Sara Hooker keynote speaker
- Building Robust and Interpretable Machine Learning Systems
- Challenges in Deploying AI Across Diverse Contexts
- Democratizing AI Research and Infrastructure
- Making AI More Inclusive and Globally Accessible
- Model Compression, Sparsity, and Efficient Deep Learning
- Rethinking Scale in AI: Efficiency vs. Size
- The Environmental Impact of Large AI Models
- The Future of Open and Community-Driven AI
Sara Hooker is a prominent AI researcher and the Head of Cohere For AI, a non-profit research lab focused on advancing open, inclusive, and community-driven artificial intelligence. Her work centers on improving the efficiency, robustness, and transparency of machine learning systems, particularly in the context of large-scale models.
Hooker has contributed influential research on model compression, sparsity, and understanding how neural networks generalize, helping challenge assumptions about scale and performance in modern AI. She is also a strong advocate for broadening participation in AI and ensuring that the benefits of advanced technologies are shared globally.
Before joining Cohere, she worked at Google Brain, where she conducted research on efficient deep learning and model interpretability. Hooker is widely recognized for her thought leadership on making AI more accessible, equitable, and environmentally sustainable.
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