Police will be handed extra powers to combat drones after the mass disruption at Gatwick airport in the run-up to Christmas. Gatwick was repeatedly forced to close between 19 and 21 December due to reported drone sightings, affecting about 1,000 flights. In response the government has announced a package of measures which include plans to give police the power to land, seize and search drones. The Home Office will also begin to test and evaluate the use of counter-drone technology at airports and prisons. The exclusion zone around airports will be extended to approximately a 5km-radius (3.1 miles), with additional extensions from runway ends.

In the beginning, archaeologists believe, the first breads were created using some of the most rudimentary technologies in human history: fire and stone. In the region that now encompasses Jordan, one of the world's most ancient examples -- a flatbread vaguely resembling pita and made from wild cereal grains and water -- was cooked in large fireplaces using flat basalt stones, according to Reuters. The taste is "gritty and salty," Amaia Arranz-Otaegui, a University of Copenhagen postdoctoral researcher in archaeobotany, told the news service. "But it is a bit sweet, as well." More than 10,000 years later, bread has clearly evolved but, perhaps, not as dramatically as the technology being used to bake it.

During the twentieth century, discoveries in mathematical logic revolutionized our understanding of the very foundations of mathematics. In 1931, the logician Kurt Gödel showed that, in any system of axioms that is expressive enough to model arithmetic, some true statements will be unprovable1. And in the following decades, it was demonstrated that the continuum hypothesis -- which states that no set of distinct objects has a size larger than that of the integers but smaller than that of the real numbers -- can be neither proved nor refuted using the standard axioms of mathematics2–4. They identify a machine-learning problem whose fate depends on the continuum hypothesis, leaving its resolution forever beyond reach. Machine learning is concerned with the design and analysis of algorithms that can learn and improve their performance as they are exposed to data.

Two scientists at the University of Washington School of Medicine have developed a software program that represents the first use of deep artificial neural networks in squeak detection. University of Washington (UW) School of Medicine researchers have developed a software program to identify and decode rodent vocalizations. The DeepSqueak deep neural network converts audio signals into an image, or sonogram, which could be further refined with machine-vision algorithms developed for self-driving cars. Said the UW School of Medicine's Russell Marx, "DeepSqueak uses biomimetic algorithms that learn to isolate vocalizations by being given labeled examples of vocalizations and noise." According to co-developer Kevin Coffey, the program could distinguish between about 20 kinds of rodent calls.

FRANKFURT (Reuters) - Mercedes-Benz's is not aiming to be the first manufacturer to develop a self-driving car but it wants to be among the first two players able to scale up the technology, Mercedes-Benz executive Christoph Schroeder told German paper Welt am Sonntag.

The evolution of artificial intelligence (AI) -- from artificial narrow intelligence (ANI), through artificial general intelligence (AGI), to artificial super intelligence (ASI) -- is on its way to changing everything. It's expected that soon, artificial intelligence will combine the intricacy and pattern recognition strength of human intelligence with the speed, memory and knowledge sharing of machine intelligence. As the rise of AI continues, AI is challenging and changing not only the way humans live, learn and work, but also how entities across nations: its government, industries, organizations and academia (NGIOA) construct their commercial and economic industries and markets. With this technology driven growth of artificial intelligence, the need to do most manual, mathematical and mundane work is already in decline and will likely be greatly diminished in the coming years. Moreover, with all these new digital assistants and decision-making algorithms assisting and directing humans, more complex day-to-day work for humans is being greatly lessened.

A coming milestone in the automobile world is the widespread rollout of Level 4 autonomy, where the car drives itself without supervision. Waymo, the company spun out of Google's self-driving car research, said it would start a commercial Level 4 taxi service by late 2018, although that hadn't happened as of press time. And GM Cruise, in San Francisco, is committed to do the same in 2019, using a Chevrolet Bolt that has neither a steering wheel nor pedals. These cars wouldn't work in all conditions and regions--that's why they're on rung 4 and not rung 5 of the autonomy ladder. But within some limited operational domain, they'll have the look and feel of a fully robotized car.

In one of the iconic scenes from the teen movie "Fast Times at Ridgemont High," sun-baked stoner Jeff Spicoli has a double cheese and sausage pizza delivered to his classroom, boldly interrupting his uncompromising instructor mid-lecture. Spicoli was considered a mischievous airhead for flouting early-1980s dining etiquette, but he may actually have been way ahead of his time. More than three decades later, a California campus is embracing a kind of food delivery -- via robot. On Wednesday, students at University of the Pacific in Stockton, Calif., will be able to order snacks and beverages for the first time from a bright-colored roving robot on wheels known as the "Snackbot." Its stout body perched atop six small wheels, the electric Snackbot resembles some combination of an Igloo cooler and a Volkswagen Microbus.

When Google announced that it would absorb DeepMind's health division, it sparked a major controversy over data privacy. Though DeepMind confirmed that the move wouldn't actually hand raw patient data to Google, just the idea of giving a tech giant intimate, identifying medical records made people queasy. This problem with obtaining lots of high-quality data has become the biggest obstacle to applying machine learning in medicine. To get around the issue, AI researchers have been advancing new techniques for training machine-learning models while keeping the data confidential. The latest method, out of MIT, is called a split neural network: it allows one person to start training a deep-learning model and another person to finish.

Amazon SageMaker, Microsoft Azure ML Services, Google Cloud ML Engine, IBM Watson Knowledge Studio are examples of ML PaaS in the cloud. If your business wants to bring agility into machine learning model development and deployment, consider ML PaaS. It combines the proven technique of CI/CD with ML model management.