MIT researchers remotely map crops, field by field
The team used machine learning to analyze satellite and roadside images of areas where small farms predominate and agricultural data are sparse.
The team used machine learning to analyze satellite and roadside images of areas where small farms predominate and agricultural data are sparse.
Performing this test could help doctors prevent dysfunction that can occur when the right and left ventricles of the heart become imbalanced.
Innovative AI system from MIT CSAIL melds simulations and physical testing to forge materials with newfound durability and flexibility for diverse engineering uses.
Research in Southeast Asia quantifies how much wildfire smoke hurts peoples’ moods; finds the effect is greater when fires originate in other countries.
Researchers developed a simple yet effective solution for a puzzling problem that can worsen the performance of large language models such as ChatGPT.
Scientists quantify a previously overlooked driver of human-related mercury emissions.
The sticky, wearable sensor could help identify early signs of acute liver failure.
The results will expand scientists’ understanding of heat flow in superconductors and neutron stars.
The method lets researchers identify and control larger numbers of atomic-scale defects, to build a bigger system of qubits.
A plastic microfluidic chip can remove some risky cells that could potentially become tumors before they are implanted in a patient.
The finding provides new insights into the ultrafast control of magnetic materials, with potential to enable next-generation information processing technologies.
Awarded $65.67 million from ARPA-H, the researchers will work to develop ingestible capsules that deliver mRNA and electric stimuli to treat metabolic disorders such as diabetes.
A county-by-county study shows where the U.S. job market will evolve most during the move to clean energy.
Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.
Dermatologists and general practitioners are somewhat less accurate in diagnosing disease in darker skin, a new study finds. Used correctly, AI may be able to help.