Perhaps the science textbooks of the future will add a new step to the scientific method: "consult with AI." That's because scientists are using artificial intelligence to help them design brand-new materials that solve human challenges like never before. A team of materials scientists at TU Delft University in the Netherlands have created a new material that is super-compressible, yet durable.. In materials science, researchers are looking for novel geometries in design that are able to be created in real life, while also ensuring those solutions aren't just random. They have to be interesting in some way. "If you change the geometry of the material, it will not do what you want it to do. It breaks or it bends in a different way, it doesn't do what you want," Miguel Bessa, one of the authors of the new paper published in Advanced Materials, told Popular Mechanics.

Going by the pains and frustrations of economic headwinds, most people tend to dismiss it as another wasted year. In this milieu, we tend to overlook the tremendous significance of 2018-19 as an inflection point in workforce composition. Those born at the dawn of the new millennium have turned 18 and are at the threshold of the job market. Their share in the workforce is bound to increase over the next decade. The ability of the cohorts to absorb technology changes and the associated cultural implications is getting sharper with each succeeding generation.

TECHNOLOGICAL innovations, artificial intelligence, virtual reality may be changing the landscape of the tourism industry, but the Filipino brand of hospitality and customer service will never go out of style. This was the message of Undersecretary for Tourism Regulation, Coordination and Resource Generation (TRCRG) Arturo Boncato Jr. of the Department of Tourism (DOT) in his keynote address at the recent 5th Tourism Human Resource Congress in Baguio City. "Tourism is bigger than artificial intelligence. Tourism is bigger than robotics. The quest for quality is something that only human beings could give," he stressed.

Artificial Intelligence has already become a widespread technology, solving a large number of tedious tasks of enterprises. Looking at its capabilities, this year marked the biggest year in funding for AI ventures yet. The Q2 of 2019 saw a total investment of US$7.4 billion in AI startups, largely going to transportation and healthcare companies. Let's have a look at the top 10 AI investments that took place in October 2019. Brightfield, a New York City-based AI and Big Data analytics company, optimizes contract labor spend and program performance for employers, MSPs, and staffing firms earlier this month received US$53 million in early-stage funding round.

Artificial Intelligence has already become a widespread technology, solving a large number of tedious tasks of enterprises. Looking at its capabilities, this year marked the biggest year in funding for AI ventures yet. The Q2 of 2019 saw a total investment of US$7.4 billion in AI startups, largely going to transportation and healthcare companies. Let's have a look at the top 10 AI investments that took place in October 2019. Brightfield, a New York City-based AI and Big Data analytics company, optimizes contract labor spend and program performance for employers, MSPs, and staffing firms earlier this month received US$53 million in early-stage funding round.

The Nutritional Immunology and Molecular Medicine Laboratory (NIMML), a leading lab at the Biocomplexity Institute of Virginia Tech is applying artificial intelligence (AI) methods to personalized nutrition and health. These efforts are aligned with the Precision Medicine Initiative (PMI) which not only aids the researchers and physicians cure people, but also empowers individuals to monitor and take a more active role in their own health. As opposed to the PMI, personalized nutrition refers to tailored nutritional recommendations aimed at the promotion, maintenance of health and prevention against diseases. However, there are numerous challenges in the path of making personalized nutritional recommendations for the health well-being and disease prevention. The "one-size-fits-all" template is based on generic suggestions regarding nutritional recommendations for improving an individual's health are not helpful.

Reem Mahmoud is the Co-founder and Education Lead at Zaka. Reem's passion for Machine Intelligence and education is the main driver for her role at Zaka. She is currently pursuing a Ph.D. degree at the American University of Beirut (AUB) in Electrical & Computer Engineering where her research is in the area of Machine Intelligence with a focus on learning from limited data in the IoT and sensing applications. Her research interests also include digital signal processing, optimization methods, and computer vision. Reem graduated with a B.S. in Electrical Engineering with high distinction from Alfaisal University in Riyadh, Saudi Arabia in 2015 and received her M.E. in Electrical & Computer Engineering from AUB in 2017 where her thesis was about designing accurate personalized user models from sensing data.

The internet and search engines like Google have made the world our oyster when it comes to sourcing information, but in the world of business, there remains a persistent need for more targeted market intelligence, a way to get reliable data quickly to get on with your work. Today, one of the startups hoping to build a lucrative operation of its own around that premise is announcing a round of funding to get there. Crunchbase -- a directory and database of company-related information that originally got its start as a part of TechCrunch before being spun off into a separate business several years ago -- has raised $30 million, a Series C that it plans to use to continue expanding its base of paid subscribers and expanding its product to include more predictive, personalised information for its users by way of more machine learning and other AI-based technology. CEO Jager McConnell, who has long viewed Crunchbase as the "LinkedIn for company profiles," said that of the 55 million people who visit the site each year, the company currently has "tens of thousands" of subscribers -- subscriptions are priced at $29/user/month varying by size of company contract -- which works out to less than 1% of its active users. That's "growing quickly," he added, speaking to site's potential.

You're probably familiar with the oft-quoted statistics from the Food and Agriculture Organization (FAO) of the United Nations by now: Globally, about one-third of food is lost or wasted each year from the farm to the refrigerator, representing about 1.3 billion tons. The economic price tag is estimated at nearly $1 trillion annually. The refrain from the FAO goes even further: If we could reverse this trend, we would have enough food to feed the world's undernourished population, as well as help meet the nutritional needs of a planet estimated to reach nearly 10 billion people by 2050. Technology has long been helping to hack world hunger. These days most conversations about tech's impact on any sector of the economy inevitably involves artificial intelligence--sophisticated software that allows machines to make decisions and even predictions in ways similar to humans.

Although mobile devices were not designed to run compute-heavy AI models, in recent years AI-powered features like face detection, eye tracking, and voice recognition have all been added to smartphones. Much of the compute for such services is done on the cloud, but ideally these applications would be light enough to run directly on devices without an Internet connection. In this spirit of "smaller is better," Shanghai-based developer "Linzai" (GitHub user name @Linzaer) recently shared a new lightweight model that enables real-time face detection for smartphones. The project has garnered a whopping 3.3k Stars and over 600 forks on GitHub. Facial recognition technology is widely applied in security monitoring, surveillance, human-computer interaction, entertainment, etc. Detecting human faces in digital images is the first step in facial recognition, and an ideal face detection model can be evaluated by how quickly and accurately it performs.