"Tabular data" is a broad term that encompasses structured data that generally fits into a specific row and column. It can be ...

Researchers at Stanford and the University of Washington have developed a model that performs comparably to OpenAI o1 and ...

When we hear about the risks of AI, we mostly hear about the risks of hallucinations. The risks go much further than that.

Typically, such predictive AI projects demand heavy involvement by experienced machine learning experts and a lengthy project lifecycle to define the requirements, prepare the data, train a model ...

A time series database management system (DBMS) efficiently handles large volumes of time-stamped data from sensors and ...

Researchers developed an automated system to help programmers increase the efficiency of their deep learning algorithms by simultaneously leveraging two types of redundancy in complex data structures: ...

Synthetic training data, or training data generated by other models, has helped drive costs down. Palmyra X 004, a model recently released by AI company Writer, trained almost entirely on ...

Until now, progress in AI had relied on bigger and better training runs, with more data and more computer power creating more intelligence. But once a model was trained, it was hard to use extra ...

In this interview, chief operating officer and cofounder of Upfront Healthcare, Carrie Kozlowski, OT, MBA, discusses the integration of artificial intelligence (AI) in health care, emphasizing both ...

Contributor Content Around 75% of healthcare providers invested in healthcare IT last year, with a particular focus in IT infrastructure and data platforms. The reasons for this notable uptake are ...