Using CNNs for Inference

Convolutional neural networks (CNNs) are a type of neural network most often used for image recognition and classification. CNNs excel at these tasks because they are designed to automatically learn how to recognize spatial hierarchies in an image. Once these algorithms are trained, they can ‘infer’ the next best prediction for the task at hand. … Read More Using CNNs for Inference

A Brief History of GPUs

Let’s take a brief look at the history of GPUs before machine learning, and their current status in machine learning applications.

Why Software Will Eat the Machine Learning World

Seven years ago, Marc Andreessen wrote his now-infamous Wall Street Journal op-ed, “Why Software is Eating the World,” ushering in the beginning of a modern, software-driven economy. It’s taken a while for machine learning to catch up to this this trend. For the last seven years, machine learning has been primarily focused on building hardware… Read More Why Software Will Eat the Machine Learning World

Welcome to Limitless AI

Throughout history, there have been two ways of solving problems: work within limits, or find ways to overcome them. Today, we seem stuck in the “work within limits” phase of AI. While plenty of exciting work is being done in the field of deep learning, our ability to address real-world problems is still constrained by… Read More Welcome to Limitless AI

Machine Learning Inference: Why Use GPUs?

Or other domain-specific chipsets, for that matter? In the machine learning inference phase, training is complete and it’s time for a model to do its job: make predictions based on the incoming data. In other words, the model has learned all of the “assumptions” it needs to know to make predictions for the task at… Read More Machine Learning Inference: Why Use GPUs?