Eye On A.I.
#178 Terry Sejnowski on Integrating Human Development Principles into AI Models
Mar 27, 2024
Terry Sejnowski, President of the NeurIPS Foundation, discusses the future of neural networks in AI, integrating human brain aspects into models, reinforcement learning challenges, ethical considerations, and neuromorphic engineering. The podcast delves into societal impact, industry reshaping, and the potential of neuroscience to inform AI development.
52:35
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Quick takeaways
- Integrating human feedback and societal norms into AI development enhances models' understanding of human behavior.
- Scalability of neural network models, like GPT-4 with trillions of parameters, offers efficiency for solving real-world problems.
Deep dives
The Importance of Incorporating Developmental Elements into AI Models
Building AI models without incorporating elements important for human brain development like feedback from society may hinder their ability to understand human behavior and societal norms. Models like GPT-4 with trillions of parameters have shown remarkable capabilities, yet there is a need for integrating more human-centric values and developmental processes into AI systems. This includes a focus on feedback, societal guidelines, and sequential learning similar to how humans grow and adapt to their environment.
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