Illia Polosukhin

A foundational figure in modern sequence modeling whose work on the Transformer changed the technical direction of language and multimodal systems.

A foundational transformer co-author who is now worth following for a very different reason: he is one of the few people trying to build a serious frontier lab around alternatives to the default scaling path.

A foundational transformer researcher whose work still matters because it connects the original architecture shift to later efforts on efficiency, scaling, and sequence modeling infrastructure.

A high-signal person to follow for the research arc from early transformer work into later sequence, vision, and multimodal model design.

A foundational figure in the transformer era who also matters because he helped carry that research lineage into one of the most important enterprise language-model companies.

One of the clearest people to study if you want the throughline from early neural sequence models to transformers, efficient long-context variants, and modern reasoning systems.