5 thinkers, books, and ideas connected to this field.
American AI researcher who was a key contributor at OpenAI — co-authoring the foundational GPT and CLIP papers — and is one of the most influential researchers in the development of large language models and multimodal AI.
The 2017 paper by Vaswani, Shazeer, Uszkoreit, and five other Google Brain researchers introducing the Transformer architecture — replacing recurrent networks with self-attention — which became the foundation for GPT, BERT, and all subsequent large language models.
German computer scientist and Google Brain researcher, co-author of 'Attention Is All You Need', who proposed the core insight that attention mechanisms alone could replace recurrent networks entirely.
American computer scientist who worked on speech recognition and natural language processing at IBM before joining Renaissance Technologies — where he eventually became co-CEO and dramatically expanded the computing infrastructure behind the Medallion Fund.
OpenAI's 2020 language model — the first AI system to demonstrate convincingly that scaling transformer models produces qualitative leaps in capability, triggering the modern AI race.