Nvidia CEO: Software Is Eating the World, but AI Is Going to Eat Software

#artificialintelligence

Tech companies and investors have recently been piling money into artificial intelligence--and plenty has been trickling down to chip maker Nvidia. The company's revenues have climbed as it has started making hardware customized for machine-learning algorithms and use cases such as autonomous cars. At the company's annual developer conference in San Jose, California, this week, the company's CEO Jensen Huang spoke to MIT Technology Review about how the machine-learning revolution is just starting. Nvidia has benefitted from a rapid explosion of investment in machine learning from tech companies. Can this rapid growth in the use cases for machine learning continue?


Nvidia CEO: "Software is eating the world, but AI is going to eat software"

#artificialintelligence

Tech companies and investors have recently been piling money into artificial intelligence--and plenty has been trickling down to chip maker Nvidia. The company's revenues have climbed as it has started making hardware customized for machine-learning algorithms and use cases such as autonomous cars. At the company's annual developer conference in San Jose, California, this week, the company's CEO Jensen Huang spoke to MIT Technology Review about how the machine-learning revolution is just starting. Nvidia has benefitted from a rapid explosion of investment in machine learning from tech companies. Can this rapid growth in the use cases for machine learning continue?


Nvidia CEO: "Software is eating the world, but AI is going to eat software"

#artificialintelligence

Tech companies and investors have recently been piling money into artificial intelligence--and plenty has been trickling down to chip maker Nvidia. The company's revenues have climbed as it has started making hardware customized for machine-learning algorithms and use cases such as autonomous cars. At the company's annual developer conference in San Jose, California, this week, the company's CEO Jensen Huang spoke to MIT Technology Review about how the machine-learning revolution is just starting. Nvidia has benefitted from a rapid explosion of investment in machine learning from tech companies. Can this rapid growth in the use cases for machine learning continue?


FAA Expects 600,000 Commercial Drones In The Air Within A Year

NPR Technology

Drones are flown at a training class in Las Vegas in anticipation of new regulations allowing their commercial use. Drones are flown at a training class in Las Vegas in anticipation of new regulations allowing their commercial use. We are in "one of the most dramatic periods of change in the history of transportation," says Transportation Secretary Anthony Foxx. He was talking about all of it: the self-driving cars, the smart-city movement, the maritime innovations. The Federal Aviation Administration expects some 600,000 drones to be used commercially within a year.


The AI Manifesto

#artificialintelligence

We live in a time of rapid technological change, where nearly every aspect of our lives now relies on devices that compute and connect. The resulting exponential increase in the use of cyber-physical systems has transformed industry, government, and commerce; what's more, the speed of innovation shows no signs of slowing down, particularly as the revolution in artificial intelligence (AI) stands to transform daily life even further through increasingly powerful tools for data analysis, prediction, security, and automation.1 Like past waves of extreme innovation, as this one crests, debate over ethical usage and privacy controls are likely to proliferate. So far, the intersection of AI and society has brought its own unique set of ethical challenges, some of which have been anticipated and discussed for many years, while others are just beginning to come to light. For example, academics and science fiction authors alike have long pondered the ethical implications of hyper-intelligent machines, but it's only recently that we've seen real-world problems start to surface, like social bias in automated decision-making tools, or the ethical choices made by self-driving cars.2, 5 During the past two decades, the security community has increasingly turned to AI and the power of machine learning (ML) to reap many technological benefits, but those advances have forced security practitioners to navigate a proportional number of risks and ethical dilemmas along the way. As the leader in the development of AI and ML for cybersecurity, BlackBerry Cylance is at the heart of the debate and is passionate about advancing the use of AI for good.