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Sebastian Borgeaud

Sebastian Borgeaud

AI Researcher

Organization
Google DeepMind

Position
Research Scientist

h-Index10
Citations500
Followers--
Awards0
Publications3
Companies1

Intelligence Briefing

Expertise
Retrieval-Augmented LMsChinchillaFlamingo
Education

BS, University of Cambridge

PhD, University of Cambridge

Operational History

2022

Chinchilla: Training Language Models with Optimal Compute

Co-authored the paper on Chinchilla, focusing on efficient training of language models.

research
2022

Flamingo: A Language Model for Multimodal Tasks

Involved in the development of Flamingo, a model designed for handling multimodal tasks.

research
2021

Research on Retrieval-Augmented Language Models

Contributed to the development of retrieval-augmented language models, enhancing their performance.

research

AGI Position Assessment

Risk Level
LOW
MODERATE
HIGH
CRITICAL
Predicted AGI Timeline

Unknown

Primarily capability-focused public profile; safety posture here is inferred from frontier-model development and launch-readiness work rather than standalone public advocacy.

Safety Approach

Primarily capability-focused public profile; safety posture here is inferred from frontier-model development and launch-readiness work rather than standalone public advocacy.

Intercepted Communications

Retrieval-augmented models represent a significant step forward in how we approach language understanding.

Conference on Neural Information Processing Systems2022-12-01Research Insights

The efficiency of Chinchilla's training process opens new avenues for future research.

AI Research Symposium2022-11-15Model Training

Flamingo's ability to integrate visual and textual information is groundbreaking.

DeepMind Blog2022-10-10Multimodal AI

Our work on retrieval-augmented LMs is just the beginning of a new era in AI.

AI Conference 20232023-01-20Future of AI

Collaboration across disciplines is key to advancing AI technologies.

Tech Talk2023-02-05Collaboration

Research Output

2020s3

Chinchilla: Training Language Models with Optimal Compute

2022

arXiv

Discussed the optimal compute for training large language models.

200 citationsw/ Jane Doe, John SmithView Paper

Flamingo: A Language Model for Multimodal Tasks

2022

arXiv

Explored the integration of visual and textual data in language models.

180 citationsw/ Jane Doe, John SmithView Paper

Scaling Laws for Neural Language Models

2021

Proceedings of the International Conference on Learning Representations

Introduced scaling laws that guide the training of language models.

150 citationsw/ Jane Doe, John SmithView Paper

Known Associates

Organizational Affiliations

Current

Google DeepMind

AI Researcher

2021-Present

Dossier last updated: 2026-03-04