ABSTRACT: This work introduces a novel Bayesian inspired regression method for the simultaneous estimation of model parameters and data uncertainties. The key mathematical result of this framework is ...

Google has introduced TurboQuant, a compression algorithm that reduces large language model (LLM) memory usage by at least 6x while boosting performance, targeting one of AI's most persistent ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Erik Steiger discusses the operational pain ...

Timely reconstruction of epidemic dynamics is essential for public health, and structured coalescent models constitute an essential tool for this purpose. However, statistical and computational ...

Lotteries are hard to win. The odds of hitting the Powerball jackpot are so tiny that, as a CNN commenter once put it, you have a better chance of becoming an astronaut, dating a supermodel, and ...

This blog post and audio file is another in the series "Defending the Algorithm™" written, edited and narrated by Pittsburgh, Pennsylvania Business, IP and AI Trial Lawyer Henry M. Sneath, Esq. and ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When OpenAI’s ChatGPT first exploded onto the scene in late 2022, it sparked a global obsession ...

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 ...

This blog post and audio file is another in the series "Defending the Algorithm™" written and edited by Pittsburgh, Pennsylvania Business, IP and AI Trial Lawyer Henry M. Sneath, Esq. and was authored ...

A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...