The rapid expansion of Big Data has transformed data-driven decision-making across diverse sectors, including healthcare, cybersecurity, smart cities, and the Internet of Things (IoT). However, traditional data management platforms struggle to address the increasing volume, velocity, variety, and veracity of modern dat...
Ateeq Ur Rehman, Kapil Joshi, Vipul Kumar Singh et al.· The International journal...· 0 citations
BACKGROUND
Traditional rehabilitation medicine, primarily dependent on qualitative clinical assessment and static therapeutic protocols, faces significant challenges in scalability, objectivity, and dynamic adaptability. The integration of Artificial Intelligence (AI) is catalyzing a paradigm shift from "experience-dri...
Hao Wu, Ya-Li Yang, Li Wang et al.· Journal of Evaluation In Cli...· 0 citations
Spiral is a new theoretical framework for understanding how artificial intelligence can reason, design, and operate inside structured domains. The work presented in this manuscript introduces a cognitive geometry — a way of describing how an intelligent system moves through a space of constraints, possibilities, and la...
Marius Grobler· Zenodo (CERN European Organi...· 0 citations
Thailand’s digital transformation is presented as a route to inclusion, yet everyday accessibility remains unresolved for many disabled people. Combining policy document analysis with critical autoethnography, grounded in emancipatory disability research and analysed through a narrative approach, this article examines...
Quanchai Kerddaen· Information Communication &...· 0 citations
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This narrative review examines the evolution of artificial intelligence (AI) in healthcare, with a focus on the transition from early rule-based systems to modern deep learning architectures and their integration into clinical practice. We examine foundational technologies, including convolutional neural networks for i...
Abdulkadir Yıldırım, Ö. Özdemi̇r· Artificial Intelligence in M...· 0 citations
Building on developments in the UK, EU, US, China and Estonia, it proposes doctrinal and procedural refinements, narrowly targeted platform duties and court-supervised AI monitoring tools to preserve jury trial and open justice while maintaining credible fair-trial guarantees in an algorithmic information environment.
It is argued that the properties that make these models attractive - their generality, accessibility, and low deployment cost - undermine the conditions under which AI safety has historically been pursued, and safety assurance shifts from an intrinsic feature of building an AI tool to an optional add-on.
This dataset is an extension of the publication of the Database of Byzantine Book Epigrams (2023). The 2023 publication is a copy of the data used for the live application on dbbe.ugent.be. The present dataset aims to offer a simplified structure of the DBBE data, facilitating computational research and data analysis....
Kristoffel Demoen, Sofia Belioti, Gilbert Bentein et al.· Ghent University Academic Bi...· 0 citations
Findings provide important scientific evidence for early posture management in 20s adults, developing individualized fitness prescriptions, and enhancing the reliability of AI-based body assessment systems.
Suzanne Seo· Journal of the Korean Societ...· 0 citations
Current mainstream artificial intelligence models including convolutional neural networks and large language models rely on statistical fitting over fragmented input symbols. Vision models fit pixel distributions, while language models predict next‑token probabilities. This paradigm is essentially pattern‑matching and...
You Zhang· Zenodo (CERN European Organi...· 0 citations
A critical analysis of tools and trust mark frameworks intended to operationalize trustworthy AI (TAI), drawing on a comprehensive dataset from the OECD identifies significant asymmetries in ethical focus, lifecycle coverage, stakeholder targeting, and tool typology.
Michael Papademas, Xenia Ziouvelou, K. Karpouzis et al.· arXiv.org· 0 citations
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduNov 2, 2026
The MIT professors collaborated to identify the first AI-discovered antibiotic, a scientific breakthrough that is widely recognized as a milestone in AI-driven drug discovery.
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