DataFramed
#214 Learning & Memory, For Brains & AI, with Kim Stachenfeld, Senior Research Scientist at Google DeepMind
Jun 10, 2024
In this conversation, Kim Stachenfeld, a Senior Research Scientist at Google DeepMind, dives into the fascinating intersection of neuroscience and AI. She discusses how our understanding of human memory can enhance AI development. Kim explains the complexities of learning techniques and emphasizes the role of storytelling in data interpretation. The chat also covers the importance of customizable AI models and their potential to unlock scientific insights, alongside the challenges of applying cognitive principles to improve AI outcomes.
44:14
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Quick takeaways
- AI models accessing memory buffers enhance learning similar to the brain's episodic memory process.
- Brain's specialized memory systems contrast AI models' generalized learning approach.
Deep dives
The Role of Episodic Memory and Retrieval Augmented Generation in Learning
The brain's process of learning, notably involving episodic memory and the hippocampus, is compared to the retrieval augmented generation (RAG) in language models. Neuroscience and AI can benefit from understanding the similarities between memory storage in the brain and AI models accessing memory buffers to enhance learning.
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