ABSTRACT As generative AI increasingly shapes consumer decision‐making, its implications for consumer well‐being remain unclear. Existing research largely focuses on the trade‐off between algorithmic efficiency and autonomy loss. This research advances understanding by proposing the algorithmic well‐being paradox, wher...
Jingru Xu, Chunli Ji, Haoqi Chu et al.· Psychology and Marketing· 0 citations
Recent advances in Artificial Intelligence (AI) have significantly improved geospatial disaster modeling applications, particularly in flood, landslide, wildfire, and earthquake susceptibility assessments. Machine learning (ML) and deep learning (DL) models integrated with geographic information systems (GIS) and remot...
Ömer Faruk UZUN· Turkish Journal of Remote Se...· 0 citations
Abstract: Today, the challenges in agriculture are so big and complicated that agricultural professionals can't just look at them and figure them out. This study looks at the newest deep learning and computer vision techniques for finding and sorting mango leaf diseases. Leaf diseases cut the quality and quantity of ma...
Large language models (LLMs) like ChatGPT are increasingly treated by the public as if theypossess subjective experience, with multiple studies probing the popular opinion on the matter. Thepresent study provides the first large-scale measurement of this phenomenon in Poland. Anationally distributed online survey panel...
Hubert Plisiecki· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
Artificial intelligence (AI) is increasingly being incorporated into clinical rehabilitation through computer vision, wearable sensors, machine learning, robotics, virtual reality, mobile applications, and remote monitoring. This structured evidence review summarizes published evidence on the clinical applications, out...
Bakytbek kyzy Archagul, Krishnasamy Gounder Ayyaswami Thamarai Krishnan, Gunasekaran Aswin Kumaravel et al.· Zenodo (CERN European Organi...· 0 citations
This paper presents the Intentional Field Ontology, a philosophical and speculative scientific framework in which reality is understood not as a collection of primary objects but as one reality whose oneness is never still. Its ground is a single primitive with two inseparable aspects. Unity names the holding: the comp...
Eric Needham· Zenodo (CERN European Organi...· 0 citations
This chapter examines the rapidly evolving role of Digital Twins in the Architecture, Engineering, and Construction industry, emphasizing their integration with Human-Centric Artificial Intelligence, ISO 19650 information management, and Industry 5.0 principles. Digital Twins, continuously updated through Building Info...
Machine-mediated output can inform, justify belief, guide inquiry, and sometimes acquire the practical force of institutional testimony. Yet the epistemic question whether a hearer may learn from such output is distinct from the speaker-side question of who owns the communicative commitment that the output presents. Th...
Nicholas Cott· Zenodo (CERN European Organi...· 0 citations
Abstract Convolutional neural networks (CNNs) have achieved state-of-the-art performance across computer vision tasks, including image classification, object detection, and medical image analysis. However, the opaque, black-box nature of these models limits their adoption in high-stakes domains such as healthcare, auto...
Ishan Gupta, Gaurav Jangid, Vishal Shrivastava et al.· Zenodo (CERN European Organi...· 0 citations
The convergence of Artificial Intelligence (AI) and pharmaceutical three-dimensional (3D) printing is proving to be a promising strategy for creating more precise and adaptable oral drug delivery systems. The review investigates the potential of AI-driven 3D printing to address some of the drawbacks of traditional manu...
Juego de ejercicios de Fisicoquímica (Grado en Farmacia): preparación de disoluciones, propiedades coligativas, fases, cinética y transporte. Cada estudiante recibe números distintos; un motor determinista calcula la solución y diagnostica el fallo por recálculo, y lleva a un ejercicio de refuerzo. La IA es opcional y...
Fernando Borrás, Montserrat Varea Morcillo· Zenodo (CERN European Organi...· 0 citations
Deep learning-based approaches have emerged as powerful tools for seasonal prediction, yet their skill remains limited for extreme anomalies, and warming climates may alter predictability sources. Here we present a convolutional neural network (CNN)-based framework to assess how seasonal predictability changes in a fut...
Seo‐Young Jo, Jeong-Hwan Kim, Daehyun Kang et al.· npj Climate and Atmospheric...· 0 citations
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
