Goto

Collaborating Authors

AI developments aren't all real

#artificialintelligence

Davis Blalock, a computer science graduate student at the Massachusetts Institute of Technology (MIT) told Science magazine that some of the gains may not exist at all. Blalock and his mates compared dozens of approaches to improving neural networks--software architectures that loosely mimic the brain and found that it wasn't obvious what the state of the art even was. The researchers evaluated 81 pruning algorithms, programs that make neural networks more efficient by trimming unneeded connections. All claimed superiority in slightly different ways. But they were rarely compared properly--and when the researchers tried to evaluate them side by side, there was no clear evidence of performance improvements over a 10 year period.


Eye-catching advances in some AI fields are not real

#artificialintelligence

Artificial intelligence (AI) just seems to get smarter and smarter. Each iPhone learns your face, voice, and habits better than the last, and the threats AI poses to privacy and jobs continue to grow. The surge reflects faster chips, more data, and better algorithms. But some of the improvement comes from tweaks rather than the core innovations their inventors claim--and some of the gains may not exist at all, says Davis Blalock, a computer science graduate student at the Massachusetts Institute of Technology (MIT). Blalock and his colleagues compared dozens of approaches to improving neural networks--software architectures that loosely mimic the brain.


Eye-catching advances in some AI fields are not real

#artificialintelligence

Artificial intelligence (AI) just seems to get smarter and smarter. Each iPhone learns your face, voice, and habits better than the last, and the threats AI poses to privacy and jobs continue to grow. The surge reflects faster chips, more data, and better algorithms. But some of the improvement comes from tweaks rather than the core innovations their inventors claim--and some of the gains may not exist at all, says Davis Blalock, a computer science graduate student at the Massachusetts Institute of Technology (MIT). Blalock and his colleagues compared dozens of approaches to improving neural networks--software architectures that loosely mimic the brain.


Scientists help artificial intelligence outsmart hackers

#artificialintelligence

An artificial intelligence (AI) trained on the photos of a dog, crab, and duck (top) would be vulnerable to deception because these photos contain subtle features that could be manipulated. The images on the bottom row don't contain these subtle features, and are thus better for training secure AI. NEW ORLEANS, LOUISIANA--A hacked message in a streamed song makes Alexa send money to a foreign entity. A self-driving car crashes after a prankster strategically places stickers on a stop sign so the car misinterprets it as a speed limit sign. Fortunately these haven't happened yet, but hacks like this, sometimes called adversarial attacks, could become commonplace--unless artificial intelligence (AI) finds a way to outsmart them.


Top Machine learning Books

#artificialintelligence

Machine learning is to learn from data repetitively and to find the pattern hidden there. By applying the results of learning to new data, in other word Machine learning allows computers to analyze past data and predict future data. Machine learning is widely used in familiar places such as product recommendation system and face detection of photos. Also, as cloud machine learning services such as Microsoft's "Azure Machine Learning", Amazon's "Amazon Machine Learning", and Google's "Cloud Machine Learning" are released. This article is written to help novices and experts alike find the best Machine learning books to start with or continue their education. So here is a list of the best Machine learning Books: Book Name: Machine Learning This textbook provides a single source introduction to the primary approaches to machine learning Good content explained in very simple language. The book covers the concepts and techniques from the various fields in a unified fashion and very recent subjects such as genetic algorithms, re-enforcement learning and inductive logic programming. Writing style is clear, explanatory and precise.