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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The Future of the Brain offers an unprecedented look at the quest to unravel the mysteries of the human brain. It features original essays by top researchers, including Christof Koch, George Church, and the Moser couple, discussing technological advances in brain mapping and the challenges of understanding the brain's complex data. The book sheds light on the implications of brain science for medicine, psychiatry, and human consciousness.
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The Norton Psychology Reader offers a diverse sampling of psychology's key concepts, featuring selections from renowned authors like Steven Pinker, Oliver Sacks, and Malcolm Gladwell. It covers topics such as the mind
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In 'The Birth of the Mind', Gary Marcus addresses the nature vs. nurture debate by linking the Human Genome Project findings to brain development. He explains how genes provide instructions for building complex biological systems, not as blueprints but as recipes that interact with environmental factors. The book offers insights into genetic engineering and the interplay between genes and environment in shaping human thought.
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Gary Marcus and Ernest Davis provide a lucid assessment of the current science in AI, explaining what today’s AI can and cannot do. They argue that current AI systems, based on deep learning, are narrow and brittle, and that achieving true artificial general intelligence requires moving beyond statistical analysis and large data sets. The authors suggest that by incorporating knowledge-driven approaches and common sense, we can build AI systems that are reliable and trustworthy in various aspects of our lives, such as homes, cars, and medical offices.
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Gary Marcus's "Kluge" explores the human mind's design as a collection of workarounds and hacks rather than a perfectly engineered system. He argues that our cognitive abilities are a patchwork of evolved mechanisms, often inefficient and prone to errors. The book uses examples from various fields, including psychology, neuroscience, and computer science, to illustrate the kludgy nature of human thought. Marcus emphasizes the importance of understanding these limitations to improve our decision-making and problem-solving skills. He suggests that by acknowledging the imperfections of our cognitive architecture, we can develop strategies to mitigate biases and make more rational choices.
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The Algebraic Mind
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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.
Machine Learning Street Talk (MLST) 
