Keeping up with the latest research is vital for scientists, but given that millions of scientific papers are published every ...

Most of what we know about the ocean just skims the surface, literally. We’ve gathered a large quantity of data on the oceans from satellites, but most of ...

Oh, sure, I can “code.” That is, I can flail my way through a block of (relatively simple) pseudocode and follow the flow. I ...

Intel is looking for a Data Scientist who specializes in Demand and Supply Planning to develop advanced analytics and machine learning systems that will optimiz ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Both are pouring serious resources into building genuine technical bridges between OpenAI's AI capabilities and Snowflake's ...

The UC Berkeley School of Information is a global bellwether in a world awash in information and data, boldly leading the way with education and fundamental research that translates into new knowledge ...

I'll explore data-related challenges, the increasing importance of a robust data strategy and considerations for businesses ...

Condensed-matter physics and materials science have a silo problem. Although researchers in these fields have access to vast amounts of data – from experimental records of crystal structures and ...

Generative AI models have been used to create enormous libraries of theoretical materials that could help solve all kinds of ...

Something extraordinary has happened, even if we haven’t fully realized it yet: algorithms are now capable of solving ...