Improved algorithms may be more important for AI performance than faster hardware

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. When it comes to AI, algorithmic innovations are substantially more important than hardware -- at least where the problems involve billions to trillions of data points. That's the conclusion of a team of scientists at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), who conducted what they claim is the first study on how fast algorithms are improving across a broad range of examples. Algorithms tell software how to make sense of text, visual, and audio data so that they can, in turn, draw inferences from it. For example, OpenAI's GPT-3 was trained on webpages, ebooks, and other documents to learn how to write papers in a humanlike way.