When GPT-3 was released, it was one of the most astonishing IT inventions of 2020.

GPT-3 and the Natural Language Processing Revolution Its stories are so believable that OpenAI, the author of GPT-2, has decided not to release the full version to the public due to concerns of “large language models being used to generate deceptive, biased, or abusive language at scale.” This decision, however, sparked several controversies in the computer science industry as the technology is deemed to be one of the most breakthrough technologies of the decade that can lead to what we are going to write about in this article, AI coding engines. One such example is the English-speaking unicorn story. The first thing about GPT-2 is that it can write coherent stories with perfect English, given any context. GPT-2 was based on the transformer model, a deep learning model in the fields of natural language processing that follows an encoder-decoder structure to generate an output without relying on recurrence and convolutions.

In short, GPT-2 is an AI language generative model that was trained on a dataset of eight million web pages to predict the next words in 40 GB of Internet text. When Generative Pre-Trained Transformer 2 (or GPT-2 for short) came out in February 2019, it topped the Artificial Intelligence news for various reasons. The Beginning of the AI-Language Model GPT-2 and Its Initial Impact

Ai writing code