GPT-3 was a massive model of 175 billion parameters, way more than GPT-2, Google’s T5 and Microsoft’s Turing NLG model. The main objective of GPT-3 was to improve the few-shot and zero-shot tasks with a large training data and computational parameters. The GPT-3 did not fail in achieving this objective and blew away all other language models in a plethora of language modelling tasks. Let’s dive deep into the world of GPT-3
Applied Singularity 