Discover how heterogeneous compute templates optimize fast token generation and lower total cost of ownership for enterprise ...

The future of AI isn't just GPUs and NPUs. New CPUs from Arm, Intel, and AMD are bringing AI acceleration to next-gen phones ...

Running AI models on x86 CPUs is becoming easier and faster ...

Tensordyne says logarithmic computing could reduce AI inference costs and power demands, offering an alternative to conventional chip designs.

Building a model capable of RSI would require automating a range of specialist tasks currently carried out by humans. At present data scientists work on the theory of AI and coders put it into ...

Abstract: Matrix computation is ubiquitous in modern scientific and engineering fields. Due to the high computational complexity in conventional digital computers, matrix computation represents a ...

Researchers at Tsinghua University developed the Optical Feature Extraction Engine (OFE2), an optical engine that processes data at 12.5 GHz using light rather than electricity. Its integrated ...

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 ...

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 ...

An NPU is a dedicated hardware accelerator designed to perform AI operations much more efficiently and faster than CPUs and GPUs. NPU cores are specifically designed to perform matrix multiplication ...