With the release of GPT-3, it seems the sky is the limit for this new paradigm of scaling large language models.

The development of large language models (LLMs) like GPT-2 marked a significant turning point for OpenAI, showcasing the potential of AI.

Generative AI and large language models, like ChatGPT, are incredibly powerful technologies that will soon become even more powerful.

Large language models, like ChatGPT, demonstrate that language can self-generate based on its internal structure, indicating that the principles governing human language generation may be the same as those in these models.

Large language models, like ChatGPT, are trained on vast amounts of text data, allowing them to generate human-like responses.

The emergence of coherent language models like GPT-3 and GPT-4 was crucial for enabling reinforcement learning from human feedback (RLHF).

The longer models like GPT-3 are able to think through complex problems, the better they perform.

OpenAI's release of GPT-2 in November 2019 marked a significant milestone with 1.5 billion parameters, followed by GPT-3, which was over 100 times larger and more capable than its predecessor.

Research indicated that previous models like GPT-3 were undertrained; despite their size, they hadn't been trained on enough text to reach their full potential. For instance, Chinchilla, a model smaller than GPT-3, outperformed larger models by being trained on four times more data.