Nissan's big push to offer 10 autonomous models in dealerships by 2020 has officially begun. Nissan announced that it will sell its first car with autonomous tech onboard, the Serena minivan, to Japanese customers starting in August. The Serena debuts the brand's self-driving system called ProPILOT, which is a Level 3 autonomous car. That means it can drive fully autonomously in a single lane on the freeway, controlling throttle, brake and steering while the driver sits back and relaxes. This compares to semi-autonomous driving systems currently offered in the U.S., which fall into the Level 2 range of autonomy like Mercedes' Drive Pilot and Tesla Autopilot.

TOKYO--Japanese smartphone-game provider DeNA Co. said Thursday it has set up a company with Preferred Networks Inc., becoming the latest major firm to bet on the startup's artificial-intelligence technology for growth. The new joint project may mean Nintendo Co.'s future smartphone games would be powered by the technology, further beefing up the business potential of its popular characters, including Pokémon, for example, which was...

Using artificial intelligence to create smart farms Is the future of farming in the software? Texas TechPulse spoke with Blake about his new startup which got its start in Israel and what it's up to here in Texas. What exactly is Flux all about? Blake Burris: "Flux Farms is about a two year old company, which was started in Israel. We've built a framework technology, which is generic, in a sense, and can be applied to multiple sectors or realms.

The basic goal of every eCommerce company is to bring the best of offline shopping experience to the online space, by offering the consumers a seamless way to discover the products they are looking for. The avenue is taking a big leap towards becoming the facilitator of a more efficient, personalized, even automated customer journey with the introduction of cognitive technologies and the employment of'smart data'. Today, the most important area of focus in eCommerce is hyper personalization which could be facilitated only by learning consumer behaviour and making predictive analyses with the help of the huge amount of data collected from user activities on smartphones, tablets and desktops, and intelligent algorithms to process them. Machine learning and artificial intelligence are no more restricted to personal assistance technology, smartphone companies are creating. They have flouted these conventions to disrupt a much wider space with limitless possibilities.

WASHINGTON – Congress passed an aviation bill Wednesday that attempts to close gaps in airport security and shorten screening lines, but leaves thornier issues unresolved. The bill also extends the Federal Aviation Administration's programs for 14 months at current funding levels. It was approved in the Senate by a vote of 89 to 4. The House had passed the measure earlier in the week and it now goes to President Barack Obama, who must sign the bill by Friday when the FAA's current operating authority expires to avoid a partial agency shutdown. Responding to attacks by violent extremists associated with the Islamic State group on airports in Brussels and Istanbul, the bill includes an array of provisions aimed at protecting "soft targets" outside security perimeters. Other provisions designed to address potential "insider threats" would toughen vetting of airport workers and other employees with access to secure areas, expand random employee inspections and require reviews of perimeter security.

Newspapers and politicians around the world have been reacting to Boris Johnson's appointment as UK foreign secretary. Many were surprised, citing his history of faux pas including insulting the president of Turkey and commenting on the US president's ancestry. Here we take a look at the response in countries where Mr Johnson will now represent the UK. The Washington Post publishes a round-up of "undiplomatic" things Mr Johnson has said during his time in public life. Washington Post writer Ishaan Tharoor also writes that Mr Johnson "has controversially bucked the Western trend and praised Syrian President Bashar al-Assad for battling the Islamic State, no matter its parallel campaign of violence on Syria's civilian population".

The Andhra Pradesh Government and SAP have signed a MoU here on Thursday to set up a start-up accelerator here. The MoU was signed by SAP Director (Start-up Focus Programme) Mayank Mathur and IT Adviser to AP Government J.A. Chowdary. Mathur said that SAP would strive to create the right kind of eco system in Vizag for the flourishing of start-ups and to develop entrepreneurial spirit among the young. "We will launch the operations initially under our experts based at Bengaluru within a month. They will be visiting Vizag periodically," he said.

A panel of Venture Capitalists from throughout the Bay Area come together to discuss how Artificial Intelligence is catching the eyes of investors across the globe. Panelists discuss the growth of the field and the recent shift in investment from different types of disruptive technologies to AI specifically.

Conventional collaborative filtering techniques treat a top-n recommendations problem as a task of generating a list of the most relevant items. This formulation, however, disregards an opposite - avoiding recommendations with completely irrelevant items. Due to that bias, standard algorithms, as well as commonly used evaluation metrics, become insensitive to negative feedback. In order to resolve this problem we propose to treat user feedback as a categorical variable and model it with users and items in a ternary way. We employ a third-order tensor factorization technique and implement a higher order folding-in method to support online recommendations. The method is equally sensitive to entire spectrum of user ratings and is able to accurately predict relevant items even from a negative only feedback. Our method may partially eliminate the need for complicated rating elicitation process as it provides means for personalized recommendations from the very beginning of an interaction with a recommender system. We also propose a modification of standard metrics which helps to reveal unwanted biases and account for sensitivity to a negative feedback. Our model achieves state-of-the-art quality in standard recommendation tasks while significantly outperforming other methods in the cold-start "no-positive-feedback" scenarios.

With the increase in adoption of Electric Vehicles (EVs), proper utilization of the charging infrastructure is an emerging challenge for service providers. Overstaying of an EV after a charging event is a key contributor to low utilization. Since overstaying is easily detectable by monitoring the power drawn from the charger, managing this problem primarily involves designing an appropriate "penalty" during the overstaying period. Higher penalties do discourage overstaying; however, due to uncertainty in parking duration, less people would find such penalties acceptable, leading to decreased utilization (and revenue). To analyze this central trade-off, we develop a novel framework that integrates models for realistic user behavior into queueing dynamics to locate the optimal penalty from the points of view of utilization and revenue, for different values of the external charging demand. Next, when the model parameters are unknown, we show how an online learning algorithm, such as UCB, can be adapted to learn the optimal penalty. Our experimental validation, based on charging data from London, shows that an appropriate penalty can increase both utilization and revenue while significantly reducing overstaying.