LOS ANGELES – Japanese carmaker Honda has joined forces with the General Motors tech start-up Cruise to develop autonomous vehicles as the race to market self-driving cars heats up, the companies announced Wednesday. Honda's investment promises broader market access for the new cars once they are ready for the public. The Japanese government hopes to showcase self-driving cars when Tokyo hosts the Summer Olympics in 2020. With a $2.75 billion commitment in equity and shared development costs over 12 years, Honda joins Japanese conglomerate SoftBank in backing the GM venture to create a multi-purpose vehicle that can be manufactured in high volume for use worldwide, the U.S. auto giant said. Major automakers, start-ups and tech firms are racing to develop truly autonomous vehicles, which the industries see as the next frontier in personal mobility. Honda's announcement comes on the heels of Toyota's move in August to invest $500 million in the ride-hailing service Uber to collaborate on a similar venture to mass-produce self-driving vehicles.

Internet giants are getting better at countering fake news. For the most part, though, they screen content on a story-by-story basis and only block entire outlets well after they've done significant damage. Researchers from MIT's CSAIL and Qatar's Computing Research Institute might have a better solution: use AI to measure the quality of the source. Their machine learning algorithm uses collections of existing articles to gauge the accuracy and bias of a given outlet on the assumption that a fake news peddler or spin factory isn't about to change its ways. Rather than focusing on the claims themselves, it studies the language used to express those claims.

One of the most noteworthy technological accomplishments of the 21st century has been artificial intelligence, popularly known as AI. AI has permeated into almost every sphere today. Many enterprises today are putting their best foot forward in amplifying their own capabilities as well as empowering clients by the adoption of this cutting-edge technology. AI has permeated into almost every sphere today. For instance, AI plays a vital role in virtual shopping today and makes suggests choices to shoppers based on their preferences and by tracking the history of their online behavior.

Although each challenge in the field of recognition has great importance, the most important one refers to online activity recognition. The present study tries to use online hierarchical hidden Markov model to detect an activity on the stream of sensor data which can predict the activity in the environment with any sensor event. The activity recognition samples were labeled by the statistical features such as the duration of activity. The results of our proposed method test on two different datasets of smart homes in the real world showed that one dataset has improved 4% and reached (59%) while the results reached 64.6% for the other data by using the best methods.

We propose shifted inner-product similarity (SIPS), which is a novel yet very simple extension of the ordinary inner-product similarity (IPS) for neural-network based graph embedding (GE). In contrast to IPS, that is limited to approximating positive-definite (PD) similarities, SIPS goes beyond the limitation by introducing bias terms in IPS; we theoretically prove that SIPS is capable of approximating not only PD but also conditionally PD (CPD) similarities with many examples such as cosine similarity, negative Poincare distance and negative Wasserstein distance. Since SIPS with sufficiently large neural networks learns a variety of similarities, SIPS alleviates the need for configuring the similarity function of GE. Approximation error rate is also evaluated, and experiments on two real-world datasets demonstrate that graph embedding using SIPS indeed outperforms existing methods.

In this paper, we introduce McTorch, a manifold optimization library for deep learning that extends PyTorch. It aims to lower the barrier for users wishing to use manifold constraints in deep learning applications, i.e., when the parameters are constrained to lie on a manifold. Such constraints include the popular orthogonality and rank constraints, and have been recently used in a number of applications in deep learning. McTorch follows PyTorch's architecture and decouples manifold definitions and optimizers, i.e., once a new manifold is added it can be used with any existing optimizer and vice-versa. McTorch is available at https://github.com/mctorch .

In the context of Europe, the UK is one of the leading places for AI adoption. "I would say it's the UK and then Germany and France," explains Ben Lorica, chief data scientist at O'Reilly Media. "If you were to look at the world as a whole, I think at this moment at least, because of the nature of the technology involved, the US and China are considered the leaders." This is because a lot of the emerging technologies, such as artificial intelligence, rely on massive amounts of data and computing to be successful. In these two markets (US and China), companies can scale up to many users right away, because of the availability of larger datasets and computational power.

A Japanese probe launched a new observation robot toward an asteroid on Wednesday as it pursues a mission to shed light on the origins of the solar system. The Hayabusa2 probe launched the French-German Mobile Asteroid Surface Scout, or MASCOT, toward the Ryugu asteroid's surface, the Japan Aerospace Exploration Agency (JAXA) said. "We can confirm that the MASCOT separated from the spacecraft as planned," the agency said in a tweet on its official account. I'm descending to Ryugu! Can't stop me now!" the lander's official Twitter account @MASCOT2018 added. JAXA tweeted shortly after the landing began that it was in communication with MASCOT.

Artificial intelligence (also known as AI) is becoming part of our lives increasingly every day. You might use a home assistant like Alexa, Siri on your iPhone, or work in a job that uses elements of AI, chances are you would have encountered it before, whether you realise it or not. In short, AI is software that can learn, adapt and think, similar to the human brain. Get our free ebook on how the Soviet Union became Putin's Russia. But unlike the human brain, AI isn't affected by feelings like boredom, pressure, and fatigue. And that's how it beats humanity -- by remaining untouched by outside influences.

China is promoting artificial intelligence (AI) in an open environment and it seeks to work with other countries to develop the field, Chinese Vice-Premier Liu He told tech honchos in Shanghai on Monday (Sept 17). It supports Chinese firms and research institutes to cooperate widely with their foreign counterparts and also welcomes countries to invest in China to tap its vast market of 1.4 billion people. Mr Liu, who is also the Chinese point man for trade talks with the United States, said China wants to work with all countries "to cope with the double-edged sword brought by new technologies", especially in security, ethical and legal issues.