Elon Musk is back on Twitter, and he is talking about a lot of random things, but it also included something about the upcoming release of the Tesla FSD Beta version 10.13, which would be the latest ...
The challenge of speeding up AI systems typically means adding more processing elements and pruning the algorithms, but those approaches aren’t the only path forward. Almost all commercial machine ...
Performing math on multidimensional arrays very efficiently. For example, the Strassen algorithm uses fast matrix math on large matrices. See multidimensional array. THIS DEFINITION IS FOR PERSONAL ...
1. Strassen's method is an important milestone in Computer Science history, largely launching the study of time complexity of algorithms. As the poster child example of a "divide and conquer" ...
Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...
In an ideal platform cloud, you would not know or care what the underlying hardware was and how it was composed to run your HPC – and now AI – applications. The underlying hardware in a cloud would ...
With each passing generation of GPU accelerator engines from Nvidia, machine learning drives more and more of the architectural choices and changes and traditional HPC simulation and modeling drives ...
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