We met Tanmay while he was giving a keynote speech to our tech associates (yes, he gives keynote speeches around the world). Please enjoy Tanmay's article on 5 machine learning services powered by Watson. Computers have never been good at understanding non-mathematical language, but a branch of artificial intelligence aims to change that. Machine learning (ML), a subset of artificial intelligence, aims to enable computers to understand natural language and allow them to reason for themselves. Leading this initiative are services like IBM's Watson, an open platform accessible to developers around the world. In today's world, everyone is using machine learning technologies on a daily basis, whether they realize it or not.

Solutions integrate patient-level data from EHRs to assess risks and other factors. At HIMSS17 in Orlando, IBM Watson Health unveiled a series of value-based cloud solutions aimed at helping providers, health plans, and employers better manage their healthcare costs and quality. The solutions integrate patient-level data from EHRs and other sources to create a better picture of patient populations, risk factors, and other red flags at the individual, group, and population level in order to improve patient outcomes under the new value-based payment models. "Healthcare organizations are operating in a complex and fluctuating business environment, one in which the insights they need to succeed can be hidden amidst an avalanche of disparate and siloed data," says Deborah DiSanzo, General Manager of IBM Watson Health. The new applications, available later this year, will include: Provider Performance Manager, Engagement Manager, Bundled Payments Forecasting and Management, and Custom analytics.

It happened recently as I was looking at demonstrations of two very interesting new technology-based companies that help automate due diligence processes. They are both classic examples of the type of technological innovation that's happening at lightning speed in the legal industry today. They are addressing an enormous pain point in the industry: the mind-numbing burden of manually reviewing thousands of contracts as part of a due diligence mandate. It's the kind of work that has provided a good living for generations of young law firm associates, but it is not efficient and, being human-based, not always very accurate. These two new companies are using technology to make that review more efficient and accurate, by analyzing, summarizing, and extracting structured data from big masses of unstructured and wildly inconsistent documents. To the extent the technology works, it's because it imposes some kind of order on the non-standard work of human lawyers.

Matt Coatney is a technology executive, business advisor, entrepreneur, author, and speaker. His focus is on bringing advanced artificial intelligence and analytic technologies to market. He has co-founded three companies, advised several others, and contributed to the early success of two different tech startups. Matt has also launched data analytics products designed for the fields of life sciences, healthcare, government, finance, and law. Currently Matt is the VP of Services for Exaptive; he previously was the IT strategy lead for global law firm WilmerHale, and was in charge of technology and operations for a legal search product at LexisNexis.

Build Cool AI Technology in 90 Minutes and Learn by Doing (No Coding!) If you're reading this, you probably know that, arguably, artificial intelligence is the most significant technological developments of our time. There will be people who are able to use AI to do incredible things and others who watch technology and the world change around them at a blistering pace without understanding fully what's going on. If you're someone who stays "in the know," you need to learn about AI. We think that you can best learn by doing.

Most of the tech hype at the big SXSW conference this week is definitely anything and everything around virtual reality, but Internet of Things has crept into today's chatter among attendees-in-the-know given reports that the Internet of Things (IoT) smart products platform, Evrything, just secured a solid $24.8M in Series B funding. This comes on the heels of IBM's recent announcement about a big IoT move that will explore how cognitive and IoT technologies will entirely transform industries. IoT is heating up, for sure. But this particular equation from IBM Watson, unlike Evrything, warrants an even closer look given the players involved and the massive impact the synergies will create in the IoT space in both the short and long term. If it succeeds, our everyday lifestyle as we know it will dramatically change forever .

The adoption and application of Artificial Intelligence (AI) continues to accelerate at an exponential rate in modern businesses. As referenced in the 2017 Tech Trend Report, AI is nearing completion of the next layer in technological advancement, integrated into everything individuals and organizations do. This trajectory is predicted to drive cumulative worldwide spending of $40.6 billion on AI projects by 2024 – according to Raconteur. This is expected to create mass opportunity for the pioneering businesses currently investing in AI development. Moving beyond the hype in existing media coverage, this post will uncover the reality behind what AI means for businesses today, in the near future, and beyond 2017.

Watson captured the public imagination about artificial intelligence after defeating two world champions of Jeopardy in 2011 and bringing home a $1 million prize. Since then, Watson has gained new cognitive capabilities through APIs like Alchemy (for sentiment analysis), Tone Analyzer (for personality and emotional analysis), and Conversation (a chatbot builder) and has been embedded in hundreds of applications across financial services, healthcare, retail, and digital. "Chances are, you've interacted with Watson without realizing it," says Alyssa Simpson, Program Director at IBM Watson. "Many companies hide their use of the technology for competitive reasons. They don't want a competitor to buy it too."

Less clear was how a new IBM partnership will change Salesforce AI plans. What's the state of Salesforce Einstein, the portfolio of artificial intelligence (AI) capabilities announced last fall? Salesforce generated plenty of media coverage this week with two big announcements. Here's my take on the realities of a partnership with IBM and what we have yet to understand about the packaging and pricing of Einstein. The first announcement from Salesforce this week was the unexpected bombshell on a new partnership with IBM that headlines simplified as "Watson meets Einstein."

The two artificial intelligence products from IBM and Salesforce, respectively, are being brought together as part of a new partnership between the tech companies. Besides creating a tag team named after two familiar characters from literature and science, the AI partnership is designed to help retailers crunch a broad variety of data -- including customer shopping preferences, weather data and industry information -- to boost business. By combining local shopping patterns, weather and retail industry data from Watson with customer-specific shopping data and preferences from Salesforce Einstein, a retailer will be able to automatically send highly personalized and localized email campaigns to shoppers. IBM is also making weather data available to Salesforce customers as a service, to help them analyze how weather events impact their business. This new partnership comes after IBM acquired huge Salesforce partner Bluewolf Group, with Salesforce CEO Marc Benioff's blessing, a year ago, reportedly spending $200 million on that deal.