Apple wants you to know it already does great AI -- but it's'subtle' South Africa's CLEVVA is making AI-powered virtual advisors a thing Polly.ai

Computers have already beaten us at chess, Jeopardy and Go, the ancient board game from Asia. And now, in the raging war with machines, human beings have lost yet another battle -- over typing. Turns out voice recognition software has improved to the point where it is significantly faster and more accurate at producing text on a mobile device than we are at typing on its keyboard. The study ran tests in English and Mandarin Chinese. Baidu chief scientist Andrew Ng says this should not feel like defeat. "Humanity was never designed to communicate by using our fingers to poke at a tiny little keyboard on a mobile phone.

PARIS – Scientists Wednesday announced the discovery of an Earth-sized planet orbiting the star nearest our Sun, opening up the glittering prospect of a habitable world that may one day be explored by robots. Named Proxima b, the planet is in a "temperate" zone compatible with the presence of liquid water -- a key ingredient for life. The findings, based on data collected over 16 years, were reported in the peer-reviewed journal Nature. "We have finally succeeded in showing that a small-mass planet, most likely rocky, is orbiting the star closest to our solar system," said co-author Julien Morin, an astrophysicist at the University of Montpellier in southern France. "Proxima b would probably be the first exoplanet visited by a probe made by humans," he told AFP.

Small is beautiful, as the old saying goes, and nowhere is that more true than in media files. Compressed images are considerably easier to transmit and store than uncompressed ones are, and now Google is using neural networks to beat JPEG at the compression game. Google began by taking a random sample of 6 million 1280 720 images on the web. It then broke those down into nonoverlapping 32 32 tiles and zeroed in on 100 of those with the worst compression ratios. The goal there, essentially, was to focus on improving performance on the "hardest-to-compress" data, because it's bound to be easier to succeed on the rest.

Lieff Cabraser partner Dean M. Harvey will be featured as a distinguished speaker on an Association of Business Trial Lawyers (ABTL) panel titled "Are Computers About to Eat Your Lunch (Or At Least Change the Way You Practice)?" The event will take place on August 30, 2016 at The Four Seasons Hotel in San Francisco. Panelists will discuss how artificial intelligence and technology impact the practice of law, especially with respect to document-intensive business litigation. Since computers prove to be more accurate and efficient than human reviewers when reviewing documents, this panel will cover how technology has changed the way lawyers work and what the future looks like for the legal industry in this heavily digitized world. "Dedicated to promoting a dialogue between the California Bench and Bar on business litigation issues," the Association of Business Trial Lawyers (ABTL) was founded in Los Angeles, California in 1973 to develop a better forum for the discussion of business trials.

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New bots are constantly being launched and we have covered a fair few, from this chatbot chef which plans meals for users via emoji, to a messenger bot that helps out in emergency situations. New innovation, Wonder, is designed to help users store and recall the information they need from their gym locker password, their insurance provider, right through to the type of ink cartridges their printer uses. Customers first enter their phone number on Wonder's website. They then text Wonder the information they want to remember at a later date. The app stores that information, and when the customer is trying to recall the details, they can ask Wonder directly via text message: "When's the next company meeting?"

Information contained on this page is provided by an independent third-party content provider. If you are affiliated with this page and would like it removed please contact pressreleases@franklyinc.com BellHawk Systems Corporation announces the availability of a new white paper "The Artificial Intelligence Revolution in Manufacturing Operations Management." This white paper is available for download from the front page News section of www.BellHawk.com. This white paper describes how real-time Artificial Intelligence (AI) techniques originally developed for the USAF and NASA are being applied to manufacturing organizations to enable managers to run their manufacturing plants with less stress and much smaller management teams. It gives examples of how even small manufacturing organizations are able to use these methods to automate their planning and scheduling and for managers to be alerted whenever problems arise.

There are so many articles about learning Deep Learning but still I decided to write one more. The reason is I find many of those articles saying the same thing over and over again. I think there is a need for a new guide for learning DL for people who are already well-versed with traditional ML. Deep Learning is as much science as it is art. I've met and spoken to a lot of people recently who believe doing deep learning is pretty easy, you only need an open source library like TensorFlow, Theano etc. and decent data at your disposal, and you are all set.

The "neural network" we're referring to were originally inspired by the networks within the human brain where information is processed through hundreds of millions of different neurons to produce an outcome in which we make decisions or take action. Neural networks in computing help to crack problems that aren't very easily solvable by simple intuition or formulas, and they can be used in various fields like image recognition, classification (which we do at Funderbeam), robotics, regression analysis, etc. Before we go into detail on how we use neural networks at Funderbeam, a brief insight into the concept seems appropriate. Say you want to invest in a startup on Funderbeam Markets, but prior to doing so you'd like to perform some due diligence and leverage your knowhow with data to determine whether it will be a worthwhile investment or not. You then decide to choose a number of different data inputs which you determine will have an effect in evaluating the potential outcome of your investment.