1. This article discusses how language models are unsupervised multitask learners.
2. It explains how language models can be used to learn multiple tasks simultaneously, without the need for manual labeling or supervision.
3. The article also explores the potential of using language models to improve natural language processing (NLP) applications.
The article is written in a clear and concise manner, making it easy to understand the main points of the discussion. The author provides evidence to support their claims, such as citing research studies and experiments that have been conducted on language models. Additionally, the author does not appear to be biased towards any particular point of view or opinion, instead presenting an objective overview of the topic at hand.
However, there are some areas where the article could be improved upon. For example, while it does discuss potential applications of language models in NLP, it does not provide any examples or further details on how this could be achieved in practice. Additionally, there is no mention of any potential risks associated with using language models for NLP applications, which should be noted in order to provide a balanced view of the topic. Furthermore, while the author cites research studies and experiments that have been conducted on language models, they do not explore any counterarguments or alternative perspectives on these findings which could provide a more comprehensive understanding of the topic at hand.