Diagnosing cancer is about to get more accurate, with the help of artificial intelligence. Pathologists have diagnosed diseases in more or less the same way for the past 100 years, by laboring over a microscope reviewing biopsy samples on little glass slides. Working almost robotically, they sift through millions of normal cells to identify just a few diseased ones. The task is tedious and prone to human error. But now, scientists and engineers have created a technique that uses artificial intelligence (AI) and can differentiate cancer cells from normal cells almost as well as a top-notch pathologist.

Yahoo has launched an application to make it easier for people to plan their next trip. Called Yahoo Radar, it brings the company's search, communication, and content areas together to help you research your destination. With elements that you'd find in Kayak, TripIt, and TripAdvisor, this iOS app pulls from a variety of sources, including your inbox, to curate information about any U.S. city. Billed as a virtual travel guide assistant, Yahoo Radar adds artificial intelligence and machine learning to bring you the best recommendations for restaurants, activities, and attractions on your trip. As it's just been released, the first version of the app only lets you do research -- you can't book flights or accommodations or make other reservations, or even deep-link into third-party apps.

MUNICH, Germany (Reuters) - Europe's growing army of robot workers could be classed as "electronic persons" and their owners liable to paying social security for them if the European Union adopts a draft plan to address the realities of a new industrial revolution. Robots are being deployed in ever-greater numbers in factories and also taking on tasks such as personal care or surgery, raising fears over unemployment, wealth inequality and alienation. Their growing intelligence, pervasiveness and autonomy requires rethinking everything from taxation to legal liability, a draft European Parliament motion, dated May 31, suggests. Some robots are even taking on a human form. Visitors to the world's biggest travel show in March were greeted by a lifelike robot developed by Japan's Toshiba and were helped by another made by France's Aldebaran Robotics.

Our inability to predict how people will interact with each other has led to many doomed relationships and awkward moments. But now MIT researchers have taught an algorithm to understand body language patterns in order to guess the next move between two individuals. Trained with YouTube videos and TV shows, it looks for outstretched arms, raised hands or prolonged stares to make predictions, which could help us avoid high-five fails and missed kisses. MIT researchers have taught an algorithm to understand body language patterns in order to guess the next move between two individuals. Researchers at MIT fed their predictive AI 600 hours' worth of videos so it could learn the next move of two characters – whether it would be a hug, kiss, handshake or high-five.

If you've ever seen a live robot manipulation demo, you've almost certainly noticed that the robot probably spends a lot of time looking like it's not doing anything. It's tempting to say that the robot is "thinking" when this happens, and that might even be mostly correct: odds are that you're watching some poor motion-planning algorithm try and figure out how to get the robot's arm and gripper to do what it's supposed to do without running into anything. This motion planning process is both one of the most important skills a robot can have (since it's necessary for robots to "do stuff"), and also one of the most time and processor intensive. At the RSS 2016 conference this week, researchers from the Duke Robotics group at Duke University in Durham, N.C., are presenting a paper about "Robot Motion Planning on a Chip," in which they describe how they can speed up motion planning by three orders of magnitude while using 20 times less power. How? Rather than using general purpose CPUs and GPUs, they instead developed a custom processor that can run collision checking across an entire 3D grid all at once.

Machine learning is at the top of the "hype curve" for emerging technologies and is one of the top 10 strategic technology trends for 2016 according to Gartner. A method of data analysis that automates analytical model building, machine learning can benefit almost any business that gathers data with the intention of acting upon it. It's safe to say that most of us are already interacting with machine learning applications on a daily basis, whether it's Apple's Siri, Facebook's face detection, Amazon and Netflix personalized recommendations, or iOS's autocorrect. What can we learn from this growing trend? What can we do with such a widely applicable technology and how can we maximize its potential?

The intelligence exhibited by machine also known as Artificial Intelligence is an area that very many large technology companies are investing into these days. Apple made its mark in artificial intelligence by introducing its digital assistant Siri, google and Microsoft also followed. Social media giants; Facebook and amazon have shown indications of investing in Artificial Intelligence. The interest of these companies in this field of computer science is an indicator that Artificial Intelligence is an area that offers a lot of promise. The country has tried to use AI in some areas for example KCCA introduced the smart traffic lights at Wandegeya.

It's going to be a pivotal year for artificial intelligence (AI). And 2016 began with British AI firms asserting dominance over the sector. In February, Southwark-based predictive keyboard company SwiftKey was purchased by Microsoft for 250 million ( 173m) – one of the highest exits ever for a UK company. Around a month later, another UK-made smart machine, DeepMind's AlphaGo, trounced professional player Lee Sedol in a five-game match of Go – an ancient and complicated board game – in a historic first. Within a few months, AI has stopped being fodder for futurists' conversations and charged headlong into the here and now. Advances in neural networks and machine learning, and the availability of vast data sets, are bringing about an AI surge that has just started gaining momentum.

The nonprofit group linked to Elon Musk and other Silicon Valley tech paragons wants to start with the basics -- household chores. Its No. 2 goal -- No. 1 being a decidedly more prosaic vow to measure its own progress in advancing artificial intelligence -- is to build a household robot, one to "perform basic housework," OpenAI said in a blog post this week. Sure, such a thing would be welcomed the world over. But what makes this future housemaid robot rank so highly among the group's ideas and experiments is that robotics in general is a "good testbed for many challenges in (artificial intelligence)," Open AI says. OpenAI dubs itself "a non-profit artificial intelligence research company" with the goal of advancing AI in ways most likely to benefit humanity, all the while uninhibited by the need to generate a profit.

Artificial intelligence nonprofit OpenAI, funded by some of the biggest names in Silicon Valley, announced its major goals today, which include the creation of a "general purpose" robot and a natural language processing chatbot. "We're working to enable a physical robot (off-the-shelf; not manufactured by OpenAI) to perform basic housework," the nonprofit said in a blog post authored by OpenAI Research Director Ilya Sutskever, OpenAI CTO Greg Brockman, Sam Altman, and Elon Musk. An agent, a system able to respond to user input like a bot, will be built with "the ability to carry a conversation, the ability to fully understand a document, and the ability to follow complex instructions in natural language." Another intelligent agent will be made to win games. Finally, OpenAI plans to identify or create a metric to measure its progress.