To improve the quality of computation experience for mobile devices, mobile-edge computing (MEC) is a promising paradigm by providing computing capabilities in close proximity within a sliced radio access network (RAN), which supports both traditional communication and MEC services. Nevertheless, the design of computation offloading policies for a virtual MEC system remains challenging. Specifically, whether to execute a computation task at the mobile device or to offload it for MEC server execution should adapt to the time-varying network dynamics. In this paper, we consider MEC for a representative mobile user in an ultra-dense sliced RAN, where multiple base stations (BSs) are available to be selected for computation offloading. The problem of solving an optimal computation offloading policy is modelled as a Markov decision process, where our objective is to maximize the long-term utility performance whereby an offloading decision is made based on the task queue state, the energy queue state as well as the channel qualities between MU and BSs. To break the curse of high dimensionality in state space, we first propose a double deep Q-network (DQN) based strategic computation offloading algorithm to learn the optimal policy without knowing a priori knowledge of network dynamics. Then motivated by the additive structure of the utility function, a Q-function decomposition technique is combined with the double DQN, which leads to novel learning algorithm for the solving of stochastic computation offloading. Numerical experiments show that our proposed learning algorithms achieve a significant improvement in computation offloading performance compared with the baseline policies.

The Tesla Autopilot system was engaged when a Tesla Model S sedan was crushed as it rammed into a stopped truck at 60 MPH in Utah last week, the driver has told police. The driver luckily escaped with only a broken foot, though the car suffered extensive damage. When interviewed by police, the Tesla's 28-year-old driver "said that she had been using the'Autopilot' feature," and was looking at her phone shortly before the accident in South Jordan, near Salt Lake City, according to a statement Monday from South Jordan Police Sgt. Winkler told The Deseret News that the diver, who hasn't been identified by police, had entered an address into the car's GPS and was looking on her phone for possible alternate routes. She "looked up just as the accident was about to happen," he said.

On May 15th, the Global X Future Analytics Tech ETF (AIQ) began trading on Nasdaq. The Global X Future Analytics Tech ETF (AIQ) seeks to invest in companies that potentially stand to benefit from the further development and utilization of artificial intelligence (AI) technology in their products and services, as well as in companies that provide hardware facilitating the use of AI for the analysis of big data. AIQ is the 7th ETF in Global X's Thematic Tech suite of ETFs. AI & Big Data is emerging as one of the most potentially disruptive themes in the digital world. As the world's data grows exponentially, AI capabilities are tracking close behind, the far-reaching implications of which are becoming clearer every day.

Marines work on armed MUTT robot in MIX-16 experiment. WASHINGTON: The debate over the use of artificial intelligence in warfare is heating up, with Google employees protesting their company's Pentagon contracts, South Koreans protesting university cooperation with their military, and international experts gathering next week to debate whether to pursue a treaty limiting military AI. While countries like Russia and China are investing heavily in artificial intelligence without restraints, the US and allied militaries like South Korea face a rising tide of opposition. The international conclave has the kind of name you only encounter when dealing with the United Nations and related organizations: the Convention on Conventional Weapons Group of Governmental Experts on Lethal Autonomous Weapons Systems (CCWGGELAWS?). Those experts meet next week and in August.

One of today's modern technological wonders is the flat-panel liquid crystal display (LCD) screen, which is the key component we find inside televisions, computer monitors, smartphones, and an ever-proliferating range of gadgets that display information electronically. What most people don't realize is how complex and sophisticated the manufacturing process is. The entire world's supply is made within two time zones in East Asia. Unless, of course, the factory proposed by Foxconn for Wisconsin actually gets built. Last week I had the opportunity to tour BOE Technology Group's Gen 10.5 factory in Hefei, the capital of China's Anhui Province.

Two technology booms -- some people might call them frenzies -- are combining to turn a once-obscure type of microprocessor into a must-have but scarce commodity. Artificial-intelligence systems, made by companies ranging in size from Google to the Chinese startup Malong Technologies, rely heavily on a computer chip called a graphics processing unit, or GPU. The chips are also very useful in mining digital currencies like Ethereum, a bitcoin alternative riding the same wave of hype as its more famous cousin. With people and companies involved in the two surging tech niches buying up the same chips, GPUs have been in short supply over the past several months. Prices have increased by as much as 50 percent, according to some resellers and customers. "The chips are simply going out of stock," said Matt Scott, a technologist from the United States who founded Malong after leaving Microsoft's research lab in Beijing in 2014.

Assessing damage caused to their rides has just gotten a lot easier for car owners in China, with the rollout of a video-based, artificial-intelligence app from Ant Financial. The Alibaba affiliate last week launched version 2.0 of its Dingsunbao (Loss Assessment Master) app, giving drivers the same power in their hands to provide detailed car-damage information to insurers and claim vehicle insurance in real time as Ant Financial gave professional insurance adjusters just under a year ago. The first version of Dingsunbao has already helped insurers, including China Taiping, China Continent Insurance, Sunshine Insurance Group and AXA Tianping process claims tens of millions of times at a rate of speed much faster than human adjusters alone could handle. "Dingsunbao has already helped the insurance industry to save over RMB 1 billion on claims handling, while saving claims adjusters around 750,000 hours of effort," said Yin Ming, president of Ant Financial's Insurance Business Unit. The AI also ensures a high degree of accuracy in damage assessment, Ant Financial said when it launched Dingsunbao last June.

BrainQ, an Israel-based startup that aims to help stroke victims and those with spinal cord injuries treat their injuries with the help of a personalized electromagnetic treatment protocol, today announced that it has raised a $5.3 million funding round on top of the $3.5 million the company previously raised. When we last talked to BrainQ earlier this year, the team was working on two human clinical trials for stroke patients in Israel. At that time, the company had closed its first funding round and had also recently started to work with Google's Launchpad Accelerator, too. The general idea behind BrainQ is to use the patient's brainwaves to generate a tailored treatment protocol. No AI company would be complete without data -- it's what drives these algorithms, after all -- and the company says it owns one the largest Brain Computer Interface-based EEG databases for motor tasks. It's that database that allows it to interpret the patient's brain waves and generate its treatment protocol.

Israel's education system and military service have created a pool of talented people working in cybersecurity and "that is something we deeply need to take advantage of", Quentin Clark, who leads engineering, product and design at Dropbox, told reporters on Tuesday during a visit to Israel.

TEL AVIV (Reuters) - U.S. file-sharing and storage company Dropbox plans to expand its development center in Tel Aviv by hiring more staff and looking out for acquisition opportunities in security and machine-learning. Israel's education system and military service have created a pool of talented people working in cybersecurity and "that is something we deeply need to take advantage of", Quentin Clark, who leads engineering, product and design at Dropbox, told reporters on Tuesday during a visit to Israel. Dropbox, which went public on Nasdaq in March in the biggest tech IPO in over a year, established a presence in Israel in 2015 when it bought mobile productivity startup CloudOn. Clark said it was now looking for potential acquisitions in the fields of security and machine learning. He said he would be visiting universities in Israel this week to look at machine-learning technologies.