AI Economics

Today's historians of technology view us as being in the “deep learning era,” which started around 2012 and continues to this day. Future historians of technology will see it differently. The deep learning era ended in 2020, when foundation model capabilities took off. Today, we are in the foundation model era. The foundation model era is characterized by different metrics, models, processes, and economics. The latter is the eventual goal of this article, but before making claims about the macro we should start with the micro. Let's begin with metrics, which are key to understanding a given field's priorities. In the deep learning era, research advanced via increased performance on established benchmarks like ImageNet. Year after year, we pushed forward performance on known but unsolved tasks. We discovered and engineered thousands of techniques of varying importance, including both new architectures and optimizers as well as new training objectives, dataset augmentations, and problem

Today's historians of technology view us as being in the “deep learning era,” which started around 2012 and continues to this day. Future historians of technology will see it differently. The deep learning era ended in 2020, when foundation model capabilities took off. Today, we are in the foundation model era. The foundation model era is characterized by different metrics, models, processes, and economics. The latter is the eventual goal of this article, but before making claims about the macro we should start with the micro. Let's begin with metrics, which are key to understanding a given fi