BI 189 Joshua Vogelstein: Connectomes and Prospective Learning
Jun 29, 2024
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Joshua Vogelstein discusses the world's largest connectome, focusing on a fruit fly's brain. He explains the concept of prospective learning in AI compared to retrospective learning, highlighting its potential. The podcast covers audio/video sync issues, data cleaning challenges, and the importance of anatomy in understanding brain function.
Connectome research in fruit flies gives insights into neural circuits and impacts medical studies, such as addiction.
Understanding the human connectome can transform approaches to spirituality and consciousness by studying meditation effects on brain activity.
Prospective learning offers a novel AI concept, integrating time for efficient task switching and adaptability in machine learning models.
Deep dives
Connectomes and Understanding Circuit Mechanisms
Connectomes provide insights into circuit mechanisms by examining the connectome of a fruit fly, offering a deeper understanding of how neurons connect and potentially impacting medical research, such as addiction studies. Researchers face challenges in obtaining funding for connectome studies and sometimes encounter pushback in academic circles, highlighting the importance of anatomical understanding in explaining brain functions.
Implications of Connectome Research
Connectome research serves as a resource for researchers to explore various cognitive states, supporting medical research, and potentially aiding in predicting and preventing neurological disorders. The potential impact extends to psychiatric treatments and understanding the brain's structural changes in response to specific behaviors or conditions.
Enhancing Consciousness Through Connectomes
Understanding the human connectome could revolutionize approaches to spirituality and consciousness. By examining differences in functional connectomes between novice and expert meditators, insights are gained into how meditation practices may alter brain activity to enhance aspects of consciousness and mindfulness. This research could lead to personalized interventions aimed at achieving desired cognitive states more efficiently.
Introduction of Prospective Learning Concept
Prospective learning, introduced at a Lifelong Learning Agents conference, demonstrates a coherent concept distinct from traditional machine learning. The approach addresses issues like catastrophic forgetting, where existing algorithms struggle to switch between tasks without forgetting prior learning. Prospective learning integrates time into algorithm performance, predicting task switches to improve adaptability and learning efficiency.
Comparison with Reinforcement Learning
In contrast to reinforcement learning's focus on decision-making impacting future outcomes, prospective learning emphasizes incorporating time as a critical variable for effective learning. By modifying existing frameworks like transformers to recognize absolute time instead of relative positions, prospective learning enhances algorithm performance amid evolving, time-sensitive tasks. This approach aims to mitigate failures in AI due to neglecting temporal dynamics, offering more efficient and adaptable learning models.
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Jovo, as you'll learn, is theoretically oriented, and enjoys the formalism of mathematics to approach questions that begin with a sense of wonder. So after I learn more about his overall approach, the first topic we discuss is the world's currently largest map of an entire brain... the connectome of an insect, the fruit fly. We talk about his role in this collaborative effort, what the heck a connectome is, why it's useful and what to do with it, and so on.
The second main topic we discuss is his theoretical work on what his team has called prospective learning. Prospective learning differs in a fundamental way from the vast majority of AI these days, which they call retrospective learning. So we discuss what prospective learning is, and how it may improve AI moving forward.
At some point there's a little audio/video sync issues crop up, so we switched to another recording method and fixed it... so just hang tight if you're viewing the podcast... it'll get better soon.
0:00 - Intro
05:25 - Jovo's approach
13:10 - Connectome of a fruit fly
26:39 - What to do with a connectome
37:04 - How important is a connectome?
51:48 - Prospective learning
1:15:20 - Efficiency
1:17:38 - AI doomerism
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