Associate Professor Catherine D’Ignazio thinks carefully about how we acquire and display data — and why we lack it for many things.
Category: Data
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Making it easier to verify an AI model’s responses
By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.
Study: Transparency is often lacking in datasets used to train large language models
Researchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.
Study: When allocating scarce resources with AI, randomization can improve fairness
Introducing structured randomization into decisions based on machine-learning model predictions can address inherent uncertainties while maintaining efficiency.
Looking for a specific action in a video? This AI-based method can find it for you
A new approach could streamline virtual training processes or aid clinicians in reviewing diagnostic videos.
An AI dataset carves new paths to tornado detection
TorNet, a public artificial intelligence dataset, could help models reveal when and why tornadoes form, improving forecasters’ ability to issue warnings.
AI generates high-quality images 30 times faster in a single step
Novel method makes tools like Stable Diffusion and DALL-E-3 faster by simplifying the image-generating process to a single step while maintaining or enhancing image quality.
Using generative AI to improve software testing
MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.
Startup accelerates progress toward light-speed computing
Lightmatter, founded by three MIT alumni, is using photonic technologies to reinvent how chips communicate and calculate.
How symmetry can come to the aid of machine learning
Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.