AI outputs vary because confidence varies. Corroboration and entity optimization turn inconsistent AI visibility into consistent presence.

Submodular maximization is a significant area of interest in combinatorial optimization, with numerous real-world applications. A research team led by Xiaoming SUN from the State Key Lab of Processors ...

This note examines the utility of pseudorandom variables (prv) in Global Search and Optimization (GSO) using Central Force Optimization (CFO) as an example. Most GSO metaheuristics are stochastic in ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

In this video, we explore why Spotify's shuffle feature isn't truly random and operates based on an algorithm. We discuss the reasons behind our preferences for non-random shuffle, the results of an ...

Racial and Ethnic Disparities Along the Treatment Cascade Among Medicare Fee-for-Service Beneficiaries With Metastatic Breast, Colorectal, Lung, and Prostate Cancers CONKO-007, an ...

If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost.

Hi, thank you for sharing the code for VideoSAGE — really appreciate your contribution! I noticed that the results vary across different runs, even when I fix all random seeds. I added the following ...

In the high-stakes arena of modern software development, where speed and security collide, a quiet revolution is unfolding. While GenAI dominates headlines with its creative potential, a less ...

Amsterdam’s struggles with its welfare fraud algorithm show us the stakes of deploying AI in situations that directly affect human lives. What Amsterdam’s welfare fraud algorithm taught me about fair ...