Google has released a paper on AI safety in collaboration with researchers from Stanford University, University of California, Berkeley and OpenAI.

Researchers have developed a series of AI-based systems that can interpret pathology images and identify the presence and absence of metastatic cancer. The AI systems could lead to new and improved diagnostic methods and treatment. A group of researchers from Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School in Boston have teamed up to develop new diagnostic methods based on artificial intelligence (AI). Humayun Irshad, PhD research fellow at Harvard Medical School and one of the lead authors on the research, says that their group is using all kinds of different computational methods to improve diagnostic techniques. "We are developing robust and efficient computational methods to improve diagnostic and prognostic assessment of pathological samples," Irshad says.

As we all know, Google is constantly looking to provide more relevant results for its users -- hence, the regular algorithm updates that frequently frustrate webmasters and anyone else's SEO efforts. The Pagerank algorithm that founders Sergey Brin and Larry Page introduced in the early days of Google was a step in the right direction, but it certainly wasn't the ultimate solution for improving the quality of search results. In fact, the search giant recently unveiled a new AI (yes, that stands for artificial intelligence) called RankBrain to help the engine better understand the queries users type into the search field. The real intention of this AI wasn't to change visitors' search engine results pages (SERPs) -- rather, it was to predict them. As a machine-learning system, RankBrain actually teaches itself how to do something instead of needing a human to program it.

Machine learning started out as the idea of giving a machine human intelligence. The discipline was originally intertwined with artificial intelligence (AI), as scientists wove together the fields of computer science, mathematics, statistics, probability, expert systems and neural networks. The original benchmark for machine learning and artificial intelligence was the Turing Test, created by British mathematician and computer scientist Alan Turing. "A computer was said to be able to'thin' if a human interrogator could not tell it apart, through conversation, from a human being". Since then, machine learning has been reorganized as a separate field from AI, with the aim of finding solutions to solvable problems using methods based in statistics and probability theory.

The FBI has access to nearly 412 million photos in its facial recognition system--perhaps including the one on your driver's license. But according to a new government watchdog report, the bureau doesn't know how error-prone the system is, or whether it enhances or hinders investigations. Since 2011, the bureau has quietly been using this system to compare new images, such as those taken from surveillance cameras, against a large set of photos to look for a match. That set of existing images is not limited to the FBI's own database, which includes some 30 million photos. The bureau also has access to face recognition systems used by law enforcement agencies in 16 different states, and it can tap into databases from the Department of State and the Department of Defense.

The magic of data from multiple sources, known as crowdsourcing, extends to apps, artificial intelligence and large-scale studies, among other advancements. While sourcing input data and sourcing processing grunt are two completely different endeavors, the kernel of an idea at the core is the same; teamwork. In the halls of MIT, long a bastion of scientific and technological breakthroughs and the minds that create them, the spirit of teamwork is alive and well in more ways than one. A team of researchers have decided to create an eye tracking system for smartphones, but rather than calling participants to the lab to let the robot scope out their eyeballs in action, they decided to allow just about anybody to jump in through the use of a special iOS app. This, and a push on Amazon's Mechanical Turk, has resulted in oodles of data from over 1,500 people, as opposed to the normal 50 or so that such a study normally draws in.

Accenture's technology R&D head urges China to scale up smart machine trials at home and abroad, Chen Yingqun and Zhang Xia report. China should step up its efforts to adopt artificial intelligence in its industries to boost the country's economic transformation, according to French technology expert Marc Carrel-Billiard. The development of artificial intelligence is a hot topic in China, he said, especially since the central government unveiled the Made in China 2025 strategy, which largely aims to upgrade the manufacturing industry with high-technology over the next decade. AI refers to machines or systems that can understand, learn and act independently, allowing them to take on cognitive functions otherwise performed by a human, such as problem-solving. Carrel-Billiard said such technology is important due to the shift toward greater connectivity, either through cloud computing or smart networks.

The fact that Catherine - who's learned that her ex-husband Theodore has taken up with Samantha, a honey-voiced Operating System who screens his emails, entertains his fantasies and sends his writing off to publishers - comes off as judgmental is testament to Jonze's filmmaking skills. But it's also proof of how deeply we've internalised the notion that artificial intelligence is an extension of male desires and that, really, few things may be hotter than the hard-to-nail promise of female servitude. As Laurie Penny writes in an April 2016 article in The New Statesman, the issue of whether or not robots are slaves designed to serve their masters or sentient beings with inner lives and autonomous instincts has long paralleled the questions we ask of women in the world. READ MORE: * New Zealand could become first country to use Domino's pizza delivery robot * Drones, self-drive cars and'car butler' in our near future * Professor hopes robots will take over the rehabilitation world * Robots could threaten up to half New Zealand's jobs in next 20 years * Robots fooling humans they love something that can't love them back: AI expert * Self-learning robot escapes Russian facility, disrupts traffic * New robot from Google shows off human-like qualities Robots may take on domestic tasks and give working mothers more time. From Metropolis, the 1927 Fritz Lang classic in which Maria, a cyborg whose sultry ways plunge the city and its workers into chaos (she's later burned at a stake) to Austin Powers: International Man of Mystery, the hit 1997 spy film whose comely fembots are programmed to ensnare the bumbling Powers with his own libido, female robots are often cast as temptresses or destroyers, coincidentally enough, the same roles reserved for flesh-and-blood women.

Massachusetts … of the robotics institute at Carnegie Mellon University in Pittsburgh, who was not involved in the MIT study, called it "an important work." "Some argue that prediction is a central part of (artificial) intelligence," Hebert …… Read More MIT's artificial intelligence passes key Turing test An MIT algorithm has managed to produce sounds able to fool human listeners and beat Turing's sound test for artificial intelligence. Researchers from the Massachusetts Institute of Technology are using Alan Turing's tests, developed in the 1950's … According to a new paper, researchers at the University of Georgia and the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory have developed a piece of software capable of turning almost any smartphone into … Massachusetts … of the robotics institute at Carnegie Mellon University in Pittsburgh, who was not involved in the MIT study, called it "an important work." "Some argue that prediction is a central part of (artificial) intelligence," Hebert … Researchers from the Computer Science and Artificial Intelligence Laboratory (CSAIL) at Massachusetts Institute of Technology (MIT) demonstrated an algorithm that was able to view silent video clips and accurately predict realistic sounds that might appear.

That's one of the questions animating the field of computational creativity, which seeks to design artificial intelligence that can replicate human creativity. We wrote recently about a Google effort to create algorithms that make original music. But what if artificial intelligence could design and make 3D objects you could actually hold in your hand? That was the challenge that Joel Lehman, an assistant professor at the IT University of Copenhagen, set out to tackle. Lehman wondered if he could somehow leverage the remarkable image recognition power of deep neural networks (DNN) to create new artifacts without human input.