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The brain may learn about the world the same way some computational models do

New MIT studies support the idea that the brain uses a process similar to a machine-learning approach known as โ€œself-supervised learning.โ€ 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.
Aran Nayebi Rylan Schaeffer Ila Fiete Mehrdad Jazayeri Robert Yang Mikail Khona
Source: mit.edu

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Computational model mimics humans' ability to predict emotions | MIT News | Massachusetts Institute of Technology

A new computational model can predict peopleโ€™s emotions โ€” including joy, gratitude, confusion, regret, and embarrassment โ€” as well as human observers can. The model, developed at MIT, is designed to mimic how observers reason about each otherโ€™s emotions.
United Kingdom Nick Chater Sean Dae Houlihan Joshua Tenenbaum Rebecca Saxe Johnw Jarve
Source: mit.edu

KSRM Table of Contents Page

This book offers a general review of the voluminous theoretical and experimental literature pertaining to physical self-replicating systems and self-replication. The principal focus here is on self-replicating machine systems. Most importantly, we are concerned with kinematic self-replicating machines: systems in which actual physical objects, not mere patterns of information, undertake their own replication. Following a brief burst of activity in the 1950s and 1980s, the fiel...
Taylor Santa Claus Assembly Of Mechanical Parts Software Simulators For Robots Design Tradeoffs In Nanofactory Assembly Process Specialization Proposals For Future Research Molecular Positional Assembly For Self

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