A cognitive sciences research duo out of Università di Padova, in Italy, have succeeded in building an artificial intelligence network that has through repetition, learned to identify relative group sizes, without counting. Ivilin Stoianov and Marco Zorzi describe in their paper published in Nature Neuroscience, how they built an AI system capable of approximate number sense (ANS). ANS is the ability of living beings to estimate with reasonable accuracy the differences in sizes of different groups. Fish, for example, demonstrate an ability to join the larger of two schools without having to count. Getting a computer to do the same has until now, never been done.

Like many kids, Antonio Torralba began playing around with computers when he was 13 years old. Unlike many of his friends, though, he was not playing video games, but writing his own artificial intelligence (AI) programs. Growing up on the island of Majorca, off the coast of Spain, Torralba spent his teenage years designing simple algorithms to recognize handwritten numbers, or to spot the verb and noun in a sentence. But he was perhaps most proud of a program that could show people how the night sky would look from a particular direction. Or you could move to another planet, and it would tell you how the stars would look from there, he says.

How do you use a scientific method to measure the intelligence of a human being, an animal, a machine or an extra-terrestrial? So far this has not been possible, but a team of Spanish and Australian researchers have taken a first step towards this by presenting the foundations to be used as a basis for this method in the journal Artificial Intelligence, and have also put forward a new intelligence test. "We have developed an'anytime' intelligence test, in other words a test that can be interrupted at any time, but that gives a more accurate idea of the intelligence of the test subject if there is a longer time available in which to carry it out", José Hernández-Orallo, a researcher at the Polytechnic University of Valencia (UPV), tells SINC. This is just one of the many determining factors of the universal intelligence test. "The others are that it can be applied to any subject whether biological or not at any point in its development (child or adult, for example), for any system now or in the future, and with any level of intelligence or speed", points out Hernández-Orallo.

Göteborg University ANNIMAB Society ANN in information intensive health care In the first phase of the project we will try to further knowledge and competence concerning ANN and related analytical methods. Later, these methods will be applied to selected medical problem areas where the amount and kind of available data require unconventional approaches. Examples are extraction of 3-D information from NMR (nuclear magnetic resonance) images, prognostication in neurosurgical intensive care, improved heart infarctation diagnosis with electrocardiography (ECG) and methods to determine the cause of fever in patients who are being treated for blood malignancies.

Xerox Corp. researchers have developed a search tool that tries to understand documents, rather than looking for keywords, in order to provide better results. The tool, FactSpotter, analyzes the underlying grammar of a text in order to infer additional information, such as whether ambiguous words are being used as nouns or verbs, or to whom a pronoun refers, said Fridirique Segond, who manages the parsing and semantics research group at Xerox Research Center Europe near Grenoble, France. The analysis allows the software to understand that references to "Bill Gates", "he" and "the head of Microsoft" in the same document likely refer to the same person. But the software should also be able to tell that "Bill Gates said ... " and "A friend of Bill Gates said ..." do not precede words spoken by the same person, a situation that would likely lead search engines using keyword analysis alone to return irrelevant results. One of the first groups to use FactSpotter will be Xerox Litigation Services, which next year will build it into a suite of "e-discovery" software for the legal profession, Segond said.

Amazon is always on the lookout for new robotic technologies to improve efficiency in its warehouses, and this year deep learning appears to be leading the way. That's according to the results of the second annual Amazon Picking Challenge, which has been won by a joint team from the TU Delft Robotics Institute of the Netherlands and the company Delft Robotics. Amazon's 2016 event was held in conjunction with Robocup 2016 in Leipzig, Germany. Two parallel competitions took place: a Pick Task much like last year's, in which a mix of items has to be lifted from warehouse shelves and packed into a container; and a new "Stow Task," which involves taking items out of a tote and putting them onto the shelves. The Pick Task asked contestants to pick up and safely deposit 12 items from a mixed shelf into a container in the shortest possible time.

Microsoft has published the source code for its Project Malmo, allowing anyone to conduct artificial intelligence experiments in the world of Minecraft with a little programming. It unveiled the project, then known as AIX, back in March, but at the time only a few academics had access to the code. On Thursday the company made good on its promise to open up the source code by publishing it on Github. Minecraft, the blocky world-building game that Microsoft paid $2.5 billion for two years ago, is an ideal place to test how artificial intelligences will interact with one another and with humans. As it's a simulation, Minecraft is a safe place to test how AIs learn to perform certain kinds of physical tasks: In Minecraft, a rogue machine or runaway car can hurt no one.

When introducing its monster 72-core Xeon Phi chip, Intel couldn't help but take a swipe at graphics processors for being sluggish for some tasks. Ironically, Xeon Phi is a byproduct of Larrabee, which was supposed to be Intel's first major GPU but was abandoned in 2009 after multiple delays. The swipe was a shot at Nvidia, whose GPUs are flourishing in the gaming and machine learning areas. But Nvidia's success has also raised questions about whether Intel should've been patient and pursued Larrabee. Nevertheless, Xeon Phi has been successfully used in supercomputing, and now Intel wants to challenge Nvidia's GPU by bringing the chip to machine learning.

Robots can paint, but when it comes to writing, they shouldn't quit their day jobs. That's the combined conclusion from results of two contests announced this week. On the upside, artificial intelligence created some pretty impressive works for RobotArt.org's The contest challenged artists and engineers to create a robot that painted like a real artist. Essentially, the aim was to get "as many teams as possible to set up a robot that can do any sort of painting," the contest site explains.

In another sign that Japan loves cute robots, SoftBank's Pepper is proving to be a hit with its consumer launch. The mobile carrier said 1,000 units of the household robot sold out in one minute on Saturday, its first day of consumer sales. The humanoid machine is designed to be a personal robot and a member of the family. It can't do housework, but it can converse, recognize people's emotions, develop its own "feelings" and retrieve information from the Internet such as messages and weather forecasts. SoftBank describes Pepper as the world's first personal robot that has its own emotions. Most of the Peppers were purchased online Saturday, but 30 units were ordered through a drawing held Friday at a SoftBank shop in Tokyo.