In this third video of our Transformer series, we’re diving deep into the concept of Linear Transformations in Self Attention. Linear Transformation is fundamental in Self Attention Mechanism, shaping ...

A new technical paper titled “Analog in-memory computing attention mechanism for fast and energy-efficient large language models” was published by researchers at Forschungszentrum Jülich and RWTH ...

In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.

A technical paper titled “Lean Attention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers” was published by researchers at Microsoft. “Transformer-based models have ...

Processing 200,000 tokens through a large language model is expensive and slow: the longer the context, the faster the costs spiral. Researchers at Tsinghua University and Z.ai have built a technique ...