Longtime Beth Israel Deaconess Medical Chief Information Officer Dr. John Halamka left that role six months ago after more than two decades – during which time he also became one of the most vocal health information technology champions and visible thought leaders during a pivotal time of IT uptake. Halamka has been traveling the world recently – more than 400,000 miles this year, he says – from Europe to Israel to Africa to China, back to his Sherborn, Massachusetts-based Unity Farm Sanctuary for a quick visit with Dudley, his shaggy Scottish Highland Bull, and then out again to explore the newest global trends in leading-edge digital health. Halamka will keynote the ConVerge2Xcelerate event in Boston on October 15, hosted by Blockchain in Healthcare Today – where he is editor-in-chief – and co-presented as part of the preconference activities of the Connected Health Conference. We caught up with him recently at another Boston event and asked him about what he's seeing on his travels. You were CIO of Beth Israel Deaconess for so long – twenty two years. How has your newish gig, as International Healthcare Innovation Professor, been going? A. That's my academic title, my Harvard Medical School title, and that was three years ago. But the official transition from CIO, a hospital based-title, was March 1, 2019. That's when the merger of Beth Israel and Lahey came together, and the CEO and I talked about: How do you create innovation? So what is next with healthcare innovation?

Mansour asked Vorhies about Google's business engagements in China. "Google has gotten in trouble in the past for doing business with the Communist government of China," Mansour said. "And I wanted to ask you were those efforts ongoing when you were with the company? Can you give us any insight into that? Because it was quite troubling."

The promise of AI is easily understood by anyone with an imagination, and for 40 years, venture capitalists have been enthusiastically investing in that promise. However, it's been significantly harder for founders to turn that investment into sustainable business models. Today we are going to look at why that is, and go over what might be a blueprint for startups to create business models around artificial intelligence. Tatsuo Nakamura founded Valuenex in 2006 with the goal of using artificial intelligence to supplement the work being done by patent attorneys, and their software was instrumental in the resolution of one of Japan's most famous, and most valuable, lawsuits. We also talk about how to sell to large companies as a small startup, the challenges in trying to make product strategy based on technology, why staying private longer is not always a good thing for startups, and how Valuenex technology accidentally discovered a secret collaboration between Honda and Google. It's a great discussion with the founder of one of Japan's most successful AI companies, and I think you will really enjoy it. Welcome to Disrupting Japan, straight talk from Japan's most successful entrepreneurs. Today, we're going to be talking about something that's frankly difficult to talk about on an audio podcast. Tatsuo Nakamura founded Valuenex in 2006 to use Artificial Intelligence and modern visualization techniques to help clients make sense of their patent portfolios and to keep an eye on what the competition is doing. In fact, this technology uncovered some of the core evidence that decided the famous blue LED case. It's highly effective but highly visual, so let me try to explain it. Valuenex creates a kind of topographical map that shows companies where in the market, their IP is strong and where it's weak.

From its inception, AI has had a rather ambivalent relationship to humans---swinging between their augmentation and replacement. Now, as AI technologies enter our everyday lives at an ever increasing pace, there is a greater need for AI systems to work synergistically with humans. To do this effectively, AI systems must pay more attention to aspects of intelligence that helped humans work with each other---including social intelligence. I will discuss the research challenges in designing such human-aware AI systems, including modeling the mental states of humans in the loop, recognizing their desires and intentions, providing proactive support, exhibiting explicable behavior, giving cogent explanations on demand, and engendering trust. I will survey the progress made so far on these challenges, and highlight some promising directions. I will also touch on the additional ethical quandaries that such systems pose. I will end by arguing that the quest for human-aware AI systems broadens the scope of AI enterprise, necessitates and facilitates true inter-disciplinary collaborations, and can go a long way towards increasing public acceptance of AI technologies.

"AI will probably most likely lead to the end of the world, but in the meantime, there'll be great companies." If investors are looking for that one great AI company that will also end the world, then they should forget Alphabet or Amazon. I'd put my money on the Japanese firm Cyberdyne Inc. Why? Because it bears the same name as the company that created the Skynet AI in the Terminator films. Skynet fulfilled Altman's prophecy before he made it, albeit on the silver screen, and wiped out human civilization.

Woodie Flowers SM '68, MEng '71, PhD '73, the Pappalardo Professor Emeritus of Mechanical Engineering, passed away on Oct. 11 at the age of 75. Flowers' passion for design and his infectious kindness have impacted countless engineering students across the world. Flowers was instrumental in shaping MIT's hands-on approach to engineering design education, first developing teaching methods and learning opportunities that culminated in a design competition for class 2.70, now called 2.007 (Design and Manufacturing I). This annual MIT event, which has now been held for nearly five decades, has impacted generations of students and has been emulated at universities around the world. Flowers expanded this concept to high school and elementary school students, working to help found the world-wide FIRST Robotics Competition, which has introduced millions of children to science and engineering.

What a time this is to be working in the machine learning field! The last few years have been a dream run for anyone associated with machine learning as there have been a slew of developments and breakthroughs at an unprecedented pace. There's just one thing to keep in mind here – these breakthroughs did not happen overnight. It took years and in some cases, decades, of hard work and persistence. We are used to working with established machine learning algorithms like neural networks and random forest (and so on). We tend to lose sight of the effort it took to make these algorithms mainstream. To actually create them from scratch. The people who lay the groundwork for us – those are the true heroes of machine learning.

Formula E Racing, like its Formula 1 counterpart, relies on speed and strategy to win. But how do you crunch through the reams of data that you can get from an electric race car and analyze it in a way that would help your driver and your racing team beat the competition? And that's why he has partnered with Sanjay Srivastava, Chief Digital Officer of Genpact, to leverage data analytics and artificial intelligence (AI) to build a multi-layer platform that turns a mountain of data into actionable analysis. Formula E racing produces different types of data across many fronts. There's a set of telemetry data from the cars, a stream of large data sets that cars produce while they are on the road, and data from competing drivers and their vehicles. Then there's data gleaned from weather, satellite, traffic, and road patterns. All that needs a data analytics system that can interpolate the information as it comes in from all these sources and analyze it in real-time in a way that the driver and the racing team can absorb and act upon instantaneously. But, as Sylvain points out, that's easier said than done, especially since a Formula E race happens in just one day, and every second counts. As Sylvain and Sanjay explain, it starts with knowing how to structure the incoming information so that the driver and engineers can act upon it quickly. That means setting up the correct algorithms, developing an analytical infrastructure that--with the help of AI--integrates all of the different types of data, and synchronizing it to give the driver and engineers the whole picture and predict the likeliest outcomes in any given scenario in order to make the right decisions during the race. That also means creating a user interface for the data that's both comprehensive and instantly comprehensible to the driver. The work that Sylvain and Sanjay are doing has notable implications for business that goes beyond racing. The technologies they are developing will trickle down to make electric cars and sustainable energy better. The analytics tools they are creating can potentially be utilized by other companies to make better sense of data coming from multiple sources in order to make well-informed business and digital transformation decisions and do so quickly, and to manage their resources more efficiently. This transcript has been edited for length and clarity. Michael Krigsman: Formula E Racing involves cars, speed, data, and advanced technologies such as AI and machine learning.

INDIA, August 16th, 2019 – IDC announced India winners of the third IDC Digital Transformation Awards (DXa) 2019 and named IFFCO Tokio General Insurance, the 2019 Digital Transformer for India last weekend. Now on its third year, IDC's DX Awards honors the achievements of organizations that have successfully digitalized one or multiple areas of their business through the application of digital and disruptive technologies. Other winners include: Cairn Oil & Gas, Escorts Ltd., L&T Hydrocarbon Engineering Limited, ReArk Digital Preservations Pvt. Ltd., Tata SIA Airlines Limited and The Federal Bank Ltd, who all distinguished themselves for their discernible and measurable excellence in their digital transformation (DX) efforts across the five DX masteries and significant efforts to transform or disrupt the market. Eva Au, Managing Director of IDC Asia/Pacific says, "There is clearly an increasing adoption of third platform technologies and innovation accelerators as enterprises race to transform for the future. The winning projects for 2019 India IDC Digital Transformation Awards mirror this trend with inclusion of AI, IoT, Robotics and analytics to achieve operational efficiency and customer satisfaction. These organizations are successfully thriving with a digitally-native culture, using insights at scale, and deliver new models of customer engagements, all of which are enabled by an intelligent, empowered and agile workforce to evolve into the Future Enterprise."

In July 1958, the U.S. Office of Naval Research unveiled a remarkable invention. An IBM 704 – a 5-ton computer the size of a room – was fed a series of punch cards. After 50 trials, the computer taught itself to distinguish cards marked on the left from cards marked on the right. It was a demonstration of the "perceptron" – "the first machine which is capable of having an original idea," according to its creator, Frank Rosenblatt '50, Ph.D. '56. At the time, Rosenblatt – who later became an associate professor of neurobiology and behavior in Cornell's Division of Biological Sciences – was a research psychologist and project engineer at the Cornell Aeronautical Laboratory in Buffalo, New York.