Research
Research

AI accelerates problem-solving in complex scenarios

A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.

New method uses crowdsourced feedback to help train robots

Human Guided Exploration (HuGE) enables AI agents to learn quickly with some help from humans, even if the humans make mistakes.

Search algorithm reveals nearly 200 new kinds of CRISPR systems

By analyzing bacterial data, researchers have discovered thousands of rare new CRISPR systems that have a range of functions and could enable gene editing, diagnostics, and more.

Synthetic imagery sets new bar in AI training efficiency

MIT CSAIL researchers innovate with synthetic imagery to train AI, paving the way for more efficient and bias-reduced machine learning.

Technique enables AI on edge devices to keep learning over time

With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.

This 3D printer can watch itself fabricate objects

Computer vision enables contact-free 3D printing, letting engineers print with high-performance materials they couldn’t use before.

Using AI to optimize for rapid neural imaging

MIT CSAIL researchers combine AI and electron microscopy to expedite detailed brain network mapping, aiming to enhance connectomics research and clinical pathology.

2023-24 Takeda Fellows: Advancing research at the intersection of AI and health

Thirteen new graduate student fellows will pursue exciting new paths of knowledge and discovery.

The brain may learn about the world the same way some computational models do

Two studies find “self-supervised” models, which learn about their environment from unlabeled data, can show activity patterns similar to those of the mammalian brain.

Accelerating AI tasks while preserving data security

The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.