Artificial intelligence
To help celebrate 50 years of the ACM Turing Award and the visionaries who have received it, ACM has launched a campaign called " Panels in Print, " which takes the form of a collection of responses from Turing laureates,ACM award recipients and other ACM experts on a given topic or trend.
Abstract
S INCE ITS INAUGURATION in 1966, the ACM A.M. Tur-ing Award has recognized major contributions of lasting importance to computing. Through the years, it has become the most prestigious award in computing. To help celebrate 50 years of the ACM Turing Award and the visionaries who have received it, ACM has launched a campaign called " Panels in Print, " which takes the form of a collection of responses from Turing laureates, ACM award recipients and other ACM experts on a given topic or trend. ACM's celebration of 50 years of the ACM Turing Award will culminate with a conference June 23–24, 2017 at the Westin St. Francis in San Francis-co to highlight the significant impact of the contributions of ACM Turing laureates on computing and society, to look ahead to the future of technology and innovation, and to help inspire the next generation of computer scientists to invent and dream. Grace Murray Hopper recipient PEDRO FELZENSZWALB to respond to several questions about Artificial Intelligence. What have been the biggest breakthroughs in AI in recent years and what impact is it having in the real-world? RAJ REDDY: Ten years ago, I would have said it wouldn't be possible, in my lifetime, to recognize unre-hearsed spontaneous speech from an open population but that's exactly what Siri, Cortana and Alexa do. The same is happening with vision and robotics. We are by no means at the end of the activity in these areas, but we have enough working examples that society can benefit from these breakthroughs. JEFF DEAN: The biggest breakthrough in the last five or so years has been the use of deep learning, a particular kind of machine learning that uses neural networks. Stacking the network into many layers that learn increasingly abstract patterns as you go up the layers seems to be a fundamentally powerful idea, and it's been very successful in a surprisingly wide variety of applications—from speech recognition, to image recognition, to language understanding. What's interesting is we don't seem to be near the limit of what deep learning can do; we'll likely see many more powerful uses of it in the coming years. PEDRO FELZENSZWALB: Among the biggest technical advances I would include the development of scalable machine learning algorithms and the computational infrastructure to process and interact with huge data-sets. The latest example of these advances is deep learning. In computer vision deep learning has …