<span class="vcard">Rachel Gordon | MIT CSAIL</span>
Rachel Gordon | MIT CSAIL
Algorithms Artificial Intelligence Cancer Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Defense Advanced Research Projects Agency (DARPA) Diagnostics Electrical Engineering & Computer Science (eecs) Health sciences and technology machine learning Medicine MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Technology and society

New hope for early pancreatic cancer intervention via AI-based risk prediction

MIT CSAIL researchers develop advanced machine-learning models that outperform current methods in detecting pancreatic ductal adenocarcinoma.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) Language machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

AI agents help explain other AI systems

MIT researchers introduce a method that uses artificial intelligence to automate the explanation of complex neural networks.

Artificial Intelligence Center for Brains Minds and Machines Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Electrical Engineering & Computer Science (eecs) image processing machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

Image recognition accuracy: An unseen challenge confounding today’s AI

“Minimum viewing time” benchmark gauges image recognition complexity for AI systems by measuring the time needed for accurate human identification.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Electrical Engineering & Computer Science (eecs) image processing machine learning MIT Schwarzman College of Computing Research School of Engineering

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.

Algorithms Artificial Intelligence Brain and cognitive sciences Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) Imaging machine learning Microscopy MIT Schwarzman College of Computing Nanoscience and nanotechnology Neurons Neuroscience Research School of Engineering Synapses

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.

Aircraft Algorithms Artificial Intelligence Aviation Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Distributed Robotics Laboratory Drones Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Networks Research Robotics School of Engineering

AI copilot enhances human precision for safer aviation

Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.

Aircraft Algorithms Artificial Intelligence Aviation Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Distributed Robotics Laboratory Drones Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Networks Research Robotics School of Engineering

AI copilot enhances human precision for safer aviation

Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Electrical Engineering & Computer Science (eecs) Laboratory for Nuclear Science machine learning MIT Schwarzman College of Computing Physics Research School of Engineering School of Science

From physics to generative AI: An AI model for advanced pattern generation

Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical engineering and computer science (EECS) Human-computer interaction Language machine learning MIT Schwarzman College of Computing School of Engineering

Multi-AI collaboration helps reasoning and factual accuracy in large language models

Researchers use multiple AI models to collaborate, debate, and improve their reasoning abilities to advance the performance of LLMs while increasing accountability and factual accuracy.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Defense Advanced Research Projects Agency (DARPA) Electrical Engineering & Computer Science (eecs) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Technology and policy Technology and society

Using AI to protect against AI image manipulation

“PhotoGuard,” developed by MIT CSAIL researchers, prevents unauthorized image manipulation, safeguarding authenticity in the era of advanced generative models.