  Large Language Models (LLMs) went from non-existent to ubiquitous in the
machine learning discourse within a few years. Due to the fast pace of the
field, it is difficult to identify the remaining challenges and already
fruitful application areas. In this paper, we aim to establish a systematic set
of open problems and application successes so that ML researchers can
comprehend the field's current state more quickly and become productive.
