Lectures in the 2016 Seminar on "Proofs, beliefs and algorithms through the lens of Sum of Squares" at Harvard and MIT, see http://www.boazbarak.org/sos/
View the complete course: http://ocw.mit.edu/5-07SCF13 Instructor(s): Prof. John Essigmann, Prof. JoAnne Stubbe, Dr. Bogdan Fedeles Biological chemistry is t...
The Chandra Astrophysics Institute (CAI) is an opportunity for students in grades 9-11 from a wide range of academic backgrounds to train for and undertake astronomy projects. The students are mentored by MIT scientists and use observations from the Chandra X-Ray space telescope.
View the complete course: https://ocw.mit.edu/5-111F14 Instructor: Catherine Drennan An introduction to the chemistry of biological, inorganic, and organic m...
Just about every AI advance you’ve heard of depends on a breakthrough that’s three decades old. Keeping up the pace of progress will require confronting AI’s serious limitations.
These technologies all have staying power. They will affect the economy and our politics, improve medicine, or influence our culture. Some are unfolding now; others will take a decade or more to develop. But you should know about all of them right now.
These are lectures for course 6.S094: Deep Learning for Self-Driving Cars taught in Winter 2017. Course website: http://cars.mit.edu Contact: deepcars@mit.ed...
Dueling neural networks. Artificial embryos. AI in the cloud. Welcome to our annual list of the 10 technology advances we think will shape the way we work and live now and for years to come.
Humans easily outperform machines when it comes to tightening and loosening screw fasteners. The future of manufacturing and recycling may depend on changing that.
MIT and SenseTime today announced that SenseTime, a leading artificial intelligence (AI) company, is joining MIT's efforts to define the next frontier of human and machine intelligence.
In December 2017, researchers at Google and MIT published a provocative research paper about their efforts into “learned index structures”. The research is quite exciting, as the authors state in the…
This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: diff...
View the complete course: http://ocw.mit.edu/RES-18-009F15 Instructor: Gilbert Strang, Cleve Moler Gilbert Strang and Cleve Moler provide an overview to thei...
MIT 2.003SC Engineering Dynamics, Fall 2011 View the complete course: http://ocw.mit.edu/2-003SCF11 Instructor: J. Kim Vandiver License: Creative Commons BY-...
A new system for creating code that manipulates tensors yields programs that are 100 times as efficient as those produced by existing software packages, with ramifications for big-data analysis and machine learning.
H. Lin, M. Tegmark, и D. Rolnick. (2016)cite arxiv:1608.08225Comment: Replaced to match version published in Journal of Statistical Physics: https://link.springer.com/article/10.1007/s10955-017-1836-5 Improved refs & discussion, typos fixed. 16 pages, 3 figs.