John Hennessy is the chairman of Alphabet, the parent company of Google, and the former president of Stanford. He's just published a fascinating new book, "Leading Matters," and he agreed to sit for an interview about his experiences. Nicholas Thompson: In the book you talk about a growing leadership crisis, and you mention some industries that have been faltering. Did you leave it out deliberately, or do you think there is a leadership crisis in Silicon Valley? John Hennessy: The valley has its share of leadership crises. And I think there's also a growing challenge that these companies have now gotten to the size where their influence on the public is much larger.

Women are redefining the boundaries set by age-old prejudices in almost every field. The arena of technology is no exception. The domain of technology is evolving every day owing to various entrepreneurs and inventors leading the way. In this backdrop, female entrepreneurs are making a significant contribution to the field of robotics. Women are altering the way humans will interact with robots in the future. From sophisticated drones to projecting and implementing symbiotic ideas, women are reshaping the future of the industry.

The AI humanoid, 'Sophia' (see above), has been making a worldwide tour on behalf of her creator, Hanson Robotics of Hong Kong, and made an unexpected stop to the Caucasus this week. The Caucasus stop meant granting the world's first ever visa granted to a robot, a process that took just two minutes thanks to some smart technology. Sophia's visit was organized by UN public service award winner ASAN (Azerbaijan Service and Assessment Network) xidmet, a government agency in Azerbaijan; which has been reducing the bureaucracy by creating one-stop centres for delivering services to the public. The agency recently took over all the country's e-government initiatives - no mean feat although in Azerbaijani, the word "asan" means easy. To underscore its electronic kinship with Sophia, and its prowess at delivering e-government services, ASAN issued her an electronic visa upon her arrival at Baku International Airport in the nation's capital.

Krystian Woznicki (KW):'Rethinking political agency in an AI-driven world' is the topic of the AMBIENT REVOLTS conference in Berlin on 8–10 November. I would therefore like to begin by asking you about the deployment of algorithms at state borders. You have noted that'in order to learn, to change daily and evolve [they] require precisely the circulations and mobilities that pass through'. This observation is part of your larger argument about how governmentality is less concerned with prohibiting movement than with facilitating it in productive ways. The role of self-learning algorithms would seem to be very significant in this context, since – like capitalism – they also hinge upon movement. When it comes to their thirst for traffic, how do you think that relationship between self-learning algorithms and capitalism? Louise Amoore (LA): Yes, I agree that the role of'self learning' or semi-supervised algorithms is of the utmost relevance in understanding how movement and circulation matters.

China's research efforts in artificial intelligence (AI) began later than the U.S. and Europe. Early contributions in the 1970s included automated theorem proving, logic reasoning, search, and knowledge engineering. For example, Wen-tsün Wu is a pioneer in automated theorem proving. He received the State Preeminent Science and Technology Award in 2000, an honor bestowed on only 25 Chinese scientists across all fields to date. Bo Zhang and Ruqian Lu received the Life Achievement Award from the China Computer Federation (CCF) for their fundamental contributions respectively on problem solving and knowledge engineering.

When you are a world-renowned pioneer in smells, it's somewhat inevitable you will end up sticking your face into peculiar places: the burned rubber tire of a Chevy lowrider, a rotting hunk of wall insulation from an abandoned home, a cupped palmful of cool water from the Detroit River. It's also inevitable that the trailing documentary crew (sent by the local gallery behind your next odor-based installation) and photographer (sent, in this case, by Engadget) will home in on this money shot, jostling ahead of and around you to capture the famous nose in intimate proximity with prosaic, occasionally distasteful, objects. Along with these very words, those images are a critical way to visualize how Sissel Tolaas, who flew to Detroit from Berlin, does the unique fieldwork that has made her a legend in the colossal yet somewhat invisible world of modern olfaction. Yet there's also no denying that the sight of this -- the sniff shot, ubiquitous in casual Google image searches of Tolaas' name -- is not only curious but also comical. The idea of placing one's grown, adult face in close communion with the fluff spilling out of a blighted house to deeply inhale its surely unhealthy molecules and have them wash over you on an emotional level... well, it's something dogs do. But how else are we, with the linguistic and visual tools at our disposal, supposed to communicate what the great Sissel Tolaas is really about to you, the reader? Anyway, Tolaas hates being shadowed by cameras this way, although she's being a terrific sport about it. On her first day in Detroit, she arrives at a former tobacco factory in Poletown.

With ML (machine learning), algorithms rewrite themselves as the machine "learns" more and more about patient care. I've written about a recent case where IBM's Watson computer "read" a Japanese leukemia patient's medical records, genetic data, and 20 million journal articles on leukemia (all in around 10 minutes) and concluded that teams of doctors had misdiagnosed her illness and treated her with the wrong medications. Watson effectively, continually reprogrammed itself to analyze the patient's illness in ways no human had done.

Picard: No one was looking at the parts of the brain that were responsible for this thought development. The "emotion" parts of the brain were critically involved in perception, decision making, rational thinking. I had this moment of like, "Oh, great -- emotion. Here I am, this woman, trying to be taken seriously in engineering, and I'm going to tell them that emotion is important? Really, this is just not going to work."

This post is the first in a three-part series we're publishing this year on artificial intelligence, written by DigitalOcean's Head of R&D, Alejandro (Alex) Jaimes. In recent months, the amount of media coverage on AI has increased so significantly that a day doesn't go by without news about it. Whether it's an acquisition, a funding round, a new application, a technical innovation, or an opinion piece on ethical and philosophical issues ("AI will replace humans, take over the world, eat software, eat the world"), the content just keeps coming. The field is progressing at amazing speeds and there's a lot of experimentation. But with so much noise, it's hard to distinguish hype from reality, and while everyone seems to be rushing into AI in one way or another, it's fair to say there is a good amount of confusion on what AI really is, what sort of value it can bring and where things will go next.

On October 23, 2018, Canadian tech leaders will gather at the Rotman School of Management's Creative Destruction Lab (CDL), located at the University of Toronto, for the fourth annual Machine Learning and the Market for Intelligence conference. Since its inception, the conference has brought together top experts in AI to share and discuss the future of AI and its impact on the economy. During the 2016 conference, Shivon Zilis, Project Director, Office of the CEO at Tesla and Neuralink, previous Partner and continued supporter of Bloomberg Beta, and Founding Fellow of the CDL AI Stream and the CDL Quantum Machine Learning Stream, gave the conference attendees a detailed overview of the AI landscape in Canada. Canada has a unique data advantage and a healthy academic environment for bringing up the next generation of AI talent. It is clear that AI is critical to economic growth.