The panel determined that major issues remain to be considered that are not tied to any one of the seven standards, that is, that apply to multiple standards or to larger issues that the standards do ...

Version of Record: This is the final version of the article. This work proposes a new approach to analyse cell-count data from multiple brain regions. Collecting such data can be expensive and ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Abstract: Bayesian sampling methods based on Hierarchical models Bayesian analysis methods are commonly used to estimate and infer the parameters of hierarchical models. In this paper, a sampling ...

Chances are, you’ve seen clicks to your website from organic search results decline since about May 2024—when AI Overviews launched. Large language model optimization (LLMO), a set of tactics for ...

The new Gemini 2.5 Computer Use model can click, scroll, and type in a browser window to access data that’s not available via an API. The new Gemini 2.5 Computer Use model can click, scroll, and type ...

Artificial intelligence can solve problems at remarkable speed, but it's the people developing the algorithms who are truly driving discovery. At The University of Texas at Arlington, data scientists ...

Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the ...

Singapore-based AI startup Sapient Intelligence has developed a new AI architecture that can match, and in some cases vastly outperform, large language models (LLMs) on complex reasoning tasks, all ...

What if the way AI agents interact with tools and resources could be as seamless as browsing the web? Imagine a world where developers no longer wrestle with custom-built adapters or fragmented ...

A team from UT Arlington and UT Southwestern Medical School has developed a new computational framework that could help scientists identify key proteins that drive diseases like cancer. By improving ...