How artificial neural networks build their own learning machinery
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
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Brain and cognitive sciences
3 Questions: What is the best path forward for AI in academia
MIT Statistics and Data Science Center Director Alexander (Sasha) Rakhlin shares important considerations for departments and institutions.
Read MoreEstimating suicide risk from text
A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.
Read MorePoitras Center to fuel early careers of 50 young scientists dedicated to psychiatric disorders research
Patricia and James Poitras ’63 provide fellowships for graduate students and postdocs who will shape the future of mental health research.
Read MoreAlexander Rakhlin named director of the MIT Statistics and Data Science Center
An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.
Read MoreBeacon Biosignals is mapping the brain during sleep
Founded by Jake Donoghue PhD ’19 and former MIT researcher Jarrett Revels, the company is creating an AI-driven platform to help diagnose and treat disease.
Read MoreImproving understanding with language
MIT senior Olivia Honeycutt investigates how the ways we communicate can shape our views of the world.
Read MoreAI algorithm enables tracking of vital white matter pathways
Opening a new window on the brainstem, a new tool reliably and finely resolves distinct nerve bundles in live diffusion MRI scans, revealing signs of injury or disease.
Read MoreAt MIT, a continued commitment to understanding intelligence
With support from the Siegel Family Endowment, the newly renamed MIT Siegel Family Quest for Intelligence investigates how brains produce intelligence and how it can be replicated to solve problems.
Read MoreA “scientific sandbox” lets researchers explore the evolution of vision systems
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
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