Intellectual Property (IP) defines intangible inventions that are a result of creativity, and increasingly is linked to new technology innovations. In a digital age, it's important to manage IP effectively and capitalize on the commercial value. The opportunity to commercialize IP in the Artificial Intelligence (AI) space has never been higher: in January, the UN's World Intellectual Property Organization (WIPO) highlighted the rapid increase in AI patent applications worldwide. More than half of the 340,000 inventions patented had taken place since 2013. Without a patent or legally enforceable IP protection, it is very difficult to commercialize an invention or idea - it undermines investment, research and development and growth opportunities.

University of Waterloo researcher Alexander Wong didn't have enough processing power for his computer vision startup, so he developed a workaround. That workaround is now the company's product. Ontario-based DarwinAI, founded by a team from the Ontario-based university, provides a platform for developers to generate slimmed-down models from neural networks. This offers a quicker way for developers to spin out multiple networks with smaller data footprints. The company's lean models are aimed at businesses developing AI-based edge computing networks to process mountains of sensor data from embedded systems and mobile devices.

A machine learning algorithm could automate the way toward annotating training datasets for predictive analytics tools, a promising progression as certain datasets become progressively huge. Created by analysts at Massachusetts Institute of Technology (MIT), the model automatically learns highlights predictive of vocal cord issues and could help create strategies to anticipate, analyze, and treat the disorder. Training datasets regularly comprise of many wiped out and healthy subjects, yet with moderately little data for each subject. Experts must discover those viewpoints or features in the datasets that will be significant for making forecasts. MIT computer researchers are hoping to quicken the utilization of artificial intelligence to improve medical decision-making, via mechanizing a key step that is generally done by hand and that is winding up increasingly difficult as certain datasets develop ever-bigger.

The founders of Vise AI met when they were 13, a couple of teenagers more interested in applied artificial intelligence than English class. Fast-forward several years and the pair has relocated from the Midwest to San Francisco to raise money for a financial technology business they've been self-funding since 2016. As teenagers with an inordinate amount of AI knowledge, Samir Vasavada and Runik Mehrotra proved to be quite useful to large businesses, investment bankers and other financiers. Leveraging their AI know-how, they were paid $700 per hour by a consulting firm to teach financial "experts" about AI. Mehrotra, according to Vasavada, is a mathematical prodigy: "And that translates extremely well to AI, right, because what underlies AI is math," Vasavada, co-founder and chief executive officer of Vise AI, tells TechCrunch.

Engineers at Tokyo-based company Seven Dreamers started developing a laundry-folding robot called Laundroid in 2005, and now, there is finally a robot to show off at CES 2018. We haven't seen it in person yet, but we spoke with Seven Dreamers CEO Shin Sakane for a preview. The idea is: You drop clean, dry clothes into a box in a pretty home appliance, and then several hours later you can collect the folded, sorted items. "Soft material like clothing is one of the hardest problems for AI even now," Sakane says. "Laundry folding seems like an easy task but it's actually very hard, so that's why no one has ever done it before."

About 3.85 million people studied Japanese at a record 18,604 institutions overseas in fiscal 2018, with the number of institutions soaring in Asia, according to a survey released this week. The number of Japanese language institutions jumped nearly fourfold to 818 in Vietnam from the previous survey in fiscal 2015 and nearly tripled to 400 in Myanmar, said the survey by the Japan Foundation, a government-backed organization conducting international cultural exchange programs. The number of Japanese learners overseas rose 5.2 percent to 3,846,773, led by a 169.0 percent surge to 174,461 in Vietnam, it said. The survey found a record high 142 countries and territories offering Japanese language education, five more than the fiscal 2015 level. The five include East Timor, Zimbabwe and Montenegro.

It's 2019 and I have been alone for most of my adult life. As I get older, and because I am male, my loneliness is generally going to increase. If I lose my job chances are that I will become even more socially isolated. Compared to women, I'm three times more likely to take my own life because of loneliness and less likely to talk about it with anyone. But writing is my companion, it's my "talk-to".

Education systems face a multitude of challenges in today's fast-moving world. Teacher workload is ever-increasing, while delivering personalised lessons to students and fostering their critical thinking skills are crucial but elusive goals. Many people lack access to high-quality learning materials and qualified professors. Fortunately, technologies such as artificial intelligence (AI) can provide schools with much needed assistance, and companies have developed smart algorithms that refine educational experiences in many different ways. Whether through personalised learning and smart content or through transcribing words and improving cognitive performance, AI-driven tools are transforming the way children learn and develop new skills.

The lighter your skin, the better AI-powered facial recognition systems work for you. The UK Home Office knows this, because the government's been briefed several times on the problem. And a recent report shows that it knew it was developing a passport program built on biased, racist AI. The UK's passport program went live in 2016. It uses an AI-powered facial recognition feature to determine whether user-uploaded photos meet the requirements and standards for use as a passport photo.

Internet of Things (IoT) is developing as a massive innovation informing the future by associating physical gadgets or things with the internet. It additionally displays different open doors for the convergence of other innovative patterns, which can enable it to turn out to be much increasingly canny and competent. IoT goes past regular machine-to-machine correspondence and enlarges the canvas by offering the expanded network of gadgets and the capacity to work over an assortment of conventions and applications. These gadgets can likewise gather data autonomously and proactively trade information and data with other "keen" gadgets associated with a system. They are regularly implanted in a bigger plan of things, and the interconnection between numerous devices is prompting a progression in many fields.