General NLP Tasks

Although writing a new article is cool, the killer feature of GPT-3 is the ability to be 're-
programmed' for general NLP tasks without any fine-tuning. This is where OpenAI's real
ambition lies: having a model to do just about anything by conditioning it with a few
examples.

The paper showed a dozen of downstream tasks, ranging from the usual players such as
machine translation and question and answer to the unexpected new tasks such as
arithmetic computation and one-shot learning of novel words. Instead of reiterating the
details of each task, the rest of this article will discuss some common patterns across the
board.

The Role of the Few-Shots

What is the role of the few examples that fed to GPT-3 model before it makes predictions?
Do more examples improve the results?
OpenAI's GPT-3 Language Model_ A Technical Overview