3 Questions: The pros and cons of synthetic data in AI
Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.
MIT researchers develop AI tool to improve flu vaccine strain selection
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
Learning from punishment
A new computational model makes sense of the cognitive processes humans use to evaluate punishment.
A new model predicts how molecules will dissolve in different solvents
Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
A shape-changing antenna for more versatile sensing and communication
You can adjust the frequency range of this durable, inexpensive antenna by squeezing or stretching its structure.
Eco-driving measures could significantly reduce vehicle emissions
New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.
Helping data storage keep up with the AI revolution
Storage systems from Cloudian, co-founded by an MIT alumnus, are helping businesses feed data-hungry AI models and agents at scale.
AI helps chemists develop tougher plastics
Researchers created polymers that are more resistant to tearing by incorporating stress-responsive molecules identified by a machine-learning model.
MIT tool visualizes and edits “physically impossible” objects
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
New algorithms enable efficient machine learning with symmetric data
This new approach could lead to enhanced AI models for drug and materials discovery.
New system dramatically speeds the search for polymer materials
The platform identifies, mixes, and tests up to 700 new polymer blends a day for applications like protein stabilization, battery electrolytes, or drug-delivery materials.
Robot, know thyself: New vision-based system teaches machines to understand their bodies
Neural Jacobian Fields, developed by MIT CSAIL researchers, can learn to control any robot from a single camera, without any other sensors.
A new way to edit or generate images
MIT researchers found that special kinds of neural networks, called encoders or “tokenizers,” can do much more than previously realized.
The unique, mathematical shortcuts language models use to predict dynamic scenarios
Language models follow changing situations using clever arithmetic, instead of sequential tracking. By controlling when these approaches are used, engineers could improve the systems’ capabilities.
This “smart coach” helps LLMs switch between text and code
The CodeSteer system could boost large language models’ accuracy when solving complex problems, such as scheduling shipments in a supply chain.