MIT engineers design structures that compute with heat
By leveraging excess heat instead of electricity, microscopic silicon structures could enable more energy-efficient thermal sensing and signal processing.
By leveraging excess heat instead of electricity, microscopic silicon structures could enable more energy-efficient thermal sensing and signal processing.
New “biomimetic” model of brain circuits and function at multiple scales produced naturalistic dynamics and learning, and even identified curious behavior by some neurons.
New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.
“MorphoChrome,” developed at MIT, pairs software with a handheld device to make everyday objects iridescent.
Founded by two MIT alumni, Samsara’s platform gives companies a central hub to learn from their workers, equipment, and other infrastructure.
“MechStyle” allows users to personalize 3D models, while ensuring they’re physically viable after fabrication, producing unique personal items and assistive technology.
While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.
With the help of AI, MIT Research Scientist Judah Cohen is reshaping subseasonal forecasting, with the goal of extending the lead time for predicting impactful weather.
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
A new method could enable users to design portable medical devices, like a splint, that can be rapidly converted from flat panels to a 3D object without any tools.
MIT community members made headlines with key research advances and their efforts to tackle pressing challenges.
From robotics to apps like “NerdXing,” senior Julianna Schneider is building technologies to solve problems in her community.
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
MIT-IBM Watson AI Lab researchers developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.