progress in the capabilities of AI systems is predictably driven by progress in three inputs—compute, data, and algorithms. Much of the progress of the last 70 years has been a result of researchers training their AI systems using greater computational processing power, often referred to as “compute”, feeding the systems more data, or coming up with algorithmic hacks that effectively decrease the amount of compute or data needed to get the same results. Understanding how these three factors have driven AI progress in the past is key to understanding why most people working in AI don’t expect progress to slow down any time soon.