Sengupta: Thank you so much for having me today. I'm really excited to be in San Francisco. I don't get to come here that often, which is strange because I live in Los Angeles, but I do like to come whenever I can. For my talk today, I'm going to talk about the future of transportation, specifically on the things that I worked on that I think are kind of the up and coming thing, the thing that I'm working on now and what's going to happen in the future. I think part of my career has always been about just doing fun and exciting new things and all my degrees are in aerospace engineering, ever since I was a little kid, I loved science fiction. I actually am a Star Trek person versus a Star Wars person, but I knew since I was a little kid that I wanted to be involved in the space program, so that's why I decided to go the aerospace engineering route and I wanted to build technology. I got my Ph.D. in plasma propulsion systems. Has anyone heard of the mission called Dawn that's out in the main asteroid belt? My Ph.D. research actually was developing the ion engine technology for that mission. It actually flew and got it to a pretty cool place out in the main asteroid belt looking at Vesta and Ceres. I did that for about five years and then I kind of felt like I had done everything I could possibly do on that front, from a research perspective. My management asked me if I wanted to work on the next mission to Mars. There's very few engineers in the space program who'd be like, "No, I'm just not interested in that." And they're like, "We want you to do the supersonic parachute for it."

In today's landscape, the AI space is one of the fastest growing sectors in technology. And there's no shortage of companies searching for the best solution to solve problems using artificial intelligence and machine learning. Despite their best intentions, many young people remain skeptical of AI and how it might affect them in terms of automation and job loss. One company that strongly believes AI can be developed to do good and make a positive change in the world is California-based startup Halfcode. We caught up with its 17-year-old founder and chief executive Richard Black shortly after the company announced its seed funding round to find out what being a social entrepreneur means to him and what his plans for the future are.

The title of this article is meant to be provocative and is aiming at sparking a debate among the readers. If the popular media are to be believed, artificial intelligence (AI) is coming to steal your job and threaten life as we know it. And if we do not prepare now, we may face a future where AI runs free and dominates humans in society. Even though these statements are somewhat exaggerated, there is some truth behind. And it seems like the dystopian views of AI doomsayers have shaken up tech giants and the leading proponent of AI – Google, that released a research paper in collaboration with OpenAI and Universities of Stanford and Berkeley, titled Concrete Problems in AI Safety detailing five practical research problems that could pose a threat to society in the future.

The story of Alberta AI starts on April 1, 1964, with the opening of the University of Alberta's department of computing science. Researchers such as Randy Goebel would graduate from the department and set the foundation for early work on the science of natural language processing and AI in the 80s, the latter of which took the form of studying games like chess. By the '90s, however, several'AI winters' -- periods of funding constraints for research and lack of press interest to generate public excitement -- inhibited the discoveries coming out of the university. "The symptoms of the winter are more that industries [that] bought into the idea that expert systems could help them found that it was way too expensive to implement," said Goebel, now a U of A professor and principal investigator at the Alberta Machine Intelligence Institute (Amii). "If you scale up, it costs a lot to have you and me write down processes for chemistry, for example."

The Food and Drug Administration has issued new guidelines on how it will regulate mobile health software and products that use artificial intelligence to help doctors decide how to treat patients. The guidelines, contained in a pair of documents released Thursday morning, clarify the agency's intent to focus its oversight powers on AI decision-support products that are meant to guide treatment of serious or critical conditions, but whose rationale cannot be independently evaluated by doctors. Unlock this article by subscribing to STAT Plus and enjoy your first 30 days free! STAT Plus is STAT's premium subscription service for in-depth biotech, pharma, policy, and life science coverage and analysis. Our award-winning team covers news on Wall Street, policy developments in Washington, early science breakthroughs and clinical trial results, and health care disruption in Silicon Valley and beyond.

Those bemoaning the amount of spam in their email account's inbox (offers of suspiciously cheap Rolexes, notifications of windfalls, requests to help transfer funds from African states) may not be aware that spam exists for one reason: it works. In a similar way, because the profits from successful cybercrime are very healthy, specific individuals and organizations will always spend time and effort learning clever exploits and methods, because, on occasion, those methods work. Cybercrime is therefore here to stay, and because both end-users and cyber specialists are becoming better educated as to attackers' methods, the threat landscape will not only shift constantly but also become more complex, as methods used by bad actors will become more – although this is not intended as a compliment – intelligent. In general, companies of all sizes have deployed a combination of three cybersecurity measures. The first is a suite of pre-programmed (albeit occasionally updated) databases of known threats: their signatures, techniques, and modus operandi.

The global threat of fraud shows no signs of slowing down. Losses related to fraud are valued at $14.7 billion, according to the most recent DataVisor Fraud Index Report. As fraudsters become increasingly aggressive, new global regulations and solutions are being deployed to keep consumers, merchants and banks safe. In the latest Digital Fraud Tracker, PYMNTS highlights the fraud trends and patterns that regulators are closely monitoring, as well as the solutions -- including artificial intelligence (AI) and machine learning (ML) -- that are being deployed to shift the anti-fraud effort from defense to offense. Fraud has become particularly problematic in the United Kingdom, where last year card-based losses increased by 19 percent compared to the previous year.

CenturyLink (NYSE: CTL) is the second largest U.S. communications provider to global enterprise customers. With customers in more than 60 countries and an intense focus on the customer experience, CenturyLink strives to be the world's best networking company by solving customers' increased demand for reliable and secure connections. The company also serves as its customers' trusted partner, helping them manage increased network and IT complexity and providing managed network and cyber security solutions that help protect their business. Key member of the Ops Transformation team who will support our Field Operations and Service Assurance teams with insights gained from analyzing company data. The ideal candidate must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and delivering solutions to drive KPI improvements.

CenturyLink (NYSE: CTL) is the second largest U.S. communications provider to global enterprise customers. With customers in more than 60 countries and an intense focus on the customer experience, CenturyLink strives to be the world's best networking company by solving customers' increased demand for reliable and secure connections. The company also serves as its customers' trusted partner, helping them manage increased network and IT complexity and providing managed network and cyber security solutions that help protect their business. The Data Scientist is a highly skilled individual contributor, under minimal supervision, who designs and develops programs, methods, processes, and systems to consolidate and analyze diverse, structured and unstructured "big data" sources to generate actionable insights and solutions using machine learning and advanced analytics. The Data Scientist proactively identifies meaningful insights by executing data discovery, exploratory data analysis, and iteratively developing predictive and prescriptive models to identify optimal solutions.

It's always the most advanced and imaginative technology that seems to get the most press. But automation at its heart is not about the fanciest, most fringe robotics or inventions. The U.K.'s Office for National Statistics agrees: "It is not so much that robots are taking over, but that routine and repetitive tasks can be carried out more quickly and efficiently by an algorithm written by a human, or a machine designed for one specific function." The benefits of a machine that can increase speed and efficiency are clear. The question is whether it's a plausible investment both in terms of the learning curve as well as cost.