GPT (Generative Pre-trained Transformer) is known for its impressive performance for several reasons:
Scale: GPT models are incredibly large, with billions of parameters. This scale allows them to understand and generate human-like text across a wide range of topics.
Pre-training: GPT models are pre-trained on vast amounts of text data, allowing them to learn grammar, context, and world knowledge. This pre-training provides a strong foundation for understanding and generating text.
Transfer Learning: GPT leverages transfer learning, meaning it can be fine-tuned for specific tasks with relatively small amounts of task-specific data. This makes it versatile and applicable to various domains.
Decoding Techniques: Modern GPT models use advanced decoding techniques like beam search and nucleus sampling, which improve the quality of generated text and make it more coherent.
Continual Improvement: GPT models have seen continuous iterations and improvements, resulting in better performance and reduced biases in later versions.
@sarvpriy_arya Backed by Microsoft, VC money 😂
IMO, they got first-mover advantage!
Jokes apart, I find Sam Altman an incredible person behind scaling it.
He says, the #1 reason behind scaling is "People like it & they share it with one another - like hey try this new thing called Chat-GPT, it's amazing"
I dont agree that the ChatGPT is one of the earliest AI products, there is so many before chat-gpt, but chat-gpt is the first one who get on the hype train. Good marketing strategy, a lot of partnerships do the thing.