Archive of posts tagged: Machine Learning
Nanoscale Optoelectronic AI Processing
In a previous blog post, we summarized some advances in optical computing that enable the implementation of low-energy optical-convolutional layers using phase masks and angle-sensitive pixels. Such approaches also present multiple challenges, such as lack of...
Data Engineering for Everyone
The rise of open-source software necessitated a software-engineering revolution (new standards, tools, licenses, etc.) to overcome the problems facing large distributed teams working on enormous code bases. Today, machine learning (ML) builds atop this vibrant and...
Rethinking Data Storage and Preprocessing for ML
Machine learning (ML) — and in particular deep learning — applications have sparked the development of specialized software frameworks and hardware accelerators. Frameworks like PyTorch and TensorFlow offer a clean abstraction for developing and running...
Multi-Modal On-Device AI: Heterogeneous Computing Once More?
What is Multi-modal AI? Prior research on developing on-device AI solutions have primarily focused on improving the TOPS (Tera Operations Per Second) or TOPS/Watt of AI accelerators by leveraging sparsity, quantization, or efficient neural network architectures...Subscribe
