So I started SageMath as an open source project at Harvard in 2004, to solve the problem that other math software is expensive, closed source, and limited in functionality, and to create a powerful tool for the students in my classes.
OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google. Torch allows the network to be executed on a CPU or with CUDA.
Today, a group of Silicon Valley luminaries and companies announced that they have committed US$1 billion to an organization they’ve named OpenAI. This nonprofit is dedicated to advancing “digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return.”
My free online class on Coursera.org entitled Global Warming I: The Science and Modeling of Climate Change has already served 45,000 people (started, not finished) in the four times that it's run. Now it's set up in a new format, called on demand mode, which allows people to start, progress, and finish on their own calendars. This would be an advantage if a teacher wanted to use the material to supplement a class; there are ...
Simtk.org is the home of the software framework initiated and developed by Simbios, the National NIH Center for Biomedical Computing focusing on Physics-based Simulation of Biological Structures. Simtk.org represents a centralized organization, a place, where like-minded people can gather to collectively pursue their interests in research areas, related to physics-based simulation of biological structures.
We analyzed and collected a great deal of data for the article on TTIP and think tanks. In this piece, Bas van Beek, Sophia Beunder, and Jilles Mast account for their choices and invite you to make use of their data.
Bro has originally been developed by Vern Paxson, who continues to lead the project now jointly with a core team of researchers and developers at the International Computer Science Institute in Berkeley, CA; and the National Center for Supercomputing Applications in Urbana-Champaign, IL.
Os sistemas de reconhecimento automático de matrículas eram algo que, durante muito tempo, estavam acessíveis apenas para aplicações profissionais e obrigando à utilização de máquinas dispendiosas. Hoje em dia, qualquer pessoa pode facilmente montar um sistema destes usando uma qualquer câmara digital, como demonstra este OpenALPR.
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