Machine Learning
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Intelligence Begins with Memory: From Reflexes to Attention
Why associative memory is the oldest mechanism of intelligence—and still its computational core. By Tomaso Poggio & John Gabrieli Buchet Modern AI systems—transformers, diffusion models, large language models—appear astonishingly sophisticated. Yet beneath their apparent complexity lies a very simple and ancient idea: Store associations between patterns, and retrieve them by similarity. This is associative memory.
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The Second Pillar: Genericity
Why learning works at all—and why not all functions are learnable By Tomaso Poggio & Pierfrancesco Beneventano In our last post, we explored the first pillar of intelligence: Sparse Compositionality. It explains the structure of the functions we want to learn: they must be sparse, hierarchical, and built from simple reusable components. Sparse compositionality tells
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The First Principle: Nature Builds with LEGO Bricks
Why can we understand a complex world? Because it is not a random mess — it is a hierarchy of reusable parts By Tomaso Poggio & Daniel Mitropolsky In our last post, we argued that modern AI resembles the period between Volta and Maxwell: we can build remarkable systems, but we do not yet have