Software major Infosys has developed a knowledge-based artificial intelligence (AI) platform to drive automation and innovation for its global clients. "The platform Mana brings machine learning with knowledge of an organisation to drive automation and innovation for enabling businesses reinvent their (computing) systems," the company said in a statement on Friday from San Francisco. Using the platform, the Indian bellwether improved productivity of a unspecified company with a fleet of field engineers by 50 percent by utilising its self-learning capabilities. "The platform enabled a global telecom firm to reduce 80 percent of its agents' entry effort by automating order validation and removing need for corrective processes," the statement asserted. Elaborating on multiple benefits of Mana, Infosys chief executive Vishal Sikka said, "We can automate the repetitive, mechanisable tasks; we can capture the knowledge and know-how across people and long-lived systems and bring this knowledge back inside the systems to drive more value; and in doing these things we can free people to put all of our creativity, passion, and imagination into thinking about the bigger opportunities ahead of us."

Deep learning could not have developed at the rapid pace it has over the last few years without companion work that has happened on the hardware side in high performance computing. While the applications and requirements for supercomputers versus neural network training are quite different (scalability, programming, etc.) without the rich base of GPU computing, high performance interconnect development, memory, storage, and other benefits from the HPC set, the boom around deep learning would be far quieter. In the midst of this convergence, Marc Hamilton has watched advancements on the HPC side over the years, beginning in the mid-1990s at Sun, where he spent 16 years, before becoming VP of high performance computing at HP. Now the VP of Solutions Architecture and Engineering, he says that there is indeed a perfect storm of technologies intermixing in both deep learning and HPC--and this bodes well for Nvidia's future business at both supercomputing sites and deep learning shops alike. "The reality is that every one of those supercomputing centers is producing data every year, more than they know what to do with, and they have problems they just can't sole with classic scientific computing and HPC approaches," Hamilton tells The Next Platform. "The number of people looking at how to apply deep learning to curing cancer or tackling weather prediction with deep learning is growing. What someone does to optimize a deep learning software package is different than what is needed in HPC, but at the end of the day, it's all matrix math. And that is what we do well; so HPC benefits and machine learning benefits."

The firm says it launched this is because progress made in reinforcement learning lags for a few reasons. Firstly, OpenAI notes that existing, open-source testing environments lack diversity and are difficult to set up and use. What's more, there's a dearth of standardization, which makes reproducing the tests -- key for any sort of academic research -- between different projects in an apples to apples way pretty hard to do.

AI is an intelligent technology that makes computer work smartly like an intelligent human, and Pichai says machine learning and AI will "allow you to use your voice to search for information, to translate the web from one language to another, to filter the spam from your inbox, to search for "hugs" in your photos and actually pull up pictures of people hugging ... to solve many of the problems we encounter in daily life. It's what has allowed us to build products that get better over time, making them increasingly useful and helpful."

The following interview is one of many included in the report. As part of our ongoing series of interviews surveying the frontiers of machine intelligence, I recently interviewed Brendan Frey. Frey is a co-founder of Deep Genomics, a professor at the University of Toronto and a co-founder of its Machine Learning Group, a senior fellow of the Neural Computation program at the Canadian Institute for Advanced Research, and a fellow of the Royal Society of Canada. His work focuses on using machine learning to understand the genome and to realize new possibilities in genomic medicine. Brendan Frey: I completed my Ph.D. with Geoff Hinton in 1997.

AI is an intelligent technology that makes computer work smartly like an intelligent human, and Pichai says machine learning and AI will "allow you to use your voice to search for information, to translate the web from one language to another, to filter the spam from your inbox, to search for "hugs" in your photos and actually pull up pictures of people hugging ... to solve many of the problems we encounter in daily life. It's what has allowed us to build products that get better over time, making them increasingly useful and helpful."

In a blog post Sundar Pichai shares his vision of Google's future that will focus on machine learning, artificial intelligence, mobile computing and the cloud.

Last December, Tesla CEO Elon Musk teamed up with Y Combinator president Sam Altman and former Google Brain Team scientist Ilya Sutskever to launch OpenAI, a 1 billion non-profit organization dedicated to furthering our understanding of artificial intelligence with a promise to share its research openly with the world. Today, it's taken its first step in that direction by launching a free toolkit for developers to build and train their own AI bots with games and algorithmic challenges. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. The OpenAI Gym, currently in beta, includes environments to simulate situations for your AI to learn from, as well as a site to compare and reproduce results. The tools are designed for use with Reinforcement Learning (RL), one of the technologies used to develop Google's AlphaGo AI that defeated Go world champion Lee Se-Dol recently. RL works on the principle that a bot will receive a reward every time it completes an action successfully – similar to how you might train a dog.

Fresh off its promotion at Facebook's F8 developer conference, Poncho announced today that it has raised 2 million for its personalized weather forecasting service. The round was led by Lerer Hippeau Ventures and will be earmarked for improvements to Poncho's natural language processing, in addition to building artificial intelligence and data science technology into its bots and apps. Participating investors include Greycroft Partners, Comcast Ventures LP, Venture51 Capital Partners, RRE Ventures, Betaworks, Broadway Video Ventures, Ore Ventures, and several angel investors. Started two years ago out of Betaworks, Poncho offers a weather forecast alternative to Yahoo Weather, AccuWeather, and The Weather Channel. The company seeks to dominate what CEO Sam Mandel calls "thin content," which is activity that "takes place within the notification layer and also on a messaging platform that's contextually relevant, customized, and comes at the right time, but with enough polish to be engaging and cause a happy emotion."

Here's the tech news you need to know this Friday. The employees were part of the account-management and sales teams within the company's "publisher ad-tech group." It was a huge win across the board, and the stock increased 12% in after-hours trading. The company claims it is "curing" cancer. The stock soared more than 15% after-hours, but settled at about 8%.