Google's new Graph Foundation Model delivers up to 40 times greater precision and has been tested at scale on spam detection.

In this blog post we introduced GNN and how to build GNN models using different features of the TF-GNN API. We also shared the results of implementing a model from scratch following DeepMind’s ...

Using this information, the model can then tell us the probability of a drug-protein interaction that we did not previously have in the database, as the algorithms can efficiently analyse large ...

A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...

An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin introduces a breakthrough in protein simulation.

When it comes to actually storing the numerical weights that power a large language model's underlying neural network, most modern AI models rely on the precision of 16- or 32-bit floating point ...