After close to twenty years at IBM, where he began as an IBM Fellow and Chief Architect for the SOA Foundation, Rob High has developed a number of core technologies that back Big Blue's enterprise systems, including the suite of tools behind IBM WebSphere, and more recently, those that support the wide-ranging ambitions of the Watson cognitive computing platform. Although High gave the second day keynote this afternoon at the GPU Technology Conference, there was no mention of accelerated computing. Interestingly, while the talk was about software, specifically the machine learning behind Watson, there was also very little about the software underpinnings. Disappointing as this might have been for the hardware-oriented folks in the crowd hoping to understand how OpenPower Foundation-spurred efforts using GPU-backed, Power-based systems make Watson's gears turn (we can fairly assume that is the case), High did provide a summary of Watson's evolution since 2011 as well as a look ahead at what the Watson research teams are looking to next. High says he is frequently asked what about the differences between AI and cognitive computing, noting that while they aren't much different conceptually, the goal of the Watson team is far more about making humans better at what they do than recreating the human brain in machine form.

WIRED Health 2016 takes place on 29 April in London. IBM's Watson supercomputer is perhaps best known for winning the gameshow Jeopardy, but its expertise is now being applied to healthcare Kyu Rhee will be speaking at WIRED Health 2016 on 29 April in London. From helping humans live longer to understanding the brain, WIRED Health will hear from the innovators transforming this critical sector. You might know IBM's Watson best for its victory on US game show Jeopardy!, or perhaps for its cookery prowess, or even the campaign to elect it to the US presidency. But IBM hopes that its supercomputer can also change the way doctors diagnose their patients, putting vast quantities of data at a physician's fingertips.

WIRED Health 2016 takes place on 29 April in London. IBM's Watson supercomputer is perhaps best known for winning the gameshow Jeopardy, but its expertise is now being applied to healthcare Kyu Rhee will be speaking at WIRED Health 2016 on 29 April in London. From helping humans live longer to understanding the brain, WIRED Health will hear from the innovators transforming this critical sector. You might know IBM's Watson best for its victory on US game show Jeopardy!, or perhaps for its cookery prowess, or even the campaign to elect it to the US presidency. But IBM hopes that its supercomputer can also change the way doctors diagnose their patients, putting vast quantities of data at a physician's fingertips.

The IBM Watson AI system drew the world's attention by winning at "Jeopardy" in February 2011 against two of the game's all-time champions, and IBM has strived to apply the Watson system to more interesting problems than a trivia quiz ever since. IBM has also extended Watson's capabilities to developers, data scientists, and even ordinary business users. Along with IBM's SPSS predictive analytics software, Watson forms the foundation of IBM's cloud offerings in machine learning and advanced analytics. IBM breaks the Watson system into five parts: machine learning, question analysis, natural language processing, feature engineering, and ontology analysis. From these parts, IBM has built out a suite of composable cloud services from which you can make your own mini-Watson for a solution to your problem.

IBM is currently attempting to merge artificial intelligence and the blockchain into a single, powerful prototype. With blockchain tech's promise of near-frictionless value exchange and artificial intelligence's ability to accelerate the analysis of massive amounts of data, the joining of the two could mark the beginning of an entirely new paradigm. Over the past three months, IBM's chief architect in charge of Internet of Things security Tim Hahn has focused specifically on introducing the blockchain to his company's artificially intelligent computer named Watson. "What we're doing with blockchain and devices is enabling the information those devices supply to effect the blockchain…You begin to approach the kind of things we see in movies." Potential applications include using distributed ledgers to let devices perform tasks like running self-diagnoses at set times and more advanced services that may someday let regulators virtually go back in time to the point where a device failed and "to identify exactly what went wrong," Hahn said.

IBM is currently attempting to merge artificial intelligence and the blockchain into a single, powerful prototype. With blockchain tech's promise of near-frictionless value exchange and artificial intelligence's ability to accelerate the analysis of massive amounts of data, the joining of the two could mark the beginning of an entirely new paradigm. Over the past three months, IBM's chief architect in charge of Internet of Things security Tim Hahn has focused specifically on introducing the blockchain to his company's artificially intelligent computer named Watson. "What we're doing with blockchain and devices is enabling the information those devices supply to effect the blockchain…You begin to approach the kind of things we see in movies." Potential applications include using distributed ledgers to perform tasks like running self-diagnoses at set times to more advanced services that may someday let regulators virtually go back in time to the point where a device failed and "to identify exactly what went wrong," Hahn said.

We opened Watson to the world a few years ago so we could put our cognitive technology directly in the hands of developers across every industry and geography. We did this by creating an AI platform that's based on advanced science yet simple for developers to adopt, and is designed to scale. In just a short time, more than 80,000 developers are already innovating on the Watson platform, building with our APIs and creating novel solutions for healthcare, finance, legal, sports and more. In some cases, developers are solving some of society's greatest challenges, in others they're tackling smaller initiatives to gain better insights from data. We're constantly motivated and inspired by what they're creating.

This also marks the first year the Masters app is available on wearables like the Apple Watch. As the sport of golf has struggled in recent years to keep growing the game's popularity among young people, many have seen new technology (such as GoPro cameras on the course) as one potential salve. At the same time, some of the most prominent figures in golf have implied they don't want to see the game change to expand to new audiences. Presidential candidate Donald Trump, who owns 18 courses, is of that camp; Tom Watson is not.

During the dot-com boom, online clothing sales were predicted to grow to 40% -50% of total sales. Although online sales of some other kinds of merchandise, such as books, have reached 50% of the market in the past 15 years, the percentage of online clothing sales hovers around 20%. The difficulty in finding the correct size and fit is one of the primary reasons that consumers are reluctant to buy clothes online. And their concern is not groundless; sizing varies among clothing manufacturers, and it is difficult to ascertain fit from online images. Consequently, 30%-40% of online clothing purchases are returned.

We curated some use cases of companies that have integrated cognitive into their solutions. If you want to know more about any these use cases and receive tips from these companies, check out their webinars. VineSleuth's Wine4.Me In-Store Wine Advisor takes the guesswork out of buying wine by empowering shoppers and increasing sales. Shoppers tell the application what they want in a wine (flavor profile, food pairing, price requirements and more) and Watson returns a custom curated, unbiased wine list and suggests food pairings for each shopper. How it works: VineSleuth uses Natural Language Classifier and Speech to text APIs to allow consumers to easily ask a question into the application, either through voice or text.