MIT engineers use heat-conducting silicon microstructures to perform matrix multiplication with >99% accuracy hinting at ...

MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...

CNBC's Squawk Box Asia Martin Soong and Chery Kang talk about AMD's chip supply deal with OpenAI, plus the web of alliances, cross shareholdings and the money loop that could shape the AI space. Major ...

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 ...

One of the ironies of the moment we’re in is that this inversion of good and evil, truth and falsehood has become more widespread and extreme at the very time that science, technology, and ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

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 difficult tasks in numerical ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The development of low-loss reconfigurable integrated optical devices enables further ...

The stochastic inversion method using logging data as conditional data and seismic data as constraint data has a higher vertical resolution than the conventional deterministic inversion method.

As the demands for hydrocarbon exploration continue to rise, the identification of thin sand bodies becomes significantly important for subsequent petroleum exploration and development efforts.