Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

A research team has introduced a new out-of-core mechanism, Capsule, for large-scale GNN training, which can achieve up to a 12.02× improvement in runtime efficiency, while using only 22.24% of the ...

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 the ...

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...

Large language model AIs might seem smart on a surface level but they struggle to actually understand the real world and model it accurately, a new study finds. When you purchase through links on our ...

Mark Stevenson has previously received funding from Google. The arrival of AI systems called large language models (LLMs), like OpenAI’s ChatGPT chatbot, has been heralded as the start of a new ...

A team led by Guoyin Yin at Wuhan University and the Shanghai Artificial Intelligence Laboratory recently proposed a modular machine learning ...

A new community-driven initiative evaluates large language models using Italian-native tasks, with AI translation among the ...

What if you could demystify one of the most fantastic technologies of our time—large language models (LLMs)—and build your own from scratch? It might sound like an impossible feat, reserved for elite ...