Tesla CEO Elon Musk speaks at the Model X launch event in Fremont, Calif. SAN FRANCISCO – Tesla is known for making an elite 100,000 electric sedan. Well watch out automakers, Elon Musk just announced his company will be pursuing small SUVs, a pickup truck and even larger scale commercial trucks in a bid to revolutionize transportation as we know it. That bombshell was just part of Musk's long-touted Tesla "Master Plan: Part Deux," which outlined a strategy that pivots the company from a builder of niche automobiles to a producer of a broad range of passenger and commercial vehicles that eschew fossil fuel. Also noted in the plan, which Musk published on the company's website late Wednesday, is the company's more well-known pursuit of the consumer solar business through its planned acquisition of SolarCity.

On a previous post we learned how to train a machine learning classifier that is able to detect the different aspects mentioned on hotel reviews. With this aspect classifier, we were able to automatically know if a particular review was talking about cleanliness, comfort & facilities, food, Internet, location, staff and/or value for money. We also learned how to combine this classifier with the sentiment analysis classifier to get interesting insights and answer questions like are guests loving the location of a particular hotel but complaining about its cleanliness? These are the kind of questions we aim to answer with this tutorial and that will lead us to some interesting insights. The source code used for this process is available in this repository.

Over the course of the past year or so, there have been a number of incredible tech projects aimed at stopping the spread of Ebola. One approach that we've never come across before, however, involves plotting the possible spread of Ebola and other "filoviruses" of the same family by predicting which bat species they're most likely to be carried by. That's exactly the goal of a team of scientists, who recently used machine learning techniques to build just such a model. Their work may help prevent future spillover events in which it is important to predict which species of wildlife help spread contagion. "This work entailed collecting intrinsic features describing the world's bat species -- 1,116 species altogether -- and training a machine learning algorithm on these data to learn which features best predict the bat species that carry filoviruses," lead author of the study Barbara Han, a disease ecologist at the Cary Institute of Ecosystem Studies, tells Digital Trends.

Automation is the past, current and next big thing. For a long time, getting robots and software to work for us has been the Holy Grail of business. In theory it makes everything cheaper, more reliable, more powerful and it frees humans up to work on creative projects. Ever since the first industrial revolution, capitalists have looked for ways to extract human labour from the means of production and replace it with smart systems. This, of course, was initially driven by greed.

For more than a decade, technology investors and entrepreneurs obsessed over social media and mobile apps that helped people do things like find new friends, fetch a ride home or crowdsource a review of a product or a movie. Now Silicon Valley has found its next shiny new thing. And it does not have a "Like" button. The new era centers on artificial intelligence and robots, a transformation that many believe will have a payoff on the scale of the personal computing industry or the commercial Internet, two previous generations that spread computing globally. Computers have begun to speak, listen and see, as well as sprout legs, wings and wheels to move unfettered in the world.

The government will introduce new rules on running Japanese language schools to eliminate poorly managed ones and keep the educational quality at an adequate level, sources said Wednesday. The Justice Ministry will revise the relevant ordinance soon, more clearly stating disqualifying conditions and making its screening more stringent, the sources said. There were 549 approved Japanese language schools in fiscal 2015, which ended in March. Due to Japan's declining population, the government aims to promote the establishment of Japanese language schools to attract more highly skilled foreign workers, but inappropriate operations at some schools have surfaced recently. A man running a Japanese language school in Fukuoka Prefecture was convicted in May of finding part-time jobs for students who worked more hours than allowed by law so they could earn money for school fees.

NEW DELHI: Startups like SnapShopr, Staqu Technologies, Wazzat Labs, MadStreetDen and iLenze are experimenting with deep learning and image search technologies focused on powering fashion e-tailers to simplify catalogue search, drive customer engagement and get higher conversions. "Two big trends prompted us to start-up -increasing number of smartphones has eased access to smart cameras, which has triggered increased image-based content on the internet. Secondly, we realised that businesses would increasingly need deep learning technologies to understand and analyse visual content to gain valuable insights - which can be the difference between success and failure now," said Ankit Sachan, cofounder of iLenze, which raised 500,000 from Singapore based Mercatus Capital. The technology is inbuilt within the etailer's application and helps connect product discovery in the offline world like reading a magazine or on the street to online searches of similar products on ecommerce websites. By making it easier and more efficient for consumers to scan the etailer's catalogue, the tech increases engagement and thus higher conversion rates and transactions.

Baidu, the Chinese internet giant, has created a new AI program to explore the connection between art and music. The Baidu AI Composer creates original music inspired by different pieces of art, evoking the mood of each picture in a musical representation. According to the promotional video released by Baidu, the Baidu AI Composer uses image recognition, connected to the'world's largest neural network', to identify the subject, mood, and even cultural signifiers of a piece of art. These are filtered through a matrix of hundreds of billions of samples and AI training features, using trillions of parameters, to create a complete and original piece of music inspired by the specific piece of art observed. The AI program first identifies elements of the picture – are people represented, or is the focus on nature, or objects, or is it an abstract piece? The AI is trained to extract attributes from labeled image data, assigning a mood to elements of the picture, for example, deciding if the overall tone is warm, upbeat, or melancholy.

The definition of artificial intelligence (AI) is a bit fuzzy, so when AT&T claims that it has been using AI for more than 20 years, it should be kept in mind that the AI of 1996 is a lot different from the AI of 2016. The bigger point is that the newer version is doing a lot for the carrier. AT&T is settling on an AI platform that can be used for different things instead of developing "one-off" solutions every time a task requiring the predictive capabilities and massive number-crunching abilities of AI presents itself. AI can be leveraged to anticipate rather than simply react to events, as less sophisticated AI platforms have done in the past. The driver is software-defined networks (SDNs), according to Computerworld.

In a galaxy known as New York, in a drab age before Trekkies and light sabers, there lived a curious boy who liked comic books, time travel and Elvis. He read Isaac Asimov and tuned in to John Zacherle, this Phantom of the Opera-type guy with scraggly hair and a creepy laugh who introduced horror movies on Channel 9, which, if you were a kid at the time, was something close to splendid. This boy, let's call him Jeffrey Walker, who incidentally would later watch "2001: A Space Odyssey" 29 times, tended toward the imaginative. His mother was a beauty queen, his father a clothier. Walker grew up to be many things, including an actor who played poker with Jesus Christ, shot a nude scene with Al Pacino and was hugged by Natalie Wood.