Researchers have made tremendous progress in recent times in the ability of machines to understand the nuances of our language. For instance, we've seen machines developed that are capable of understanding things such as empathy, sarcasm, humor, and a range of other emotions. This understanding has even been compiled together to have machines automate the speech writing process (although the speaking part remains a challenge). A recent international team believe that a simple crossword puzzle can help us to develop robots with even greater language processing capabilities. Their recent study hypothesizes that if we can develop machines capable of understanding crossword clues, then it will go a long way to helping them understanding the complexities of human language.

Toyota is going all in on Ann Arbor, Mich., as a global test site for connected cars to gather data for research into autonomous driving and safety applications. In partnership with the University of Michigan's Transportation Research Institute, Toyota's goal is to equip 5,000 cars with information-gathering boxes that communicate wirelessly with similar vehicles and infrastructure such as traffic signals, the company said in a statement today. The effort does not include Google-style autonomous cars sometimes seen on the streets of California and the Southwest. Rather, regular drivers will be recruited to have a small box installed in the rear of their vehicles along with two small antennas on the trunk or the roof. The drivers will make their normal rounds.

The fear of job loss due to automation is no longer relegated to only physical-labor manufacturing jobs and relatively simple transaction-based, customer-service workers (i.e., bank tellers, grocery store clerks, and travel agents). Companies are increasingly adopting sophisticated "cognitive" technologies across a new swath of knowledge-worker jobs in fields such as finance, health care, and insurance. However, figuring out what this increased adoption rate really means seems elusive. Special reports and articles from respected economists and IT professionals present divergent and ambiguous views concerning whether or not automation will displace millions of knowledge workers. In a recent New York Times Magazine article, "The Robots Are Coming for Wall Street," executives from Goldman Sachs and Barclays bemoaned and praised a growing trend of financial analysts becoming displaced by smarter, big data-oriented software.

Your math teacher lied to you. Sometimes getting your sums wrong is a good thing. So says Joseph Bates, cofounder and CEO of Singular Computing, a company whose computer chips are hardwired to be incapable of performing mathematical calculations correctly. Ask it to add 1 and 1 and you will get answers like 2.01 or 1.98. Pentagon research agency DARPA funded the creation of Singular's chip because that fuzziness can be an asset when it comes to some of the hardest problems for computers, such as making sense of video or other messy real world data. "Just because the hardware is sucky doesn't mean the software's result has to be," says Bates.

The data consists of a sample of Australian Sign Language signs performed by volunteers. There are 95 unique signs, each recorded 27 times on different days. The data was recorded using two Fifth Dimension Technologies (5DT) gloves (one for each hand) and two Ascension Flock-of-Birds magnetic position trackers. Together, this produced 22 channels of data, 11 for each hand. These channels included x, y and z position, roll, pitch and yaw movements and finger bend measurements for each finger.

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Google just expanded its free software for creating smart, self-learning computers. The company added the ability to run this software, known as TensorFlow, across a network of many computers -- the same way that Google uses it for its own operations. This means that anyone with access to a bunch of computer servers can create their own smart computer that can basically program itself. Set the computer program up with whatever it is you want it to learn. Give it a bunch of data to study and then the computer knows how to do things that, until now, only humans could do like talk, recognize pictures, draw, etc.

DUBAI – The teaching methods of Kazuya Takahashi, 35, using Lego blocks and speaking entirely in English, may not be the norm in the Japanese education system. But on a global level, the educator, who teaches at the Kogakuin junior high and high schools in Hachioji, western Tokyo, is considered ahead of the game and has won recognition for his efforts to promote global citizenship. His methods may provide clues as to where education should be heading in Japan, a nation often criticized for focusing more on cramming knowledge rather than encouraging critical thinking. At the Global Education and Skills Forum in Dubai, which ran for two days from March 12, Takahashi gave a presentation as one of the 10 finalists for the Global Teacher Prize, known in the industry as the Nobel Prize in education. The event was attended by around 1,600 people from 110 nations.

Elon Musk has not been shy about his concerns over artificial intelligence turning evil. So it wasn't a surprise in December when Musk announced the formation of OpenAI, an open-source, non-profit focused on advancing "digital intelligence in the way that is most likely to benefit humanity as a whole." That's all well and good, but not much has been revealed about what exactly OpenAI is working on. OpenAI's co-founder and CTO Greg Brockman told Tech Insider that OpenAI is primarily focusing on advancing machine learning, which is the technology that enables computers to learn how to complete tasks through experience. Specifically, the company is focusing on two key types of machine learning that every major tech company is investing in right now.

Google announced the new feature yesterday, on the day that Google Calendar turned 10. The feature works by looking at a user's existing schedule in Calendar and identifying windows of time that can accommodate personal goals. Goals was developed with the help of Duke University behavioral economist Dan Ariely, whose time-management app company, Timeful, was acquired by Google last year. Ariely told The New York Times that the new Calendar feature was designed as a "tool to help us against ourselves, and all the short-term things we agree to do in our calendar." Research has shown that people are more likely to achieve goals if they track their progress regularly.