Figure S4: High resolution version of the Supplemental Figure S4. FINAL DATASET.CSV: The complete beer dataset of this work (chemical + sensory), except for the RateBeer scores (these are proprietary data owned by RateBeer - contact the authors and RateBeer to gain full access). Model predictions vs actuals XGBR.CSV: A...
Michiel Schreurs, Supinya Piampongsant, Florian A. Theßeling et al.· Zenodo (CERN European Organi...· 0 citations
This study examines how AI-generated financial recommendations and digital interface design influence users’ trust, perceived control, decision confidence, and willingness to follow financial guidance. The study begins from a simple but important question: when an AI system recommends what a person should do with their...
Ruchi Gaur Anamika Yadav· Zenodo (CERN European Organi...· 0 citations
Safety training can teach an AI to make fewer mistakes. It can also teach it to hide themistakes it still makes. Both can produce better test scores. This paper explains how thathappens, examines experiments that have produced it, and asks what follows for the risk ofa major accident. A passed test is reassuring when t...
This study examines how AI-generated financial recommendations and digital interface design influence users’ trust, perceived control, decision confidence, and willingness to follow financial guidance. The study begins from a simple but important question: when an AI system recommends what a person should do with their...
Ruchi Gaur Anamika Yadav· Zenodo (CERN European Organi...· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
This study examined Generative Artificial Intelligence utilisation and academic integrity among master’s students in Lagos State University, Nigeria. The AI literacy and competence, institutional regulation, and academic ethics awareness as determinants of academic integrity among master's students at Lagos State unive...
Muhammad Sidique MALIK, Taofeek Olawale Shittu, Rukayat Towobola MALIK· Zenodo (CERN European Organi...· 0 citations
Despite significant pilot activity in Generative AI across financial institutions (78% running active pilots), only a fraction transition these projects into operational production. While commercial maturity exists for underlying technologies such as retrieval-augmented generation and private endpoints, significant org...
Rakesh Ganesan· Zenodo (CERN European Organi...· 0 citations
Abstract This paper introduces an acid-base equilibrium (titration curve) model from biochemistry as an analogy and dynamic mathematical framework to explain the non-linear jump phenomenon in outcome creation during interaction with Generative AI. Traditional project management and business performance metrics have rel...
Hideo Kajino· Zenodo (CERN European Organi...· 0 citations
Purpose This study examines whether generative AI chatbot features are associated with user autonomy and competence and whether these psychological states are, in turn, associated with GenAI misuse intention, conceptualized here as an empowerment backfire mechanism. Design/methodology/approach Drawing primarily on the...
Shiu‐Wan Hung, Jyun-Hao Jian· Asia Pacific Journal of Mark...· 0 citations
Abstract This paper introduces an acid-base equilibrium (titration curve) model from biochemistry as an analogy and dynamic mathematical framework to explain the non-linear jump phenomenon in outcome creation during interaction with Generative AI. Traditional project management and business performance metrics have rel...
Hideo Kajino· Zenodo (CERN European Organi...· 0 citations
Window Theory - AI (wtAI): A Falsifiable Framework for Flexibility-Fragility Coupling in Large Language Models This is a six-part research series examining a structural pattern in decoder-based next-token-prediction systems deployed as dialogue and instruction agents. It is written for readers with a background in mach...
Wai-Hung (Pan) Tam· Zenodo (CERN European Organi...· 0 citations
Window Theory - AI (wtAI): A Falsifiable Framework for Flexibility-Fragility Coupling in Large Language Models This is a six-part research series examining a structural pattern in decoder-based next-token-prediction systems deployed as dialogue and instruction agents. It is written for readers with a background in mach...
Wai-Hung (Pan) Tam· Zenodo (CERN European Organi...· 0 citations
Window Theory - AI (wtAI): A Falsifiable Framework for Flexibility-Fragility Coupling in Large Language Models This is a six-part research series examining a structural pattern in decoder-based next-token-prediction systems deployed as dialogue and instruction agents. It is written for readers with a background in mach...
Wai-Hung (Pan) Tam· Zenodo (CERN European Organi...· 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.
