Co-creating climate futures with real-time data and spatial storytelling
Five multimedia projects communicating climate futures selected for 2023 WORLDING program, online and at MIT.
Technique could efficiently solve partial differential equations for numerous applications
MIT researchers propose “PEDS” method for developing models of complex physical systems in mechanics, optics, thermal transport, fluid dynamics, physical chemistry, climate, and more.
Inclusive research for social change
The MIT Summer Research Program pairs underrepresented students with opportunities to examine inequity through the IDSS Initiative for Combatting Systemic Racism.
Leveraging language to understand machines
Master’s students Irene Terpstra ’23 and Rujul Gandhi ’22 use language to design new integrated circuits and make it understandable to robots.
“MIT can give you ‘superpowers’”
MITx MicroMasters credential leads learner to accelerated graduate program in data science.
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.
Three MIT students selected as inaugural MIT-Pillar AI Collective Fellows
The graduate students will aim to commercialize innovations in AI, machine learning, and data science.
MIT campus goals in food, water, waste support decarbonization efforts
Series of 2030 quantitative campus impact goals aims to reduce emissions and inform and advance the Institute’s commitment to climate.
Automated system teaches users when to collaborate with an AI assistant
MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.
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.
Rewarding excellence in open data
MIT researchers who share their data recognized at second annual awards celebration.
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.
Explained: Generative AI
How do powerful generative AI systems like ChatGPT work, and what makes them different from other types of artificial intelligence?
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.