4 sources
A high-signal researcher for understanding the modern scaling playbook, especially around compute-optimal training, retrieval-augmented language models, and the text side of Gemini-era multimodal systems.
Researcher Profile
Editor reviewedRohan Anil
Gemini (multimodal foundation models)
Gemini co-lead for text modeling
One of the more useful people to study for the Gemini era because his work spans both the text-core of multimodal frontier models and the optimization tricks that make those systems cheaper and more stable to train.
Organizations
Google DeepMind
About This Page
This profile is meant to help you get oriented quickly: why this researcher matters, what to read first, and where to explore next.
Known For
The ideas, systems, and research directions that make this person worth knowing.
01
Gemini and Gemma-era text modeling
02
Optimization and distillation at large scale
03
Long-context evaluation work inside the Google stack
04
Gemini (multimodal foundation models)
05
Gemini: A Family of Highly Capable Multimodal Models
06
Gemini
Start Here
Canonical papers, project pages, or repositories that anchor this profile.
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