Today's episode with is one of my favorite conversations ever. In it, the hilarious and fascinating Dr. Kimberly Stachenfeld (of both DeepMind and Columbia) blows my mind by detailing relationships between human neuroscience and A.I.

More on Kim:
• Research Scientist at Google DeepMind, the world’s leading A.I. research group.
• Affiliate Professor of Theoretical Neuroscience at Columbia University.
• Research interests include deep learning, reinforcement learning, representation learning, graph neural networks and a brain structure called the hippocampus.
• Holds a PhD in Computational Neuroscience from Princeton.

Today’s episode should be fascinating for anyone (🧠 + 🤖 = 🤯).

In it, Kim details:
• Her research on computer-based simulations of how the human brain simulates the real world.
• What today’s most advanced A.I. systems (like Large Language Models) can do… and what they can’t.
• How language serves as an efficient compression mechanism for both humans and machines.
• How a leading neuroscience theory called the dopamine reward-prediction error hypothesis relates to reinforcement learning in machines.
• The special role of our brain’s hippocampus in memory formation.
• The best things we personally can do to improve our cognitive abilities.
• What it might take to realize Artificial General Intelligence (AGI)

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.