German automaker Daimler AG, which makes the Mercedes and Smart car brands in the U.S., said Friday it had launched an investigation, at the request of the U.S. Department of Justice, into how it measures diesel exhaust emissions. The carmaker was approached by USDJ last week, following a class-action lawsuit filed against the company in February. In its statement, released Friday, Daimler dismissed the claims as being "without merit" and said it was cooperating fully with the authorities. The announcement came in the same week which saw Japan's Mitsubishi Motors admitting it had rigged data on some of its models' fuel efficiency, while France's PSA Peugeot Citroen's offices were raided by anti-fraud investigators as part of ongoing investigations in the auto industry. Regulators and carmakers have increased their scrutiny of emission tests in the wake of the Volkswagen emissions scandal, which emerged in late September.

Alibaba has invested some serious dollars in their AI program, and as an e-retail platform it's no surprise that cranky customers are one of their top concerns. The company is now using audio speech recognition to guess just how angry a customer is over anything from a botched product to a bungled order. "Speech recognition will enable [Alibaba] to tell [us what] our customer's emotions are like, and how angry [they are]. Then our customer service will be able to react to the customers accordingly, with the help of data derived from speech recognition," Wanli Min, Senior staff data scientist in Alibaba Cloud said in Cloud Computing Conference held in Shenzhen on Wednesday. Speech recognition is the next step of Alibaba's AI development plan.

A Google empire built on search shifted attention on Thursday to high-speed Internet networks, 360-degree video broadcasting and "other bets" as parent company Alphabet logged disappointing earnings. Alphabet said net income hit 4.2 billion in the first three months of this year, but shares sank more than five percent to 714 in after-market trades that followed release of the report. The earnings per share fell 46 cents short of analysts' expectations. Revenue in the quarter rose to nearly 20.3 billion compared to 17.26 billion in the same period a year earlier. The results "represent a tremendous start to the year," said Alphabet chief financial officer Ruth Porat.

BigML is a leading Machine Learning company that helps other businesses make highly automated, data-driven decisions. BigML was founded in 2011 in Corvallis, OR, USA and made its European expansion official by opening its European headquarters in Valencia, Spain in July 2015. The company has pioneered the Machine Learning as a Service (MLAAS) wave of innovation through its consumable, programmable, and scalable software platform streamlining the creation and deployment of smart applications powered by state-of-the-art predictive models. To date, BigML has 15 patent applications, more than 25,000 customers from 120 countries and 5M in venture capital investment. In addition to commercial activities, BigML is playing an active role in promoting Machine Learning in education around the world through its rapidly expanding ambassador program thanks to active participation from top universities in diverse geographies such as North America, Europe and Africa, making real BigML's motto: "Machine Learning made beautifully simple for everyone".

Machines could gradually come to replace doctors, usurping their technical and surgical know-how. However, this could be good news for the patient. Doctors would be more available to counsel and reassure their patients. In this way, machines deployed in the medical field could actually help to bring more of a human touch to the doctor-patient relationship. This is the prediction put forward by Guy Vallancien – a surgeon, member of the French National Academy of Medicine and President of the European School of Surgery – in his book'La médecine sans médecin.

Doctors, teachers, coders, pets, and CEOs, all will be replaced by robots. When robots do all the work you can enjoy and play, be more creative and create more value out of your life. You don't need to stop working. If all our food, shelter, utilities and health services are met somehow without going to the office 5 days a week; what would you do? What would you do if all your work can be done by automation?

The last few weeks, it's become nearly impossible to scour the latest in tech news without coming across something related to the idea of "bots." Bots, per their current implementations, are bits of software AI geared toward helping users complete tasks, request information or even shop online. Their usage isn't limited to these things and may also consist of programs used to carry out mundane or time consuming tasks that might have otherwise required a human. The idea around bots and their proposed usage is pretty straight-forward. As internet communications, cloud computing and complex machine learning improves, there are companies well positioned to leverage the power of bots to make all sorts of tasks faster and easier for users of modern technology.

Algorithms and open-source machine-learning tools are as good as, or even better than, human reviewers in detecting cancer cases using information from free-text pathology reports, according to a new study from the Regenstrief Institute and Indiana University School of Informatics and Computing at Indiana University at Purdue. Further, the computerized approach also was faster and less resource-intensive. Researchers sampled 7,000 free-text pathology reports from more than 30 hospitals that participate in the Indiana Health Information Exchange. The researchers used open-source tools, classification algorithms, and varying feature selection approaches to predict if a report was positive or negative for cancer. The results indicated that a fully automated review yielded results similar or better than those of trained human reviewers, saving both time and money, Indiana University said.

Algorithms and open-source machine-learning tools are as good as, or even better than, human reviewers in detecting cancer cases using information from free-text pathology reports, according to a new study from the Regenstrief Institute and Indiana University School of Informatics and Computing at Indiana University at Purdue. Further, the computerized approach also was faster and less resource-intensive. Researchers sampled 7,000 free-text pathology reports from more than 30 hospitals that participate in the Indiana Health Information Exchange. The researchers used open-source tools, classification algorithms, and varying feature selection approaches to predict if a report was positive or negative for cancer. The results indicated that a fully automated review yielded results similar or better than those of trained human reviewers, saving both time and money, Indiana University said.

Kelly Fisher started using a robo-advisor a year and a half ago because she thought it would be more convenient and easier than investing through a human advisor. What she didn't anticipate, though, was just how much more truthful she would be with an automaton rather than a living, breathing person sitting across the desk. When someone starts asking me about my net worth, I get uncomfortable. The San Francisco-based retail executive has about 8,000 invested in accounts with robo-advisors. These are sites that ask a series of questions and then they match a fund with that investor's risk tolerance and lifestyle.