It is the third-generation language prediction model in the GPT-n series (and the successor to GPT-2) created by OpenAI, a San Francisco-based artificial intelligence research laboratory. The model demonstrated strong few-shot learning on many text-based tasks. The training method is "generative pretraining", meaning that it is trained to predict what the next token is. The architecture is a standard transformer network (with a few engineering tweaks) with the unprecedented size of 2048-token-long context and 175 billion parameters (requiring 800 GB of storage). Given an initial text as prompt, it will produce text that continues the prompt. Generative Pre-trained Transformer 3 ( GPT-3 stylized GPT♳) is an autoregressive language model that uses deep learning to produce human-like text.
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