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

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 ...

We’re just a few years into the AI revolution, but AI systems are already improving decades-old computer science algorithms. Google’s AlphaEvolve AI, its latest coding agent for algorithm discovery, ...

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 ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

Google’s DeepMind research division claims its newest AI agent marks a significant step toward using the technology to tackle big problems in math and science. The system, known as AlphaEvolve, is ...

The VMamba (Visual State Space Model) is built upon the Mamba model by stacking Visual State Space (VSS) modules and utilizing the 2D Selective Scan (SS2D) module to extend the original Mamba model’s ...

It’s a bright day for computing — literally. Two tech companies have unveiled computer components that use laser light to process information. These futuristic processors could soon solve specific ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.