IBM will soon bring some of the core machine learning technology from IBM Watson to mainframes and the private cloud, the company announced on Wednesday. The new cognitive platform, simply called IBM Machine Learning, will make its debut on the z System mainframe. In a press release, IBM described IBM Machine Learning as a platform for "continuously creating, training and deploying a high volume of analytic models in the private cloud at the source of vast corporate data stores." The service could help enterprise data scientists more quickly get to valuable insights. "IBM Machine Learning was designed leveraging our core Watson technologies to accelerate the adoption of machine learning where the majority of corporate data resides," Rob Thomas, general manager for IBM Analytics, said in a press release.

It learns the parameter vector by formulating the problem as a structural SVM problem. The exact details of the method are described in the paper Max-Margin Object Detection by Davis E. King.

Research on machine learning and artificial intelligence needs to be done in the open and not by military research labs, Eric Schmidt, executive chairman of Google's parent Alphabet has said. Mr Schmidt was speaking at the RSA Conference in San Francisco on Wednesday. Some 40,000 security professionals have been attending the event this week. Security threats discussed at hundreds of sessions include the Russian hacking of the Democratic National Committee in advance of the US presidential election last year, as well as threats to business, to government and to internet-connected devices. In conversation with journalist Gideon Lewis-Kraus, Mr Schmidt said machine learning capabilities, which allow computers to learn without being programmed, needed to be done in the open and not by military research labs.

Could machines that think someday pose an existential threat to humanity? Some big names in science and tech seem to think so--Stephen Hawking, for one--and they've issued grave warnings about the looming threat of artificial intelligence.

At Google's inaugural TensorFlow Dev Summit in Mountain View, California, today, Google announced the release of version 1.0 of its TensorFlow open source framework for deep learning, a trendy type of artificial intelligence. Google says the release is now production-ready by way of its application programing interface (API). But there are also new tools that will be part of the framework, which includes artificial neural networks that can be trained on data and can then make inferences about new data. Now there are more traditional machine learning tools, including K-means and support vector machines (SVMs), TensorFlow's engineering director, Rajat Monga, said at the conference. And there's an integration with the Python-based Keras library, which was originally meant to ease the use of the Theano deep learning framework.

Aircraft maker Airbus is turning to smart industrial drones, data analytics and machine learning to make aircraft inspections easier and faster. One day while working on a shiny new Airbus A350 aircraft, Ronie Gnecco figured it was time to build a better relationship between drones and passenger airplanes. His bold idea to use flying robots for aircraft safety inspections worked so well it has -- among other projects -- it inspired aircraft manufacturer Airbus to move deeper into the industrial drone revolution. Within a couple of years, the company's intelligent unmanned aerial vehicles (UAV) systems could be used for safety inspections at airports around the world, making planes safer with more on-time flight departures. To make that happen, Gnecco said it will require pioneering efforts from technology experts, regulators and airport authorities from around the world.

Ethan Bloch was in junior high school in Baltimore during the dot-com boom. For his bar mitzvah -- the ceremony that welcomes 13-year-old Jewish boys into adulthood -- Bloch received $7,000 in cash. It was 1998 and, like so many amateur traders at the time, he plunged his wealth into the stock market, mostly software and telecommunication names like Lucent and Nortel. He quickly tripled his money. By age 15, it was all gone.

David Ulevitch, head of Cisco's security business, has a problem with the hype around artificial intelligence, the field that encompasses the booming computer science discipline of machine learning. Suddenly, everyone in the tech world is buzzing about the subject. Marketers, especially ones in the cybersecurity industry, have started plugging it as something of a panacea; there's no network AI can't protect, if the salespeople are to be believed. "The real threat in security is not whether we have things that are too smart," Ulevitch told Fortune in advance of his Wednesday RSA security conference keynote, during which he planned to touch on the topic. Whenever someone starts dropping the latest buzzwords--algorithms, analytics, AI--Ulevitch tunes them out, he said.

Computer vision is concerned with the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images. Making an approach to pursue the most advanced technology takes a lot of innovation and it is exactly what Mantra Labs has been doing. If you are keen to solve real world problem using AI, Drop us a line hello@mantra.ai

This article is by Featured Blogger Daniel Newman from his LinkedIn page. Decades ago, artificial intelligence was a distant concept meant for future generations. We're seeing advancements every day that will make our lives easier and more efficient. And as a way to make big data useful, AI might be a game changer. Data collection has always been an important facet of business, but never before have we been able to access it in such a responsive and useful manner.