Machine-learning models for absorption, distribution, metabolism, excretion and toxicity (ADMET) are usually reported on benchmark splits drawn from the same curated collections used to train them. External validation is rarer, and when it is attempted, the assumption that a public dataset carrying a matching endpoint...
The utilization of artificial intelligence (AI) is transforming underwater surveillance. It has made underwater surveillance smart, autonomous, and real-time. This chapter discusses the ways that AI technologies such as machine learning, deep learning, computer vision, and reinforcement learning are being incorporated...
Sonia Vatta, Jasmeet Singh Sobti· Digital Technologies for Und...· 0 citations
Although underwater ecosystems have many species and provide economic benefits, they are now being threatened by actions such as unregulated fishing, smuggling by sea, underwater attacks, and violations of boundaries. Older ways of surveillance find it tough to follow what happens in these big and complex waters due to...
Arpita Nayak, Ipseeta Satpathy, Vishal Jain et al.· 0 citations
In this opening chapter, we set the stage for the book by describing both the opportunities and risks that artificial intelligence (AI) presents as it becomes increasingly embedded in critical domains such as healthcare, education, transportation, energy, conservation, and security. We argue that researchers and practi...
Ayan Mukhopadhyay, Yevgeniy Vorobeychik· River Publishers eBooks· 0 citations
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As renewable energy sources and electric vehicles proliferate, managing energy efficiently under uncertainty has become critical. This chapter focuses on optimization challenges in electric vehicle (EV) charging and vehicle-tobuilding (V2B) integration, formalizing them as sequential decision-making problems under unce...
Fangqi Liu, Rishav Sen, Abhishek Dubey et al.· River Publishers eBooks· 0 citations
Within a cross-sectional design, higher DIT-2 N2 scores were associated with higher self-reported responsible academic use of generative AI and should be interpreted as an important correlate rather than a primary determinant of responsible AI use.
Robinson Bernardino Almanza Cabe, Angela Aurora Mamani Calizaya, Florencia Beatriz Herrera Córdoba et al.· Frontiers in Education· 0 citations
Successful omnichannel retail management requires integrated strategies because customers evaluate product aspects differently across online and offline channels. However, prior research has relied on macro-level or qualitative analyses that cannot quantify which specific aspects are associated with customer satisfacti...
Large language models (LLMs) are increasingly embedded in knowledge work, raising the question to what extent they can systematically influence their users’ decisions—a question with commercial as well as societal stakes. Across an exploratory study and two pre-registered experiments grounded in moral foundations the...
Giles Hirst, W. Johnson, April Li et al.· Scientific Reports· 0 citations
The rapid evolution of AI-powered cyberattacks has revolutionized the environment of cybersecurity, with adversaries using the means of automation of sophisticated attacks, which are beyond the capabilities of the existing cybersecurity environment. The estimated amount of cybercrimes in the world is $10.5 trillion ann...
I. Obiokafor, M. Onyesolu, F. C. Aguboshim· World Journal of Advanced Re...· 0 citations
The proposed framework demonstrated clinically meaningful performance for automated oral cancer detection and grading, with explainability analysis confirming alignment with established histopathological criteria, suggesting that such a framework have the potential to serve as a viable decision-support tool for ENT pra...
L. Rahul, Swagatika Pradhan· The Egyptian Journal of Otol...· 0 citations
The graphic presented represents a summary of the overall workflow used for creating, characterizing, and medical uses of the brain organoids derived from stem cells, and represents a detailed process of brain organoid research and its application.
H. E. Marei, Anwarul Hasan· Cellular and molecular neuro...· 0 citations
A deployable Explainable AI (XAI) framework for dysglycemia screening in Indonesia that was deployed as an Android application combining visual SHAP explanations with LLM-generated narratives illustrates an approach for developing transparent, population-representative mHealth AI that is meaningful and accessible to it...
Latifa Dwiyanti, Raynard Tanadi, Bernardus Willson et al.· Discover Artificial Intellig...· 0 citations
MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
Microsoft Research Blog· microsoft.comOct 30, 2026
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.
Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.
Microsoft Research Blog· microsoft.comOct 29, 2026
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
