As someone who works on a Python library solely devoted to making AI text generation more accessible to the normal person (
https://github.com/minimaxir/aitextgen ) I think the headline is misleading.
Although the article focuses on the release of GPT-Neo, even GPT-2 released in 2019 was good at generating text, it just spat out a lot of garbage requiring curation, which GPT-3/GPT-Neo still requires albeit with a better signal-to-noise ratio. Most GPT-3 demos on social media are survivorship bias. (in fact OpenAI's rules for the GPT-3 API strongly encourage curating such output)
GPT-Neo, meanwhile, is such a big model that it requires a bit of data engineering work to get operating and generating text (see the README: https://github.com/EleutherAI/gpt-neo ), and it's unclear currently if it's as good as GPT-3, even when comparing models apples-to-apples (i.e. the 2.7B GPT-Neo with the "ada" GPT-3 via OpenAI's API).
That said, Hugging Face is adding support for GPT-Neo to Transformers (https://github.com/huggingface/transformers/pull/10848 ) which will help make playing with the model easier, and I'll add support to aitextgen if it pans out.