Natural language processing is everywhere. But what exactly is it? ML@GT's Diyi Yangexplains NLP in the latest edition of Learning Machines. Bonus: Yang also gives hints for what she thinks makes for a great paper and more.
In a guest column for MIT Sloan Management Review, College of Computing Dean Charles Isbell and School of Interactive Computing Chair Ayanna Howard address AI's invisibility problem, why it matters, and what we can do about it moving forward.
In his first time submitting to a machine learning conference, ML@GT's Molei Tao won the best paper award at AISTATS. A mathematician, Tao hopes his win will encourage others to continue searching for ways to fuse ideas and create new venues of applications.
On Oct. 30, ML@GT and the University of California, Berkeley will co-host members of The New York Times Research and Development team for a live, virtual event. Members of the R&D team will participate in a virtual conversation to discuss how the Times is embracing new technologies within photogrammetry and spatial computing to bring their readers as close to a story as possible, reveal their research wishlist, and more.
“The truth is machine learning is not a panacea, nor it resolves suddenly all questions in materials science. Machine learning is never perfect, nor is the user,” - ML@GT Professor Nazanin Bassiri-Gharb.
