"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.

Department of Electrical & Computer Engineering (ECE) welcomed Professor Nicolas Papernot as its newest faculty member this fall. He joins ECE from Pennsylvania State University after spending a year at Google Brain as a research scientist. We sat down with Professor Papernot to hear about his research, why he chose ECE at U of T and asked him what advice he had for the class of 2T3. You joined us after spending a year at Google. Can you tell us a bit about your academic history?

IBM today announced the 2019 Call for Code grand prize was awarded to Prometeo for developing a health monitoring platform for firefighters. The Barcelona-based team consisting of a nurse, a firefighter, and three developers will receive $200,000 and assistance from IBM and its partners to bring the project to life. TNW's finance, blockchain, and business event is coming up soon Promoteo began as an endeavor by firefighter Joan Herrera. Realizing there were no systems in place to monitor the health of firefighters combating wildfires, Herrera and nurse Vicenç Padró began collecting data by hand. Eventually, they joined forces with three IT professionals, Salomé Valero, Josep Ràfols, and Marco Rodriguez, and the team joined the Call For Code challenge.

You might not be aware of it, but there's a quiet arms race going on over our collective reality. The fight is between those who want to subvert it and usher in a world where we no longer believe what we see on our screens and those who want to help preserve the status quo. Up until this point in time, we have largely trusted our eyes and ears when consuming audio and visual media content, but new technological systems that create something known as deepfakes, are changing that. And as these deepfake videos nudge into the mainstream, experts are increasingly worried about the ramifications it will have on the information sharing that underpins society. Dr Richard Nock is the head of machine learning at CSIRO's Data 61 and understands the daunting potential of the technology that powers deepfake videos.