The wide adoption of AI in biomedical research raises concerns about misuse risks. Trotsyuk, Waeiss et al. propose a framework that provides a starting point for researchers to consider how risks ...

Advances in machine intelligence often depend on data assimilation, but data generation has been neglected. The authors discuss mechanisms that might achieve continuous novel data generation and the ...

Abstract: Despite the advancements of autonomous systems from decades of engineering, there is always the need to make them even more efficient and reliable. Machine learning holds great potential to ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. As an enthusiastic digital marketer who is passionate about search engine optimization (SEO) ...

Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...