To address AI bias at its roots, we must understand the human heuristics that shape it. Unlike prior frameworks that focus ...

In 2026, tech leaders are learning a painful lesson: the problem with scaling AI adoption isn't understanding the algorithm, ...

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

Oregon Health & Science University researchers have developed a first-of-its-kind method to predict cancer patient survival ...

Embed technical assurance into vendor contracts, requiring evidence of performance/robustness/bias testing, transparency ...

When linguists want to tell one vowel from another, they measure the peaks of acoustic energy that the human vocal tract ...

Researchers have shown that blending quantum computing with AI can dramatically improve predictions of complex, chaotic ...

Large-scale applications, such as generative AI, recommendation systems, big data, and HPC systems, require large-capacity ...

DNA methylation data can be used to estimate biological age, but results across commercial tests differ, raising questions ...

AS ARTIFICIAL INTELLIGENCE COMPANIES EXPAND ACROSS THE U.S., THERE NEEDS TO STORE THAT DATA GROWS. WE ARE SEEING THIS MANIFEST IN REAL TIME AS DATA CENTERS ARE STARTING TO POP UP ALL ACROSS THE STATE.

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...