MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

Every medication in your cabinet, every material in your phone's battery, and virtually every compound that makes modern life ...

The tech tool has been subject to criticism and controversy since being launched by the department five years ago.

Data inconsistencies arise when formats, units, or collection practices change over time, undermining model reliability. Poor ...

For a project in Bangladesh, Prof. Mushfiq Mobarak and his team used machine-learning models applied to mobile phone records ...

Transparency is another priority. Given the decentralized and trust-based nature of Web3.0, the expert emphasizes ...

A new set of simple equations can fast-track the search for metal-organic frameworks (MOFs), a Nobel-Prize-winning class of ...

These developments suggest AI’s impact on materials R&D is as much organisational as it is technical, shifting labs toward ...

On January 9, 2026, the latest edition of Applied Artificial Intelligence for Drug Discovery was published online as a Springer Nature volume, spanning 27 chapters authored by leading international ...

Who is a data scientist? What does he do? What steps are involved in executing an end-to-end data science project? What roles are available in the industry? Will I need to be a good ...

Generative AI in medtech raises questions on safety, validation, and regulatory challenges, explored in MD&M West's "GenMLP" ...

Researchers demonstrate that misleading text in the real-world environment can hijack the decision-making of embodied AI ...