Simpler models can outperform deep learning at climate prediction
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
data
Helping data storage keep up with the AI revolution
Storage systems from Cloudian, co-founded by an MIT alumnus, are helping businesses feed data-hungry AI models and agents at scale.
Read MoreThis new approach could lead to enhanced AI models for drug and materials discovery.
Read MoreShake Shack’s Digital Playbook: More Tech, Same Hospitality?
How a fast-casual favorite retools its guest experience with kiosks, apps, and a data-driven touch.
Read MoreThe unique, mathematical shortcuts language models use to predict dynamic scenarios
Language models follow changing situations using clever arithmetic, instead of sequential tracking. By controlling when these approaches are used, engineers could improve the systems’ capabilities.
Read MoreResearchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.
Read MoreExploring data and its influence on political behavior
In MIT’s course 17.831 (Data and Politics), students are introduced to the power of analysis, visualization, and research-supported insight into political outcomes.
Read MoreBrave Leadership In Uncertain Times
Data suggests that the companies that thrive during uncertainty combine prudence with bold action.
Read MoreMerging AI and underwater photography to reveal hidden ocean worlds
The LOBSTgER research initiative at MIT Sea Grant explores how generative AI can expand scientific storytelling by building on field-based photographic data.
Read MoreUnpacking the bias of large language models
In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.
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