Viewpoint: Moore’s law isn’t broken - it’s overheated

Recent advancements in machine learning, computer vision, natural language processing, deep learning and more are already impacting life and humanity in ways seen and often unseen. This is especially true as it relates to artificial intelligence (AI). The demands of AI are growing at a blistering rate. Training AI models today requires ultra-high performance computer chips, leading to what one might refer to as a ‘space race’ among top technology companies to build, acquire, or get exclusive access to the highest-performance chips as soon as they come to market.

The problem is the latest high-performance chips are being produced using yesterday’s design ideas and technology. This results in progressively smaller chips, that consume a similar amount of energy, leading to unsustainable levels of energy density, much of which is dissipated in the form of heat that then negatively impacts the performance of the chip and reduces the energy efficiency of the compute system overall. It is this “shrink = energy density increase” problem that is at the root of the divergence from Moore’s Law; a divergence which itself threatens the pace of AI innovation. An additional important but less talked about negative impact of the energy density problem is the effect that removing all of the wasted energy in the form of heat is having on the environment.