GBH Morning Edition host Mark Herz spoke with MIT computer science professor Marzyeh Ghassemi about AI's use in medicine.

Security professionals can recognize the presence of drift (or its potential) in several ways. Accuracy, precision, and ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

As firms race to adopt AI, the real challenge lies in making data accessible, structured and usable across organizations. He ...

Data modeling is the blueprint that transforms raw information into structured, usable insights. By defining entities, relationships, and rules, it connects business needs to technical implementation.

The models are designed to predict someone’s risk of diabetes or stroke. A few might already have been used on patients.

The ability to collect data from electronic medical records, medical images, devices, diagnostics, wearables and apps means that more real world data (RWD) is available to be analyzed and derive ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...

This isn't about rejecting large models; it's about having the engineering discipline to use smaller, specialized models ...

By combining the efficiency of a Mixture-of-Experts architecture with the openness of an Apache 2.0 license, OpenAI is ...

Large language models can transmit harmful behavior to one another through training data, even when that data lacks any ...

Cirrascale runs on-prem Gemini on a Dell-made appliance running Intel and Nvidia CPUs and GPUs but doesn’t use Google’s ...