Intel is in transition right now: An executive shakeup this month laid the path for new boss Venkata Renduchintala to put his imprint on the company's PC, Internet of Things and software operations. So no wonder the vibe at this week's Intel Developer Forum in Shenzhen was mellow. Intel kept the show a low-key affair, choosing not to bring it to the attention of a worldwide audience, unlike previous years. But IDF Shenzhen remains an important event on Intel's calendar. China is a huge market, and it's also a place where the chip maker encourages small hardware shops in the alleys of Shenzhen to experiment with PC, mobile and now, IoT ideas.

Synxi, a ManyWorlds brand, discovers content and expertise across your organization most relevant to you. Delivered as apps for collaborative platforms including Microsoft SharePoint, Yammer and Tibbr, Synxi uses patented machine learning and behavioral inferencing technologies to anticipate and adapt to your context and needs.

Of course, the effectiveness of a machine learning fraud solution boils down to how well it works at doing what it promises to do: predict fraud. But when talking about accuracy, don't forget to think about the flip side of stopping bad users – namely, not stopping good users. How well does the tool do at recognizing your good users? So, how do you actually measure the accuracy of a new tool you're not already using? Some platforms may give you the option of trying them out for free, without the commitment of a long-term contract.

Cloud-based athenahealth is expanding its portfolio to include machine learning and artificial intelligence with its acquisition of analytics startup Arsenal Health. Arsenal's Smart Scheduling tool has already been effective with athenahealth's providers, officials said. The acquisition, terms of which were not disclosed, will move Arsenal from a third-party vendor to a native capability available for all athenahealth's customers through its athenaCoordinator network. In the future, athenahealth's officials say they hope the acquisition will accelerate the company's analytics and AI capabilities, broadening insights and enhancing offerings for its 74 million patient records. "The prospect of building on Arsenal Health's technology and combining it with our own valuable data to positively impact care and expand the power of our network is extremely compelling," said Robinson.

Pop quiz: is the following statement true or false? Canada is the birthplace of a transformative technology set to disrupt countless industries and potentially lead the next wave of global economic growth. Most Canadians aren't aware of it, but artificial intelligence (more specifically its subset, deep learning) -- the inspiration for scores of dystopian science-fiction movies -- is a made-in-Canada technology that will become profoundly important over the next few years. Deep learning was the name given to a group of complex mathematical models that came out of the University of Toronto in 2006. In a nutshell, the technology mimics the neural networks of a human brain, giving machines the capacity to learn on their own and discover previously undetectable patterns within massive data sets.

As Machine Learning tools become mainstream, and ever-growing choice of these is available to data scientists and analysts, the need to assess those best suited becomes challenging. In this study, 20 Machine Learning models were benchmarked for their accuracy and speed performance on a multi-core hardware, when applied to 2 multinomial datasets differing broadly in size and complexity. It was observed that BAG-CART, RF and BOOST-C50 top the list at more than 99% accuracy while NNET, PART, GBM, SVM and C45 exceeded 95% accuracy on the small Car Evaluation dataset. On the larger and more complex Nursery dataset, we observed BAG-CART, BOOST-C50, PART, SVM and RF exceeded 99% accuracy, while JRIP, NNET, H2O, C45, and KNN exceeded 95% accuracy. However, overwhelming dependencies on Speed (determined on an average of 5-runs) were observed on a multicore hardware, with only CART, MDA and GBM as contenders for the Car Evaluation dataset.

Digital engagement is once again shifting, as we can see from the main discussions at Facebook's F8 conference this week about the new release of Messenger and its smart chatbots, or when we look at what's happening with popular team messaging services like Slack, which is being "overrun by friendly, wonderful bots." While bots seem like a minor improvement to digital user experience, some believe -- including myself -- that a combination of today's latest technologies will transform this what's-old-is-new-again technology into a major new force in contemporary digital experience and social engagement. Over the last couple of years, conversing in everyday language with our digital devices has become relatively commonplace with the advent of widely used digital concierge services like Siri, Google Now, and Amazon Echo. Known more formally as'conversational user experiences (UXs)', this dialogue-based interaction model actually has quite a long history going way back to command-line programs like Eliza and Zork (both of which yours truly spent far too much time with when younger), the first commercial expert systems in the 1980s, IRC bots, and other early examples. While there's always been an assumption that bots had a bit code behind them with a little situated intelligence -- from performing simple services like scheduling reminders via IM all the way up to the first textual AI-based systems such as MYCIN for helping doctors diagnose infections -- most conversational interfaces tend to be relatively simple affairs with a little bit of basic natural language processing connected to a decision tree.

The last place you want to learn you have heart failure is where it often winds up being diagnosed: in the emergency room. Researchers analyzing electronic health records are using artificial intelligence and GPUs to get ahead of this curve. They've shown they can predict heart failure as much as nine months before doctors can now deliver the diagnosis. A research team from Sutter Health, a Northern California not-for-profit health system, and the Georgia Institute of Technology, believe their method has the potential to reduce heart failure rates and possibly save lives. "The earlier we can detect the disease, the more likely we can change health outcomes for people and improve their quality of life," said Andy Schuetz, a senior data scientist at Sutter Health and an author of a paper describing one aspect of the research.

Now that the 2016 edition of the interactive festival is a thing of the past, here are the main ideas and trends that will shape both technology and the media in the coming years. On the one hand, we are told that things evolve fast and that the future is already upon us; on the other hand, there are claims that this digital revolution is just barely beginning and that there is a lot more to come. What's counts most may not be so much being able to differentiate sociology and foresight but instead to confront one's own ideas and take in the ideas of others. Multiplatform is one of the major trends that made a very prominent mark on this year's festival. It's a question of designing one's content to suit each broadcasting platform instead of adapting one's preformatted content to the platforms in question.

Artificial intelligence (AI), sometimes described as "machine learning," is quickly becoming a key component of several tech leaders' growth ambitions. To its credit, IBM (NYSE:IBM) recognized early on that the key to the fast-growing cloud market lies with the data, not the hosting platform, a fact Alphabet (NASDAQ:GOOG) (NASDAQ:GOOGL) is beginning to take to heart as it explores the expansion of its own AI, data-centric solutions. For Microsoft (NASDAQ:MSFT), its industry-leading cloud business is as much about offering off-site data hosting utilizing its Azure platform to grow its software-as-a-service (SaaS) suite of products. Most pundits agree that SaaS delivered via the cloud is where the real opportunity lies. That said, Microsoft's recently completed BUILD conference in San Francisco made one thing abundantly clear: Its future includes utilizing AI to enhance a person's interactive experience.