Generating opportunities with generative AI
Rama Ramakrishnan helps companies explore the promises and perils of large language models and other transformative AI technologies.
Rama Ramakrishnan helps companies explore the promises and perils of large language models and other transformative AI technologies.
Complimentary approaches — “HighLight” and “Tailors and Swiftiles” — could boost the performance of demanding machine-learning tasks.
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.
MIT computer scientists developed a way to calculate polygenic scores that makes them more accurate for people across diverse ancestries.
AI models that prioritize similarity falter when asked to design something completely new.
StructCode, developed by MIT CSAIL researchers, encodes machine-readable data in laser-cut objects by modifying their fabrication features.
Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.
Open-source software by MIT MAD Fellow Jonathan Zong and others in the MIT Visualization Group reveals online graphics’ embedded data in the user’s preferred degree of granularity.
By focusing on causal relationships in genome regulation, a new AI method could help scientists identify new immunotherapy techniques or regenerative therapies.
Organizations will support government agencies in using evidence to advance economic mobility and racial equity in the wake of Covid-19.
Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.
PhD student Avni Singhal uses computational tools to help design new materials that address environmental challenges.
The MIT and Accenture Convergence Initiative for Industry and Technology announces new graduate fellows.
Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.
Researchers use synthetic data to improve a model’s ability to grasp conceptual information, which could enhance automatic captioning and question-answering systems.