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Welcome to episode 150 of the ‘Eye on AI’ podcast. In this episode, host Craig Smith sits down with Yann LeCun, a Turing Award winner who has been instrumental in advancing convolutional neural networks and whose work spans machine learning, computer vision, and more.
Tune is as Craig and Yann explore the intricacies of AI, world models, and the challenges of continuous learning.
In this episode, Yann delves deep into the concept of a "world model" - systems that can predict the world's future states, allowing agents to make informed decisions. The discussion transitions to the challenges of training these models, particularly when dealing with diverse data like text and images. We then discuss the computational demands of modern AI models, with Yann highlighting the nuances between generative models for videos and language.
He also touches upon the idea of the "Embodied Turing Tests" and how augmented language models can bridge the gap between human-like behavior and computational efficiency.The spotlight then shifts to pressing concerns surrounding the open-source nature of AI models, with Yann articulating the legal ramifications and the future of open-source AI. Drawing from global perspectives, including China's stance on open-source, Yann underscores the imperative for a collaborative approach in the AI space, ensuring it's reflective of diverse global needs.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview, Oracle and Introduction
(02:42) Decoding The World Model and Gaia 1
(07:43) Energy and Computational Demands of AI
(08:06) Video vs. Text Processing & True AI Capabilities
(11:17) Embodied Turing Test & Augmented LLMs
(15:38) Is AI a Threat To Society?
(25:04) Where is AI Development Headed?
(31:06) Interplay of Neuroscience and AI**
(33:33) Yann's Vision, JEPA, and Learning Challenges
(39:05) Yann's Career, AI Progress, and Challenges
(44:47) The Open Source Debate in AI
(55:30) Oracle Cloud Infrastructure
#185 Damon Rasheed & Saurabh Jain: Achieving Up to 90% Accuracy in Predicting Drug Clinical Trial Outcomes with Opyl's Trialkey.ai
#184 André van Schaik: Building An Artificial Brain With 100 Billion Neurons
#183 Will Falcon: Lightning Studio, an iOS for AI Developers?
#182 Dragomir Anguelov: The Role of AI and Machine Learning in Waymo's Self-Driving Cars
#181 Nick Bostrom: The Meaning of Life in a World where AI can do Everything for Us
#180 Thomas Lah: Navigating AI Adoption in Tech Businesses
#179 Ylli Bajraktari: AI and National Security - The Race with China
#178 Terry Sejnowski on Integrating Human Development Principles into AI Models
#177 Björn Ommer: Diffusion Mods Explained By Stable Diffusion’s Creator
#176 Sergey Levine: Decoding The Evolution of AI in Robotics
#175 Aravind Srinivas: Revolutionizing Search with Perplexity AI
#174 Tianmin Shu: How World Models are Shaping The Future of AI
#173 Vincent Vanhoucke: How Is AI Helping Advance Robotics?
#172 Cristóbal Valenzuela: Can AI Revolutionize How We Create Art?
#171 Anna Marie Wagner: Harnessing AI for Synthetic Biology
#170 Richard Sutton on Pursuing AGI Through Reinforcement Learning
#169 Guillermo Rauch: How To Use AI to Improve Web Development
#168 Ian Bremmer on Regulating AI for a Safer Future
#167 Matt Powell: The Impact of AI on Security and Surveillance
#166 Itamar Arel: Is Voice AI the Future of Customer Service?
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