Saving seaweed with machine learning
PhD candidate Charlene Xia is developing a low-cost system to monitor the microbiome of seaweed farms and identify diseases before they spread.
At Mass STEM Week kickoff, MIT RAISE announces Day of AI
Artificial intelligence is top-of-mind as Governor Baker, President Reif encourage students to “see yourself in STEM.”
Artificial networks learn to smell like the brain
When asked to classify odors, artificial neural networks adopt a structure that closely resembles that of the brain’s olfactory circuitry.
Accelerating the discovery of new materials for 3D printing
A new machine-learning system costs less, generates less waste, and can be more innovative than manual discovery methods.
These neural networks know what they’re doing
A certain type of artificial intelligence agent can learn the cause-and-effect basis of a navigation task during training.
A dispatch and routing platform to improve deliveries
Wise Systems has grown from an MIT class project to a company helping multinationals improve last-mile logistics.
Deep learning helps predict traffic crashes before they happen
A deep model was trained on historical crash data, road maps, satellite imagery, and GPS to enable high-resolution crash maps that could lead to safer roads.
3 Questions: Kalyan Veeramachaneni on hurdles preventing fully automated machine learning
Researchers hope more user-friendly machine-learning systems will enable nonexperts to analyze big data — but can such systems ever be completely autonomous?
Blockchain technology could provide secure communications for robot teams
The transaction-based communications system ensures robot teams achieve their goal even if some robots are hacked.
A robot that finds lost items
This robotic arm fuses data from a camera and antenna to locate and retrieve items, even if they are buried under a pile.
Using AI and old reports to understand new medical images
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
How quickly do algorithms improve?
MIT scientists show how fast algorithms are improving across a broad range of examples, demonstrating their critical importance in advancing computing.
SpectrumX collective launches the first NSF Spectrum Innovation Initiative Center
MIT Haystack Observatory will be part of the new radio spectrum management and coordination center.
Research collaboration puts climate-resilient crops in sight
MIT professors Dave Des Marais and Caroline Uhler combine plant biology and machine learning to identify genetic roots of plant responses to environmental stress.
Making self-driving cars safer through keener robot perception
PhD student Heng Yang is developing algorithms to help driverless vehicles quickly and accurately assess their surroundings.