Researchers at Tsinghua University and Z.ai built IndexCache to eliminate redundant computation in sparse attention models ...

Data centers face a conundrum: how to power increasingly dense server racks using equipment that relies on century-old technology. Traditional transformers are bulky and hot, but a new generation of ...

Abstract: Graph convolutional networks (GCNs) are emerging neural network models designed to process graph-structured data. Due to massively parallel computations using irregular data structures by ...

There is a minor bug with the sparse structure resolution parameter when running at 64 in cascade mode. The code initializes the model in 512 mode causing the model generated to only be a small ...

Abstract: In this paper, we investigate a data-driven framework to solve infinite-horizon Linear Quadratic Regulator (LQR) problems when the dynamics are partially unknown, with the additional ...

Ever wonder why ChatGPT slows down during long conversations? The culprit is a fundamental mathematical challenge: Processing long sequences of text requires massive computational resources, even with ...

Arkansas is on track to see construction of three proposed data center projects in the next year valued at a combined $12 billion. Plans for the huge centers, which are not yet set in stone, come as ...

Lance datasets storing sparse matrix data in coordinate (COO) format achieve minimal compression compared to other columnar formats like Parquet. This results in storage sizes that are nearly ...

A new seminal review in a special issue of the Journal of Dairy Science® highlights that the complex structure of dairy foods affects their metabolism beyond just their composition David W. Everett, ...

When you watch “The Matrix” at Cosm, you’re essentially seeing a film within a film. A shot inside an apartment becomes a glimpse into an entire complex. A fight scene on a rooftop is now one small ...