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New MIT studies support the idea that the brain uses a process similar to a machine-learning approach known as “self-supervised learning.” This type of machine learning allows computational models to learn about visual scenes based solely on the similarities and differences between them, with no labels or other information. ....
Neuroscientists often use neural networks to model the kind of tasks the brain performs, in hopes that the models could suggest new hypotheses regarding how the brain itself performs those tasks. But a group of MIT researchers urges that more caution should be taken when interpreting these models. ....
In our most recent peer-reviewed paper published in Frontiers in Neural Circuits, A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex, we put forward a novel theory for how the neocortex works. In this updated blog about the Thousand Brains Theory of Intelligence originally published in March 2018, Jeff Hawkins and Christy Maver describe the key insights of our theory and how it compares to the classic view of the hierarchy, as well as its implications for AI. ....
People who grew up in cities are better at navigating grid-like environments full of straight routes, while those raised in more rural settings are best at navigating routes that meander ....