Genpact (NYSE: G), a global leader in digitally-powered business process management and services, today launched its Neural Intelligence Platform that harnesses the power of artificial intelligence technologies, and brings middle and back office processing to the same level of digital automation as the front office to drive seamless customer journeys. Using a cognitive system powered by natural language processing, machine and deep learning techniques, the platform provides a versatile artificial intelligence-based capability that digitizes many business process solutions, including omni-channel management, contact center, account payable query management, and financial and accounting automation. The platform is the result of more than a decade of research and development in high performance business processing practices, recently crystallized into digital solutions through an aggressive build out of advanced technologies including robotic process automation, natural language processing, and machine learning. The platform also leverages Genpact's unique Lean DigitalSM approach that harnesses the combined power of process-centric technologies, design thinking, and deep domain expertise.

Genpact (NYSE: G), a global leader in digitally-powered business process management and services, today launched its Neural Intelligence Platform that harnesses the power of artificial intelligence technologies, and brings middle and back office processing to the same level of digital automation as the front office to drive seamless customer journeys. Using a cognitive system powered by natural language processing, machine and deep learning techniques, the platform provides a versatile artificial intelligence-based capability that digitizes many business process solutions, including omni-channel management, contact center, account payable query management, and financial and accounting automation. The platform automates and improves processes, continually learns, and even can help anticipate customers' needs. Enterprises struggle to effectively integrate digital technologies into business processes that cut across the company to deliver the right customer experience. Analytics also must drive more upstream decisions around product design, customer sentiment, and distribution chain visibility.

Soteria Intelligence is excited to announce the company's research and development focused on creating the next generation of social media threat intelligence solutions with the power to learn and become more effective over time. Instead of taking an approach that looks at combinations of keywords, conversations on a map or other social media analytics that produce a high number of recurring false positives, Soteria Intelligence is implementing machine learning to use false positives, vetted by analysts, as educational tools that continually improve system accuracy. The company is also training its system with proprietary data on past social media threats and, through the understanding of false positives and integration of historical data, combined with natural language processing, image recognition, sentiment analysis and other functionality, Soteria Intelligence is revolutionizing the way social media threats are identified and assessed. "As someone who has spent the past 10 years guiding large organizations throughout the world on complex social media initiatives while using social media analytics tools along the way, I understand where they shine and fall short. I also see what's needed to accurately identify threatening social media behavior on the horizon," stated Aaron Schoenberger, Founder and CEO of Soteria Intelligence.

In this week's Brain Boost: Adidas' robots, AI and humans, and getting started with crowdfunding. Adidas' Robots Robotic manufacturing is going beyond cars for the first time. Adidas, the German sportswear company, announced that the first ever robotic reproduced shoe line will be available to customers in 2017 and, though Adidas is not aiming for full robotic automation, it is looking to learn more about the possibilities of robotic manufacturing, starting with this for a series of shoes. AI Humans However, on the other side of the Atlantic, the 2016 Exponential Manufacturing Conference wrapped up and one of the world's foremost data scientists, Professor Sandy Pentland of MIT, says that artificial intelligence is best used in collaboration with humans. Professor Pentland says that one of the most common challenges to large organizations is delivering the right information to the right people at the right time and he's proposing that software developers use artificial intelligence programs to predict who needs what data when and where and then use the internal computing systems to deliver key figures, best practices, etc. at the right time to the right people.

CVPR 2016 -- CEVA, Inc. (NASDAQ: CEVA), the leading licensor of signal processing IP for smarter, connected devices, today introduced CDNN2 (CEVA Deep Neural Network), its second generation neural network software framework for machine learning. CDNN2 enables localized, deep learning-based video analytics on camera devices in real time. This significantly reduces data bandwidth and storage compared to running such analytics in the cloud, while lowering latency and increasing privacy. Coupled with the CEVA-XM4 intelligent vision processor, CDNN2 offers significant time-to-market and power advantages for implementing machine learning in embedded systems for smartphones, advanced driver assistance systems (ADAS), surveillance equipment, drones, robots and other camera-enabled smart devices. CDNN2 builds on the successful foundations of CEVA's first generation neural network software framework (CDNN), which is already in design with multiple customers and partners.

The word Artificial Intelligence is increasing. The latest example is Picturesqe, a tool for photographers that uses AI-powered automation to help pick out the best snaps and filter out the dross. Founders of Picturesqe, a machine-learning powered piece of software, are confident that it can select the good photos from your large stack. But unlike similar mobile Apps, Picturesqe is targeted specifically at professional photographers and semi-pros. Features of the application include smart grouping, which automatically groups similar photos based on visual content, intelligent zoom so that you can quickly compare the same spot on multiple shots, and aesthetic ranking.

SpotMini is a new smaller version of the Spot robot, weighing 55 lbs dripping wet (65 lbs if you include its arm.) SpotMini is all-electric (no hydraulics) and runs for about 90 minutes on a charge, depending on what it is doing. SpotMini is one of the quietest robots we have ever built. It has a variety of sensors, including depth cameras, a solid state gyro (IMU) and proprioception sensors in the limbs. These sensors help with navigation and mobile manipulation.

Twitter Inc. agreed to acquire a London-based artificial intelligence startup to make tweeted live videos look more professional. In a blog post Monday, Twitter Chief Executive Officer Jack Dorsey said he was buying Magic Pony Technology "so Twitter can continue to be the best place to see what's happening and why it matters, first." Seeking to shore up slowing growth, the social media company has in recent months begun emphasizing video on its site. Magic Pony uses machine learning, a way of teaching software to perform tasks without explicit programming instructions based on pattern recognition, a technology that's "increasingly at the core of everything we build at Twitter," Dorsey said. Twitter paid about 150 million for Magic Pony, according to a person familiar with the matter.

If you're a child of the '80s like me, you might recognize this famous line from the movie WarGames. This innocent-sounding question comes not from one of the movie's human stars, but from a military super-computer named Joshua, after a bored high school student, played by Matthew Broderick, accesses the computer's hard drive. Thinking he's hacked into a video game company, Broderick's character accepts Joshua's challenge and chooses the most intriguing game he can find: global thermonuclear war. Joshua is an intelligent computer programmed to learn through simulations like the one Broderick's character initiates. And because the computer actually does control the arsenal of U.S. nuclear weapons, it's a "game" that puts the planet on the brink of World War III.

Gensim users and developers have shaped the newest release 0.13.0 through their comments, requests and Python code contributions. The release includes new features like Word Movers Distance (WMD) and offers a new tool which is used to tune Topic Models. RaRe Technologies today announced a major update of the software package Gensim, an open source machine learning toolkit for understanding human language. Gensim users and developers have shaped the newest release 0.13.0. This release includes new features like Word Movers' Distance (WMD)*, a novel distance function between unstructured text documents, plus new Tutorials and Quickstarts.