Marc Andreessen once said that software was eating the world. The point he was trying to make was that software increasingly represents the value in most economic processes. In this sense, where software was previously one small component of a complex process that involved lots of human input and complex non-digital systems, it now represents the bulk of the intelligence and value-add. Think about cars before Tesla. You had carburetors, fuel injection systems, spark plugs, complex mechanical transmission systems, cooling systems, pumps and much more.

Zenedge just raised 6.2 million in Series C funding, led by Pilot Growth Equity. Additional funds come from Zoho Corporation and existing investors TELUS Ventures and Yehuda Neuberger. Founded in 2014, Zenedge is a leading provider of cloud-based, artificial intelligence, driven Web Application Firewall (WAF) and Distributed Denial of Service (DDoS) cybersecurity Infrastructure-as- a-Service (IaaS) provider. The company leverages patent-pending deep machine-learning capabilities to detect anomalies, dynamically alter security postures, and initiate auto-mitigation and automatic routing with minimal to zero human intervention. This allows the company to provide better cybersecurity and faster time to mitigation than traditional cloud and on-premise cybersecurity vendors, ultimately resulting in less and shorter business interruptions, while helping reduce operational costs.

IPhone owners will get an upgrade on September 13 that allows them to find a picture of nearly anyone or anything, anywhere and from any time. Neural network artificial intelligence in the new iOS 10 performs 11 billion calculations in a tenth of a second on each photo snapped to figure out who people are and even what mood they're in. Aipoly, an app released in January, recognizes objects and speaks their names aloud to blind people. Google Translate can replace text in one language with another language as soon as you point your camera at it. All this happens even if you can't get cell reception.

HENDERSON, Nev.--(BUSINESS WIRE)--Quertle LLC has developed the first artificial intelligence and visual analytics big data (BioAI) platform for biomedical drug discovery. This platform combines machine learning, neural networks, and other AI methods to improve discovery and insight. The BioAI platform includes predictive visual analytics that accelerate search and discovery from the literature, enable discovery of documents that are otherwise overlooked and improve drug discovery. The AI-powered visualizations summarize an entire set of documents, detect trends and uncover hidden connections. Biomedical literature is the foundation of the 5 trillion health care market, serving as the basis for drug discovery, medical device opportunities, marketing decisions and direct health care.

Welcome to robot nursery school," Pieter Abbeel says as he opens the door to the Robot Learning Lab on the seventh floor of a sleek new building on the northern edge of the UC-Berkeley campus. The lab is chaotic: bikes leaning against the wall, a dozen or so grad students in disorganized cubicles, whiteboards covered with indecipherable equations. Abbeel, 38, is a thin, wiry guy, dressed in jeans and a stretched-out T-shirt. He moved to the U.S. from Belgium in 2000 to get a Ph.D. in computer science at Stanford and is now one of the world's foremost experts in understanding the challenge of teaching robots to think intelligently. But first, he has to teach them to "think" at all. "That's why we call this nursery school," he jokes. He introduces me to Brett, a six-foot-tall humanoid robot made by Willow Garage, a high-profile Silicon Valley robotics manufacturer that is now out of business. The lab acquired the robot several years ago to experiment with. Brett, which stands for ...

When Apple unveiled the seventh iteration of the iPhone yesterday, it made sure to play up the camera. After all, the company has a small army working on the iPhone's ability to take photos. The device's camera is also often touted as one of its most cherished features, keeping Apple's smartphone ahead of the competition. Yet in recent years, competition from Samsung and others has caught up to Apple's imaging lead. The newest Apple devices, the iPhone 7 and iPhone 7 Plus, are naturally more capable in the photo department than their predecessors.

But research developed in part by NASA's Jet Propulsion Laboratory, Pasadena, California, may change that, introducing artificial intelligence (AI) that could collect data on temperatures, gases and other danger signals and guide a team of first responders safely through the flames. AUDREY, the Assistant for Understanding Data through Reasoning, Extraction, and sYnthesis, has received the Undersecretary's Award for Collaboration from the Department of Homeland Security (DHS) in recognition of its joint development by JPL and DHS. It's part of the Next Generation First Responder (NGFR) program, a DHS initiative to innovate new ways to keep firefighters, police, paramedics and other first responders safe in the field through increased awareness of their surroundings and communication abilities. But the big picture is even more exciting: AUDREY can track an entire team of firefighters, sending relevant signals to individuals while helping to make recommendations for how they could work together. "As a firefighter moves through an environment, AUDREY could send alerts through a mobile device or head-mounted display," said Mark James of JPL, lead scientist for the AUDREY project.

While the convenience of getting groceries delivered to doorsteps is enticing, it tends to be a costly luxury. The vast majority of Americans are still strolling down store aisles themselves to check items off their shopping lists. And it's this demographic that startup Basket is targeting. The company is highlighting price transparency to helping people discover the best priced items at local stores. It does so by leveraging the power of the crowd. Basket has built up a database of grocery store items and their prices by tasking shoppers with capturing that information.

XGBoost is the high performance implementation of gradient boosting that you can now access directly in Python. The idea of boosting came out of the idea of whether a weak learner can be modified to become better.

We need a labelled dataset that we can feed into machine learning algorithm. Fortunately, some researchers published urban sound dataset. It contains 8,732 labelled sound clips (4 seconds each) from ten classes: air conditioner, car horn, children playing, dog bark, drilling, engine idling, gunshot, jackhammer, siren, and street music. The dataset by default is divided into 10-folds. To get the dataset please visit the following link and if you want to use this dataset in your research kindly don't forget to acknowledge.