Author's Latest Posts

How Inferencing Differs From Training in Machine Learning Applications

Machine learning (ML)-based approaches to system development employ a fundamentally different style of programming than historically used in computer science. This approach uses example data to train a model to enable the machine to learn how to perform a task. ML training is highly iterative with each new piece of training data generating trillions of operations. The iterative nature of the tr... » read more

How Dynamic Hardware Efficiently Solves The Neural Network Complexity Problem

Given the high computational requirements of neural network models, efficient execution is paramount. When performed trillions of times per second even the tiniest inefficiencies are multiplied into large inefficiencies at the chip and system level. Because AI models continue to expand in complexity and size as they are asked to become more human-like in their (artificial) intelligence, it is c... » read more