In this engaging discussion, Gary Marcus, a renowned scientist and AI entrepreneur, alongside Luis Lamb, Secretary of Innovation for Science and Technology in Brazil, dive into the future of artificial intelligence. They challenge the limitations of deep learning and advocate for a hybrid neurosymbolic approach to enhance AI understanding and reasoning. Topics include the importance of integrating symbolic reasoning, exploring the complexities of abstraction, and the role of intention in knowledge acquisition. Their insights illuminate the path towards more sophisticated AI systems that can genuinely understand and reason like humans.
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insights INSIGHT
ML vs. Programming
Machine learning, like curve fitting, relates inputs to outputs, while programmers define algorithms independently of data.
This difference impacts how these systems generalize and handle novel situations.
insights INSIGHT
Deep Learning Limitations
Gary Marcus's previously criticized views on deep learning's limitations are now widely accepted.
Even his critics like Yann LeCun now acknowledge issues with semantics and generalization.
question_answer ANECDOTE
Marcus vs. Bengio Debate
Gary Marcus and Yoshua Bengio debated symbolic vs. connectionist approaches.
They disagreed on the core representations and how to integrate different AI approaches.
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Professor Gary Marcus is a scientist, best-selling author, and entrepreneur. He is Founder and CEO of Robust.AI, and was Founder and CEO of Geometric Intelligence, a machine learning company acquired by Uber in 2016. Gary said in his recent next decade paper that — without us, or other creatures like us, the world would continue to exist, but it would not be described, distilled, or understood. Human lives are filled with abstraction and causal description. This is so powerful. Francois Chollet the other week said that intelligence is literally sensitivity to abstract analogies, and that is all there is to it. It's almost as if one of the most important features of intelligence is to be able to abstract knowledge, this drives the generalisation which will allow you to mine previous experience to make sense of many future novel situations. Also joining us today is Professor Luis Lamb — Secretary of Innovation for Science and Technology of the State of Rio Grande do Sul, Brazil. His Research Interests are Machine Learning and Reasoning, Neuro-Symbolic Computing, Logic in Computation and Artificial Intelligence, Cognitive and Neural Computation and also AI Ethics and Social Computing. Luis released his new paper Neurosymbolic AI: the third wave at the end of last year. It beautifully articulated the key ingredients needed in the next generation of AI systems, integrating type 1 and type 2 approaches to AI and it summarises all the of the achievements of the last 20 years of research. We cover a lot of ground in today's show. Explaining the limitations of deep learning, Rich Sutton's the bitter lesson and "reward is enough", and the semantic foundation which is required for us to build robust AI.