One of the most hilarious things you can do with an LLM-based chatbot is to ask it to do calculations. If it’s a well-written ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Abstract: A deep variational inference learning (DVIL) framework is proposed for data detection for cell-free massive multiple-input multiple-output (MIMO). The ...

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Google says its new TurboQuant method could improve how efficiently AI models run by compressing the key-value cache used in LLM inference and supporting more efficient vector search. In tests on ...

Abstract: To identify a reliable model for a dynamic system with nonideal measurements, this article develops a novel parameter transfer identification (PTI) algorithm that leverages the knowledge ...

It’s hard to ignore the seismic shifts brought about by algorithm-driven content. Every time you scroll through your social media feed or check your favorite news app, algorithms are diligently at ...

While the creation of this new entity marks a big step toward avoiding a U.S. ban, as well as easing trade and tech-related tensions between Washington and Beijing, there is still uncertainty ...

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 ...

Its deal with Merck & Co. is the latest in a series of Variational AI collaborations. (iStock/Getty Images Plus) Merck & Co. has doubled down on its partnership with Variational AI, striking a deal ...

At first glance, Bayes’ Theorem appears deceptively simple—it provides a clear framework for updating our beliefs about an unknown quantity after observing new data. The core idea is to combine prior ...