Media
Jason Mars: On the future of artificial intelligence
Clarity is short for cross-layer architectures and runtimes in 10 years, which designs the scalable architecture needed to support future artificial intelligence applications. "How to scale to billions of queries a second," he said. They also run a fast-growing startup in Ann Arbor called Clinc Inc., with Mars as …
Robots Should Learn How to Improvise Before Entering Society
Giving specific tasks to AI is quite easy for engineers and programmers, but designing a codebase that gives artificial intelligence the ability to adjust on the fly is not easy. "It turns out those things are really hard," said Cynthia Breazeal, a roboticist at the Massachusetts Institute of Technology's Media Lab …
[D] Machine Learning - WAYR (What Are You Reading) - Week 38 • r/MachineLearning
This is a place to share machine learning research papers, journals, and articles that you're reading this week. If it relates to what you're researching, by all means elaborate and give us your insight, otherwise it could just be an interesting paper you've read. Please try to provide some insight from your understanding and please don't post things which are present in wiki. Preferably you should link the arxiv page (not the PDF, you can easily access the PDF from the summary page but not the other way around) or any other pertinent links. Besides that, there are no rules, have fun.
[D] Entry level papers? • r/MachineLearning
"I really want to read a proper research paper, and know what innovations are actually taking place in the field, not simply learn from a course and apply." However, getting there from zero is tough. I am dabbling in the field for about 4 years (including a graduate program in ML) in still find it challenging if a paper introduces a truly new concept, or if it is some branch of applied math/statistics/cs that I only vaguely know to that point. But of course, the "easy" papers, which are very method/empirically driven, are convenient to read (given good writing!) at some point. Given that, I would strongly advice to complement Ngs quite nice introductory course with some proper self-study based on books.
Developers are using artificial intelligence to spot fake news
The animated face of prototype robot GRACE, Graduate Robot Attending Conference, is tested by Carnegie Mellon University computer scientist Reid Simmons, right, in the lab at the school in Pittsburgh Tuesday, July 9, 2002. It may have been the first bit of fake news in the history of the Internet: in 1984, someone posted on Usenet that the Soviet Union was joining the network. It was a harmless April's Fools Day prank, a far cry from today's weaponized disinformation campaigns and unscrupulous fabrications designed to turn a quick profit. In 2017, misleading and maliciously false online content is so prolific that we humans have little hope of digging ourselves out of the mire. Instead, it looks increasingly likely that the machines will have to save us.