AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
Category
2,336 papers
Various deep learning architectures including the domain-specific pre-trained transformers for the task of legal sentence classification are explored, finding that domain-specific transformer models lead the row.
This review presents a critical comparative analysis of MSI and HSI-based LU/LC classification and prediction frameworks by systematically examining remote-sensing platforms, preprocessing requirements, ML/DL architectures, prediction models, validation strategies, and XAI integration under heterogeneous experimental c...
AI assistants are increasingly used to support behavioural modelling from natural-language requirements, yet they provide little assurance that the resulting models are logically coherent. We argue that this limitation stems not only from the capabilities of large language models but also from the absence of explicit r...
It is concluded that AI literacy is no longer optional: the radiologist's role is not threatened by AI but transformed by it—from film reader to AI-augmented clinical imaging physician capable of extending world-class diagnostic care to underserved populations across India and globally.
Reach audiences
Advertise in front of researchers, engineers, and readers.
The proposed dual-stream framework enables accurate and interpretable multi-label classification of dental restorations from panoramic radiographs and demonstrates robust generalisation across independent datasets, which support its potential as an AI-assisted clinical decision-support tool for dental radiographic inte...
Conventional artificial intelligence in dentistry is limited by a 'diagnostic-executive disconnect', functioning primarily as static 'bystander intelligence'. This review aims to delineate the technical architecture of Embodied Artificial Intelligence (EAI) in dentistry and analyze its potential to bridge this gap thro...
It is suggested that the moderate achievement gains reported for GenAI may mask weaker retention and transfer and poorer metacognitive calibration, especially under unstructured use, and that structured tasks requiring learners to explain or critique AI output should reduce maladaptive offloading.
The obtained results validate the proposed AI-DSS framework with AFO as a promising solution to cover the distance between accuracy in a controlled lab environment and reliability in the field, providing a strong, explainable, and resource-efficient solution to the digital sustainable agriculture problem.
A four-layer hybrid intelligence framework (FLHIF) that unifies cloud model uncertainty quantification, social network analysis of data lineage graphs, DeepSeek-V4-driven multi-agent semantic reasoning, and adaptive weight learning via proximal policy optimization, and adaptive weight learning via proximal policy optim...
For non-Hermitian Hamiltonians, gain, loss, and non-reciprocity produce complex eigenvalues which, in turn, facilitate different kinds of topological phases. One example is the imaginary line-gap phase, where eigenvalues cannot lie on the real line. This notion was recently shown to explain the robust temporal localisa...
It is shown that fairness, accountability and transparency make distinct contributions to trust, while their combined contribution can also be represented as an overall FAT appraisal in the exploratory collective model.
The findings suggest that SMEs benefit from GenAI adoption when technological implementation is supported by entrepreneurial behavior and adaptive organizational practices, and when technological implementation is supported by entrepreneurial behavior and adaptive organizational practices.
Professor Deb Roy contends there should be someone who is “answerable” for every piece of text in public life, no matter its origins.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
GPT-Lab
· gpt-lab.eu
Oct 12, 2026
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.
MIT Statistics and Data Science Center Director Alexander (Sasha) Rakhlin shares important considerations for departments and institutions.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
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.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.