DeepSeek researchers are trying to solve a precise issue in large language model training. Residual connections made very deep networks trainable, hyper connections widened that residual stream, and ...
Abstract: While the Karatsuba algorithm reduces the complexity of large integer multiplication, the extra additions required minimize its benefits for smaller integers of more commonly-used bitwidths.
TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...
The new method accelerates encrypted matrix multiplication, advancing practical fully homomorphic encryption (FHE) for AI SEOUL, South Korea, Nov. 12, 2025 ...
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 ...
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 ...
Google DeepMind’s AI systems have taken big scientific strides in recent years — from predicting the 3D structures of almost every known protein in the universe to forecasting weather more accurately ...
Google DeepMind today pulled the curtain back on AlphaEvolve, an artificial-intelligence agent that can invent brand-new computer algorithms — then put them straight to work inside the company's vast ...
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