Tensor Processing
Tensor processing refers to a range of techniques and technologies used to efficiently process and manipulate Tensors, multi-dimensional arrays used to represent complex data in various fields, including Machine Learning, Physics, and Engineering. The concept of tensor processing has gained significant attention in recent years, particularly with the development of Tensor Processing Units (TPUs), specialized hardware designed to accelerate tensor computations. Ashish Vaswani and his team have made notable contributions to the field, introducing techniques such as Self-Attention and Transformers that rely heavily on tensor processing. These advancements have enabled breakthroughs in areas like Natural Language Processing and Computer Vision. Tensor processing is also closely related to Linear Algebra and Optimization Techniques, which provide the mathematical foundations for efficient tensor computations.