It seems like everyone wants to get an AI tool developed and deployed for their organization quickly—like yesterday. Several customers I’m working with are rapidly designing, building and testing ...

The 3D printing laboratory, operating within the Simulation Centre of the Faculty of Medicine at Masaryk University (SIMU), has contributed to the development of 3D printing in medicine by launching a ...

The ATT&CK Data Model (ADM) provides a type-safe, object-oriented interface for working with MITRE ATT&CK datasets. Built on STIX 2.1 compliance, it uses Zod schemas and TypeScript types to ensure ...

Tesla Inc. (NASDAQ:TSLA) continues to see sales pressure for its electric vehicles in the Chinese market. A new report indicates that the introduction of a new vehicle from a growing rival in the ...

Abstract: Entity-Relationship (ER) model is a high level conceptual data model and has become universally popular as their representations are very close to the way the end-users perceive data in a ...

The Cleveland Clinic is partnering with San Francisco–based startup Piramidal to develop a large-scale AI model that will be used to monitor patients’ brain health in intensive care units. Instead of ...

The potential applications of DTs extend beyond individual patient care to public health surveillance, hospital resource management, and epidemiological modeling. However, several challenges persist, ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Sea urchins climb onto kelp when their densities are so high they remove all drift kelp and then actively forage on attached, living kelp. (Credit: Steve Lonhart / NOAA MBNMS) Tipping points are the ...

Extensive research efforts are dedicated to studying and understanding the dynamics of the crystallization of an active pharmaceutical ingredient (API), aiming to optimize product quality, yield, and ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...