The title for this monthly talk from WWCode-SV Data Science Group is "Scalable Machine Learning in R and Python with H2O" . The focus of this talk is scalable machine learning using the H2O R and Python packages. H2O is an open source, distributed machine learning platform designed for big data, with the added benefit that it's easy to use on a laptop (in addition to a multi-node Hadoop or Spark cluster). The core machine learning algorithms of H2O are implemented in high-performance Java, however, fully-featured APIs are available in R, Python, Scala, REST/JSON, and also through a web interface. Since H2O's algorithm implementations are distributed, this allows the software to scale to very large datasets that may not fit into RAM on a single machine.

Apple and Samsung supplier Foxconn has reportedly replaced 60,000 factory workers with robots. One factory has "reduced employee strength from 110,000 to 50,000 thanks to the introduction of robots", a government official told the South China Morning Post. Xu Yulian, head of publicity for the Kunshan region, added: "More companies are likely to follow suit." In a statement to the BBC, Foxconn Technology Group confirmed that it was automating "many of the manufacturing tasks associated with our operations" but denied that it meant long-term job losses. "We are applying robotics engineering and other innovative manufacturing technologies to replace repetitive tasks previously done by employees, and through training, also enable our employees to focus on higher value-added elements in the manufacturing process, such as research and development, process control and quality control.

Terrapattern is a visual search engine that, from the first moment you use it, you wonder: why didn't Google come up with this ten years ago? Click on a feature on the map -- a baseball diamond, a marina, a roundabout -- and it immediately highlights everything its algorithm thinks looks like it. It's remarkably fast, simple to use, and potentially very powerful. Go ahead and give it a try first to see how natural it is to search for something. And how did a handful of digital artists and developers create it -- and for under 35,000?

Even in the 1990s, when Australian banks copped a lot of flak for closing branches, consumer behaviour was changing. The banks may not have undertaken their branch network rationalisations in the most amenable fashion for the wider community but even then, as data from the Australian Prudential Regulation Authority show, actual points of representation didn't change as much as the headlines suggested. Indeed, points of representation actually increased for 11 straight years from 2001, the first year APRA started compiling proper data. The shift from traditional branch banking and physical currency has been immense. But the next generational shift in financial services – and services more generally – will be even more confronting.

"Many of our current partners are based here," the team wrote, "so having a local facility will help us collaborate more easily and access Michigan's top talent in vehicle development and engineering." Novi is about a 35-minute drive from Fiat Chrysler's US headquarters in Auburn Hills, so it makes sense that Google would set up shop nearby in order to do some R&D work on those autonomous Chrysler Pacifica minivans. Google has previously said it wants to see 100 Pacificas added to its self-driving fleet by the end of 2016, which lines up nicely with their move-in plans at the Novi facility.

One-fifth of the films and television shows offered in the European Union by on-demand providers like Netflix, iTunes and Amazon would have to be Europe-made under new proposals issued Wednesday. The quota would match one that already exists for TV networks in European countries and aims to protect the film industry, culture and national languages of the EU's 28 states in an increasingly globalized world dominated by programs in English and from the U.S. The proposal, however, is not popular in the industry and was immediately criticized by some. "Cultural quotas are outdated and unnecessary -- video-on-demand providers are already investing heavily into European local content," said James Waterworth, vice president of Europe operations for the CCIA computer and Internet industry association. Officials from the European Commission, the EU executive branch that made the proposal Wednesday, noted that Netflix's library is already made up of 21% European content, while other providers have up to 30%. "These percentages are not going to represent a major effort," said Guenther Oettinger, the commissioner responsible for Europe's digital market. "We are providing a certain degree of security for the European film industry."

WIRE)--CrowdStrike Inc., a leader in cloud-delivered next-generation endpoint protection, threat intelligence and response services, today announced enhanced next-generation antivirus (AV) capabilities to its CrowdStrike Falcon Platform to help customers identify and block popular ransomware families such as Locky, Cerber and Teerac, among others. The new protection is part of CrowdStrike's Spring release of new solutions and services that also includes introducing an expanded and updated set of APIs for the Falcon Platform, along with CrowdStrike's new open source tool, CrowdStrike Falcon Orchestrator. When dealing with the uptick in ransomware attacks, organizations need a combination of security features to protect against new variants of ransomware that are launched faster than outmoded signature-based defenses can be updated. As part of its next-generation endpoint protection technology, CrowdStrike uses powerful machine learning algorithms and Indicators-of-Attack-based (IoA) threat prevention to identify and block not only previously unknown ransomware families, but also new and emerging script-based ransomware that do not use executable binaries to encrypt the systems of victims. CrowdStrike's next-generation antivirus capabilities also offer complementary capabilities that include exploit blocking as well as cloud-driven anti-malware and machine learning to stop the execution and spread of ransomware.

The four founders, two of whom have resigned their professorships to devote their full attention to TwentyBN, met each other during studies at the University of Bielefeld in Germany. Each of the founders has over 15 years of experience in machine learning and the relatively young deep learning discipline. Prof. Dr. Roland Memisevic, Chief Scientist, received his doctorate in Toronto, studying with Geoffrey Hinton, one of the founding fathers of deep learning. Prior to co-founding Twenty Billion Neurons, Memisevic was a member of the faculty at the renowned Machine Learning Institute of the University of Montréal led by Yoshua Bengio. The institute counts Google, Facebook, and IBM amongst its most active donors.

Affectiva, a startup developing "emotion recognition technology" that can read people's moods from their facial expressions captured in digital videos, raised 14 million in a Series D round of funding led by Fenox Venture Capital. According to co-founder Rana el Kaliouby, the Waltham, Mass.-based company wants its technology to become the de facto means of adding emotional intelligence and empathy to any interactive product, and the best way for organizations to attain unvarnished insights about customers, patients or constituents. She explained that Affectiva uses computer vision and deep learning technology to analyze facial expressions or non-verbal cues in visual content online, but not the language or conversations in a video. The company's technology ingests digital images--including video in chat applications, live-streamed or recorded videos, or even GIFs--through simple web cams typically. Its system first categorizes then maps the facial expressions to a number of emotional states, like happy, sad, nervous, interested or surprised.

They say that kids aren't born sexist or racist--hate is taught. Artificial intelligence is the same way, and humans are fabulous teachers. ProPublica reported, for example, that an algorithm used to to predict the likelihood of convicts committing future crime tends to tag black folks as higher risk than whites. Despite the oft-repeated claim that such data-driven approaches are more objective than past methods of determining the risk of recidivism or anything else, it's clear that our very human biases have rubbed off on our machines. Consider the case of Microsoft's simple Tay bot, which sucked up all the slurs and racist opinions that Twitter users threw at it and ended up spouting Nazi drivel.