expand the capability to devices with other kinds of operating systems and add more languages, according to King, who lost his vision as a US college student studying electrical engineering.

It doesn't really have a name, and not much of a personality. But a robot created by Aviano middle and high schoolers performed well enough to qualify for the FIRST Tech Challenge World Championships. At a recent competition in Prague, the robot flipped over three times, said Julia Markel, the lead programmer on the 13-member team, which calls itself Robotica Santi Robotics Club. But it rallied enough to achieve one of the team's top goals: climb up a ramp and do a pull-up. "We were one of the only teams that were able to do that," said Dave Izzo, the club's adviser.

Are you struggling to find the right resources to guide you in your machine learning journey? Sign-up for the Machine Learning Resource Guide and you'll get a hand-picked list of the best resources for Machine Learning. In addition, you'll get 2-to-3 short, educational emails every week with actionable advice on how to further your study of Machine Learning. Yes, I want the best resources for Machine Learning (free)! I want to get started with Machine Learning Algorithms! Gentle introduction to 10 top machine learning algorithms and 12 tutorials to implement them step-by-step from scratch.

In this challenge we want you to take data from the world around you and turn it into shared learnings. For example, you might take College Scorecard Data and help high school students mathematically determine where they should go to college. Additionally, robots are data generating machines (literally). You might use this challenge to collect data from your wheels and drive train, and then use it to automatically switch gears based on different surfaces. You might use it for predictive maintenance.

Hand gestures, like pointing and waving, could one day be used to command the Apple Watch. A new patent revealed that the Cupertino company may be working on a variety of sensors to detect and interpret hand gestures. Images shown in the application also suggest the wearable device could detect sign language and the paired iPhone would convert it to speech or text. A new patent revealed that the Cupertino company may be working on a variety of sensors to detect and interpret hand gestures. 'Based on the detected movements, a user gesture can be determined.

With a number of recent Hollywood films representing intelligent machines as either hero or villain, the subject of Artificial Intelligence (AI) has attracted the imagination of the media and popular culture. On the practical engineering side, over the past decade humanity's age-old dream of developing intelligent machines has experienced rapid development. The prospect of expert systems being increasingly able to outperform humans in a growing set of disciplines has led to deep soul-searching concerning the evolving future of labor. Meanwhile, cognitive computing platforms such as IBM's Watson are demonstrating a powerful ability to support and guide humans in complex activities as diverse as oncology diagnostics, investment management, biomedical research, and even the introduction of novel culinary recipes as Chef Watson.

The power of artificial intelligence is beyond our imagination. We all know robots have already reached a testing phase in some of the powerful countries of the world. Governments, large companies are spending billions in developing this ultra-intelligence creature. The recent existence of robots have gained attention of many research houses across the world. Does it excite you as well? Personally for me, learning about robots & developments in AI started with a deep curiosity and excitement in me! Let's learn about computer vision today. The earliest research in computer vision started way back in 1950s.

The world's first social robot went on show at the South by Southwest (SXSW) function in Austin on Saturday. JIBO has been specifically designed to serve in the home, offering various useful functions which accommodate to a domestic setting, including home security, storytelling and entertainment. Commenting on the robot's qualities, software developer Jonathan Ross said that "JIBO is a social robot for the home he can recognise you by your face by your voice" adding that "he can understand what you are saying and it can talk back to you." He went on to explain that humans "are hard wired to be responsive to social interactions. So by having a piece of hardware that actually acts like a person and can acknowledge you and can have a social presence, we can tap into that."

It's by now a given that one of the best ways to eat better, whether that means consuming less calories and-or more vegetables and-or whatever, is to just actually pay attention to what we eat. This is the big secret behind dieting--any old fad diet is probably going to have a positive effect simply because the dieter is paying more attention to what they put into their face. And just by virtue of paying attention, they will probably eat healthier. The fad diet usually gets the credit, but just caring at all goes a very long way. Paying attention is hard, however.

In the late 00's some clever academics rebranded a subset of neural network techniques to'Deep Learning', which just means a stack of different nets on top of one another, forming a sort of computationally-brilliant lasagne. When I say'machine learning' in this blogpost, I'm referring to some kind of neural network technique.) Robotics has just started to get into neural networks. This has already sped up development. This year, Google demonstrated a system that teaches robotic arms to learn how to pick up objects of any size and shape.