Data
Data

Data

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3 Questions: The pros and cons of synthetic data in AI

Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.

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3 Questions: On biology and medicine’s “data revolution”

Professor Caroline Uhler discusses her work at the Schmidt Center, thorny problems in math, and the ongoing quest to understand some of the most complex interactions in biology.

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MIT researchers develop AI tool to improve flu vaccine strain selection

VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.

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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.

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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.

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New algorithms enable efficient machine learning with symmetric data

This new approach could lead to enhanced AI models for drug and materials discovery.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Quest for Intelligence Research School of Engineering

The 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.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab National Science Foundation (NSF) Research School of Engineering

Study could lead to LLMs that are better at complex reasoning

Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.

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Exploring 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.

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Merging 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.