Cracking open the black box of automated machine learning
Interactive tool lets users see and control how automated model searches work.
Topic
Computer Science and Artificial Intelligence Laboratory (CSAIL)
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Q&A: Phillip Isola on the art and science of generative models
Image-translation pioneer discusses the past, present, and future of generative adversarial networks, or GANs.
Sensor-packed glove learns signatures of the human grasp
Signals help neural network identify objects by touch; system could aid robotics and prosthetics design.
Developing artificial intelligence tools for all
MIT Quest for Intelligence-sponsored undergraduate research projects demystify AI.
Bringing human-like reasoning to driverless car navigation
Autonomous control system “learns” to use simple maps and image data to navigate new, complex routes.
This robot helps you lift objects — by looking at your biceps
CSAIL system can mirror a user's motions and follow nonverbal commands by monitoring arm muscles.
MIT and U.S. Air Force sign agreement to launch AI Accelerator
New program will focus on rapid deployment of artificial intelligence innovations in operations, disaster response, and medical readiness.
Virtual reality game simulates experiences with race
A novel computational model that considers how users have been conditioned to think about race might facilitate training for teachers and students.
3Q: Hal Abelson on empowering kids through mobile technology
Through MIT App Inventor, Abelson aims to show children how they can use technology to shape their world.
How to tell whether machine-learning systems are robust enough for the real world
New method quickly detects instances when neural networks make mistakes they shouldn’t.
Wireless movement-tracking system could collect health and behavioral data
In some cases, radio frequency signals may be more useful for caregivers than cameras or other data-collection methods.
Using AI to predict breast cancer and personalize care
MIT/MGH's image-based deep learning model can predict breast cancer up to five years in advance.
Smarter training of neural networks
MIT CSAIL project shows the neural nets we typically train contain smaller “subnetworks” that can learn just as well, and often faster.
Merging cell datasets, panorama style
Algorithm stitches multiple datasets into a single “panorama,” which could provide new insights for medical and biological studies.
New approach could accelerate efforts to catalog vast numbers of cells
Data-sampling method makes “sketches” of unwieldy biological datasets while still capturing the full diversity of cell types.