Firefighters undergo rigorous training before responding to their first call but they still aren't superhuman. In a burning building there's a difference between what someone can sense in the surroundings and all the environmental data around him. Researchers at NASA's Jet Propulsion Laboratory (JPL) and the Department of Homeland Security (DHS) are working to fill that gap with an artificial intelligence system that can collect relevant information from the environment and relay it back to firefighters in real time. AUDREY -- or, the Assistant for Understanding Data through Reasoning, Extraction, and sYnthesis -- is integrated with the Internet of Things, which lets the system connect to wearable sensors and head-mounted displays on each firefighter, communicating data about temperatures, hazardous gases, and even GPS locations from one team member to another. "When first responders are connected to all these sensors, the AUDREY agent becomes their guardian angel," Edward Chow, manager of JPL's Civil Program Office and program manager for AUDREY, said in a press release.

We hear from Apple CEO Tim Cook during the company's quarterly earnings calls, but lately the leader of Apple has been opening up in ways that non-analysts can understand. First he sat down with Fast Company, and on Monday an in-depth Washington Post interview on Cook's 5-year anniversary as CEO offered more insight into the company's past failures and future surprises. A lot has changed in the last five years, Cook told the Post. Steve Jobs passed away just six weeks after Cook took the reins, which came as a shock, he said. Apple expanded its product lineup after Jobs's death, and some of those devices were conceived of and developed entirely without Jobs's input.

After my second year at Stanford, I got an internship at the National Institutes of Health, doing neuroscience research with TMS. I was very excited about it, TMS is a technology that uses magnetic fields to influence electrical activity inside a person's brain without having to cut their head open. I had read a lot about it and thought it was the coolest thing ever. After I got there, it turned out to be actually kind of boring. The first time you get to zap someone's brain, it is indeed very exciting.

Have you ever talked to your computer or smartphone? Maybe you've seen a coworker, friend or relative do it. It was likely in the form of a question, asking for some basic information, like the location of the best nearby pizza place or the start time of tonight's sporting event. Soon, however, you may find yourself having entirely different interactions with your device – even learning its name, favorite color and what it thinks about while you are away. It is now possible to interact with computers in ways that seemed beyond our dreams a few decades ago. Witness the huge success of applications as diverse as Siri, Apple's voice-response personal assistant, and, more recently, the Pokémon Go augmented reality video game.

Data is the fuel that drives the machine learning algorithmic engines and ultimately provides the business value. In his session at Cloud Expo, Ed Featherston, a director and senior enterprise architect at Collaborative Consulting, will discuss the key considerations around quality, volume, timeliness, and pedigree that must be dealt with in order to properly fuel that engine. Speaker Bio Ed Featherston is a director/senior enterprise architect at Collaborative Consulting. He brings 35 years of technology experience in designing, building, and implementing large complex solutions. He has significant expertise in systems integration, Internet/intranet, and cloud technologies, Ed has delivered projects in various industries, including financial services, pharmacy, government and retail.

On my current project as well as several others, there is a noted increase in interest and curiosity about adding and integrating chatbots to digital platforms for Banks and Financial Institutions. This has spawned a wide variety of offerings in the marketplace – especially from the big players like Microsoft, IBM, Google, and Facebook. The initial question that most organization might tackle is whether or not to adopt one or multiple platform offerings in the marketplace or to grab some open source components and try to create your own chatbot engine. It is becoming very clear that a chatbot ecosystem is going to be made up of a series of components that will help organize and manage chatbot interactions. Other components may be integrated for special features or biometric authentication of a user as this space matures.

It is a coincidence, but one laden with meaning, that Nvidia is setting new highs selling graphics processors at the same time that SGI, one of the early innovators in the fields of graphics and supercomputing, is being acquired by Hewlett Packard Enterprise. Nvidia worked up from GPUs for gaming PCs to supercomputers, and has spread its technology to deep learning, visualization, and virtual desktops, all with much higher margins than GPUs for PCs or any other client device could deliver. SGI, in its various incarnations, stayed at the upper echelons of computing where there is, to a certain extent, less maneuvering room and more intense competition. In fact, systems using Nvidia's GPU motors have given the shared memory and clusters – many of the latter using Nvidia's Tesla accelerators to improve their computational efficiency – made by SGI a run for the money. SGI is no doubt wishing it had made GPUs for all kinds of devices and had transformed its OpenCL environment into something akin to CUDA.

Wee-Hyong Tok has decades of database systems experience, spanning academia and industry, including deep experience driving and shipping products and services that span distributed engineering teams from Asia and the United States. Before joining Microsoft, Tok worked on in-database analytics, demonstrating how association rule mining can be integrated into a relational database management system, Predator-Miner, which enables users to express data mining operations using SQL queries and provides opportunities for better query optimization and processing. Tok is instrumental in driving data mining boot camps in Asia and was honored as a Microsoft SQL Server Most Valuable Professional for several consecutive years because of his active contribution to the database community in Asia. He has co-authored several books, including the first book on Azure machine learning, Predictive Analytics with Microsoft Azure Machine Learning, and has also published more than 20 peer-reviewed academic papers and journals. Tok holds a Ph.D. in computer science from the National University of Singapore.

Just recently, DeepMind's AlphaGo won a series of Go matches against a top-level human opponent. This victory has caused a mix of excitement and consternation. Are we seeing another case of a bigger and faster machine pushing the edge of performance, or are we perhaps approaching a fundamental crisis of "cognitive competition?" To answer this questions, we look at the succession of game-playing computers, and then explore the rise of "model-free methods" and what it foretells for our future. We have become used to the idea that purpose-built machines can surpass humans in almost any physical task.

The supercomputer swiftly cross-referenced a patient's genetic data to make a diagnosis that would have taken a human doctor weeks. In a world where big data is fast transforming healthcare across the globe, PCs could not only assist GPs, but eventually, replace them. Now, it appears that IBM's supercomputer Watson has greatly speeded up the diagnosis of a rare form of leukemia in a patient, and in doing so, may have saved her life. In January 2015, the patient was admitted to a hospital affiliated to the University of Tokyo's Institute of Medical Science in Japan. Doctors initially diagnosed her with acute myeloid leukemia, a type of blood cancer.