Carlos Ghosn's ouster as chairman of Nissan Motor Co. signals that the automaker is seeking to reshape itself to better deal with a rapidly changing market environment, breaking from nearly two decades under his charismatic leadership style, according to some analysts. Chasing volume and sharing costs were a large part of Ghosn's business strategy for one of the world's most successful auto partnerships -- the alliance between Nissan, Renault SA and Mitsubishi Motors Corp. -- led by the Brazil-born executive. Nissan officials say they intend to maintain the alliance due to its benefits, even as the company's board on Thursday approved the dismissal of Ghosn as chairman following his arrest for alleged financial misconduct. Ghosn, sent in by Renault in 1999, closed plants, cut thousands of jobs and streamlined its supply chain to pull the automaker back from the brink of bankruptcy. He set lofty numerical targets to propel growth at Nissan, and as a result, the Japanese-French alliance he forged in pursuit of greater economies of scale grew into one of the world's biggest auto groups.

There are many criticisms you can level at China's growing reliance on facial recognition, including its absolute faith in technology: what happens if there's a false positive? Unfortunately, we just saw an example of that in action. Police in the city of Ningbo have taken corrective action after the facial recognition system at a crosswalk mistakenly accused famous businesswoman Dong Mingzhu of jaywalking because she appeared in an ad on a passing bus. As with any other detected offender in the area, it posted both Dong's name (incorrectly displaying her surname as "Ju") and government ID. The police have since deleted the infraction and claim they've upgraded the facial recognition technology to "reduce the false recognition rate," although it's unclear just what they could have done to address this specific issue.

Rainbow Six Siege players around the world will not have to play a censored version of the game after a major U-turn by developers Ubisoft. The company announced earlier this month that it would be making substantial changes to the game's look to allow it to be played in China. Those included getting rid of symbols and decoration that used skulls, blood that was cleaned up and the disappearance of gambling machines. Despite assurances that the alterations were entirely superficial and would not affect gameplay, fans were immediately angry that such significant changes were being made wherever they were in the world. Though the alterations were in response to demands from the Chinese government, they were rolled out globally.

Facebook has been hit by major problems with its ad platform right as the biggest shopping days of the year approach. The company said there had been significant issues with uploading ads that meant that users were unable to post any marketing content. And the issues happened just days before Black Friday and then Cyber Monday, as users search for the best deals and advertisers rush to get their attention. Uber has halted testing of driverless vehicles after a woman was killed by one of their cars in Tempe, Arizona. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

Researchers at Shree Devi Institute of Technology, in India, have recently carried out a study investigating the use of artificial intelligence (AI) to communicate with deceased loved ones. Like in the chilling sci-fi fantasy foreshadowed by popular television series Black Mirror, AI tools could soon allow people to connect with virtual versions of deceased dear ones. Shriya Devadiga and Bhakthi Shetty, the two researchers who carried out the study, wanted to further examine this fascinating and yet rather unsettling possibility. They particularly focused on Replica AI, an app designed to create duplicates of people's digital personalities, allowing others to communicate with them. "We got the basic idea for our study from Eugenia Kuyda, the founder of Replika AI," Devadiga told TechXplore.

The Regional Transportation Commission of Southern Nevada, the Nevada Department of Transportation and the Nevada Highway Patrol teamed up for the pilot program with Waycare. The Israeli startup already carried out a similar program in Tel Aviv, and it started a crash prevention program last year in Tampa, Florida.

Diabetic Retinopathy is the leading cause of blindness in the world. At least 90\% of new cases can be reduced with proper treatment and monitoring of the eyes. However, scanning the entire population of patients is a difficult endeavor. Computer-aided diagnosis tools in retinal image analysis can make the process scalable and efficient. In this work, we focus on the problem of localizing the centers of the Optic disc and Fovea, a task crucial to the analysis of retinal scans. Current systems recognize the Optic disc and Fovea individually, without exploiting their relations during learning. We propose a novel approach to localizing the centers of the Optic disc and Fovea by simultaneously processing them and modeling their relative geometry and appearance. We show that our approach improves localization and recognition by incorporating object-object relations efficiently, and achieves highly competitive results.

Sequence generation models such as recurrent networks can be trained with a diverse set of learning algorithms. For example, maximum likelihood learning is simple and efficient, yet suffers from the exposure bias problem. Reinforcement learning like policy gradient addresses the problem but can have prohibitively poor exploration efficiency. A variety of other algorithms such as RAML, SPG, and data noising, have also been developed from different perspectives. This paper establishes a formal connection between these algorithms. We present a generalized entropy regularized policy optimization formulation, and show that the apparently divergent algorithms can all be reformulated as special instances of the framework, with the only difference being the configurations of reward function and a couple of hyperparameters. The unified interpretation offers a systematic view of the varying properties of exploration and learning efficiency. Besides, based on the framework, we present a new algorithm that dynamically interpolates among the existing algorithms for improved learning. Experiments on machine translation and text summarization demonstrate the superiority of the proposed algorithm.

In many practical machine-learning applications, it is critical to allow knowledge to be transferred from external domains while preserving user privacy. Unfortunately, existing transfer-learning works do not have a privacy guarantee. In this paper, for the first time, we propose a method that can simultaneously transfer knowledge from external datasets while offering an $\epsilon$-differential privacy guarantee. First, we show that a simple combination of the hypothesis transfer learning and the privacy preserving logistic regression can address the problem. However, the performance of this approach can be poor as the sample size in the target domain may be small. To address this problem, we propose a new method which splits the feature set in source and target data into several subsets, and trains models on these subsets before finally aggregating the predictions by a stacked generalization. Feature importance can also be incorporated into the proposed method to further improve performance. We prove that the proposed method has an $\epsilon$-differential privacy guarantee, and further analysis shows that its performance is better than above simple combination given the same privacy budget. Finally, experiments on MINST and real-world RUIJIN datasets show that our proposed method achieves the start-of-the-art performance.

A Japanese venture group have devised a wearable exoskeleton which can carry the burden of heavy lifting. The so-called Muscle Upper weighs just 17 pounds (8 kilograms) and has the power to raise a maximum of 66 pounds (30 kilograms), it's inventors say. The brainchild of Innophys - a company set-up by the Tokyo University of Science - it could relieve humans of muscle and joint damage through repetitive heavy-lifting. Specifically, it alleviates wear-and-tear on the back and arms, which means it could be ideal for those who work in factories. A video showcasing the frame reveals that compressed air is used to flex the'muscles', which are made of rubber.