When Watson answered the final question to win "Jeopardy!" in 2011, voice recognition and artificial intelligence software were just making their large consumer debut on mobile devices. At the start, these capabilities were engaging, interesting and even exciting, but sometimes more as a parlor game than a deeply functional application. Yet they've continued to improve at an accelerating rate and now demand our serious attention as productivity tools. We are now half a decade on, and cognitive computing is making its presence felt at a deeply functional business level -- not just at the gateway of the journey on our devices, but deep within the industry-process level. For instance, cognitive computing is having a real impact at the clinical-process level for healthcare, which was featured specifically in a segment on artificial intelligence on "60 Minutes."

As artificial intelligence (AI) has progressed at quite a pace in recent years, it is inevitable that governments have tried to get a handle on things and better understand how it might influence society. For instance, I wrote recently about a report by the British government's Science & Technology Select Committee into AI, which looked at a number of topics, from ethics to employment. Hot on the heels of this is another British government report, this time from the office of the Chief Scientific Advisor. It examines the increasingly blurred lines between big data and AI, and particularly the benefits of this for the state. For instance, it highlights that governments could secure enormous savings by utilizing both to reduce tax fraud and minimize errors in tax collection.

Video games where people matter? If you're a video game fan of a certain age, you may remember Edge magazine's controversial review of the bloody sci-fi shooting game, Doom. Perhaps you enjoyed a good laugh, as many first-person shooter fans have, at the writer's much-mocked assertion: "if only you could talk to these creatures, then perhaps you could try and make friends with them, form alliances … Now that would be interesting." Of course, we all know what happened. There would be no room in the Doom series, nor any subsequent first-person blast-'em-up, for such socio-psychological niceties. Instead, we enjoyed 20 years of shooting, bludgeoning and stabbing, the ludicrous idea of diplomacy cast roughly aside. But during this era, something else was happening in game design, and in academic thinking around video games and artificial intelligence.

IBM Chief Executive Ginni Rometty (above) announced that its cognitive computing services already reach 200 million people worldwide and would reach 1 billion by the end of 2017. Healthcare and consumers are proving especially ripe targets for Watson. IBM will continue to engage data scientists, but it indicated that increasingly it will turn its attention to reaching developers. It aims to reach those developers by making Watson's machine learning tools and services as easy-to-use and cost-effective as renting cloud virtual machines. IBM Chief Executive Ginni Rometty (above) announced that its cognitive computing services already reach 200 million people worldwide and would reach 1 billion by the end of 2017.

For instance, there is legislation that governs the use of citizen data by analysts and policy makers to ensure that privacy is maintained and equal treatment is given to all. This is a crucial aspect of public service, and there have been numerous stories about the implicit bias in AI systems, whether because of biased data used to train the systems, or a bias in the algorithms behind them. For AI to thrive in public service therefore, developers need to understand these legal frameworks and how they might apply to AI based decision support.

Cray says the new XC50 provides the highest performance density of any of its supercomputers. Cray has shown off its fastest supercomputer yet, which puts a petaflop of computing power in a single cabinet. The company also says it is adding machine-learning capabilities across its systems. The XC50 supercomputer is designed for the most demanding high-performance computing (HPC) users, according to Cray. It said supercomputing applications are evolving to include more deep-learning algorithms, and as a result the uses of the GPUs in its systems are increasingly "enabling our customers to use new analytics techniques to gain insight from increasingly large and complex data".

As the Big Data London event coincided with a new development in the Brexit story, back-stage discussions could not possibly have remained unaffected. In some cases they even took to the center stage, going as far as panelist Kim Nilsson from Pivigo who has been quoted to say that "if we have a hard Brexit, the data industry is going to die". The newly elected US president has drawn parallels between himself and the Brexit movement, so even though comparing leaving a federated union of nations and changing head of state is like comparing apple pie to Marmite, looking at what organizations can do using data to cope with political change may be of relevance. Predictions are always hard, no matter how much data you have. Predictions are hard, especially about the future.

To build OpenAI--a new artificial intelligence lab that seeks to openly share its research with the world at large--Elon Musk and Sam Altman recruited several top researchers from inside Google and Facebook. But if this unusual project is going to push AI research to new heights, it will need more than talent. It will needs enormous amounts of computing power. Google and Facebook have the resources needed to build the massive computing clusters that drive modern AI research, including vast networks of machines packed with GPU processors and other specialized chips. Google has even gone so far as to build its own AI processor.

SANTA CLARA, CA--(Marketwired - Nov 14, 2016) - NVIDIA (NASDAQ: NVDA) today announced that it is teaming up with the National Cancer Institute, the U.S. Department of Energy (DOE) and several national laboratories on an initiative to accelerate cancer research. The initiative -- known as the Cancer Moonshot, announced by President Barack Obama during his 2016 State of the Union Address, and led by Vice President Joseph Biden -- aims to deliver a decade of advances in cancer prevention, diagnosis and treatment in just five years. The research efforts include a focus on building an AI framework called CANDLE (Cancer Distributed Learning Environment), which will provide a common discovery platform that brings the power of AI to the fight against cancer. CANDLE will be the first AI framework designed to change the way we understand cancer, providing data scientists around the world with a powerful tool against this disease. Teams collaborating on CANDLE include researchers at the National Cancer Institute (NCI), Frederick National Laboratory for Cancer Research and DOE, as well as at Argonne, Oak Ridge, Livermore and Los Alamos National Laboratories.

Boston -- November 15, 2016 -- Machine learning automation leader DataRobot today announced the integration of its enterprise machine learning platform with the Alteryx, Inc. self-service data analytics platform. The Alteryx connector for DataRobot allows users of both platforms to simplify and automate the end-to-end workflow for predictive analytics, from data preparation to modeling to deployment. The connector is now available to download from the Alteryx Analytics Gallery. Predictive analytics can be challenging and complex, often requiring disconnected tools and a variety of programming environments to blend data from disparate sources, build predictive models and then seamlessly deploy them so they can drive real business value. The integration of Alteryx and DataRobot brings together self-service data preparation, blending and advanced analytics from Alteryx with intuitive, automated machine learning from DataRobot.