GPT-3, a Giant Step for Deep Learning and NLP

A few days ago, OpenAI announced a new successor to their Language Model (LM) - GPT-3. This is the largest model trained so far, with 175 billion parameters. While training this large model has its merits, reading a large portion of 72 pages can be tiresome. In this blog post I'll highlight the parts that I find interesting for people familiar with LMs, who merely wish to know (most of) the important points of this work. "The diversity of tasks the model is able to perform in a zero-shot setting suggests that high-capacity models trained to maximize the likelihood of a sufficiently varied text corpus begin to learn how to perform a surprising amount of tasks without the need for explicit supervision" This is an excerpt from the paper accompanying GPT-2.