IP diligence comes in many forms—and in today’s environment, it demands more than ever before. Whether the context is a financing round, a strategic partnership, or a full acquisition, the ...

Causal inference is one of the most important and challenging aims in statistics and data science. Many fields, from clinical medicine to social sciences, strive to use empirical data to understand ...

CNBC’s MacKenzie Sigalos reports on Nvidia putting its $60 billion cash pile to work with a Groq licensing-and-talent deal that brings in TPU architect Jonathan Ross and on-chip inference tech. Canada ...

From In re Complaint of John Doe (8th Cir. Jud. Council), by Chief Judge Steven Colloton: This is a judicial complaint against a district judge who has participated in a hiring boycott against ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now DeepSeek AI, a Chinese research lab gaining ...

One of Gaelic football’s leading referees has expressed hesitancy about the application of proposed playing rule changes at club level in 2025. Four-time All-Ireland football final referee David ...

The Bayesian approach to statistical inference and other data analysis tasks gets its name from Bayes’s theorem (BT). BT specifies that a posterior probability for a hypothesis concerning a data ...

The STAC Machine Learning Model (MLM) extension provides a standard set of fields to describe machine learning models trained on overhead imagery and enable running model inference. The main ...

AI systems are the product of many different decisions made by those who develop and deploy them. From system purpose to how people interact with AI systems, we need to proactively guide these ...

A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally ...