Making MGAIC
generative AI research with real-world impact
Advancing the frontiers of generative AI
MIT researchers are pushing the boundaries of model architecture, safety, and alignment to enable generative AI systems that are more capable, trustworthy, and open. These breakthroughs support discovery and creativity across science, health, education, and the arts.
Designing AI that elevates human work
MGAIC supports the development of tools that amplify human intelligence—enhancing productivity, creativity, and decision-making in real-world domains. The goal is not to replace people, but to create AI that collaborates, augments, and empowers.
Engineering for scalable, responsible deployment
Scaling generative AI requires addressing critical infrastructure challenges—from compute efficiency and power consumption to data integrity and system robustness. MIT’s cross-disciplinary expertise helps design AI systems that are both powerful and sustainable.
Expanding access through education
To ensure AI benefits are broadly shared, MGAIC promotes open-source tools, new models of learning, and global collaborations. With a focus on inclusion and opportunity, we are helping shape a future where everyone can participate in AI innovation.
“The remarkable progress in generative AI we’ve seen over the past year has been fueled by advances in fundamental science and engineering — areas where MIT excels.”
— Sally Kornbluth, President of MIT
Our founding members
Drive the strategic direction of the Generative AI Impact Consortium and fund project ideas from MIT’s research community.
Student impact
The future of generative AI will be shaped by today’s students—and the MIT Generative AI Impact Consortium is committed to giving them a central role in that future.
Through research opportunities we support undergraduate and graduate students in tackling real-world challenges with generative AI. These opportunities empower students to collaborate with faculty and industry mentors, work on projects with societal significance, and gain hands-on experience at the forefront of AI research.
From developing open-source tools to exploring ethical deployment frameworks, students in the Consortium are not just learning about the future of AI—they’re building it. Their work spans disciplines, connects communities, and accelerates progress toward responsible, cross-sector solutions.
Funded projects
Multimodal Generative AI Framework for Brain Age Prediction and Future MRI Forecasting
Team: Marzyeh Ghassemi (IMES) and Laura Lewis (IMES)
Area: AI for Science / Healthcare
This project proposes a multimodal generative artificial intelligence framework that addresses limitations in current brain age prediction methodologies by integrating diverse neuroimaging modalities (structural and functional MRI, PET), clinical assessments, genetic factors, and lifestyle information to co-predict both brain age gap and future structural changes.
AI-Driven Tutors and Open Datasets for Early Literacy Education
Team: John Gabrieli (MIT McGovern Institute) and Satrajit Ghosh (MIT McGovern Institute
Area: AI for Education / Literacy
This project leverages generative AI to develop an AI-powered tutor for Pre-K–7th grade, particularly for at-risk students. Using large language models and speech recognition, the tutor provides real-time, personalized feedback while analyzing multimodal data—speech patterns, facial expressions, and engagement cues—to enhance learning.