Tech Xplore on MSN
Tiny silicon structures compute with heat, achieving 99% accurate matrix multiplication
MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat ...
A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Morning Overview on MSN
MIT’s heat-powered silicon chips hit 99% accuracy in math tests
Engineers at MIT have turned one of computing’s biggest headaches, waste heat, into the main act. By sculpting “dust-sized” silicon structures that steer heat as precisely as electrical current, they ...
The Register on MSN
Nvidia leans on emulation to squeeze more HPC oomph from AI chips in race against AMD
AMD researchers argue that, while algorithms like the Ozaki scheme merit investigation, they're still not ready for prime ...
Understanding the benefits of matrix converters for EV chargers and a comparison of different matrix converter topologies.
A Cloudflare blog post claiming a "production-grade" Matrix homeserver on Workers didn't survive community scrutiny. Missing ...
Abstract: For many scientific applications, dense matrix multiplication is one of the most important and computation intensive linear algebra operations. An efficient matrix multiplication on high ...
Abstract: High-dimensional and incomplete (HDI) matrices are commonly encountered in various big data-related applications for illustrating the complex interactions among numerous entities, like the ...
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