AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,055 papers
AI-driven cybersecurity in the software engineering field is discussed, where machine learning, deep learning, natural language processing, and reinforcement learning can be applied throughout the software development lifecycle to provide increased security.
A new scientific object – the Autonomous Recovery Efficiency Score (ARES) – is introduced – a quantitative measure of autonomous resilience, as well as a supporting foundation for future autonomous self-healing AI agentic infrastructure.
The design, deployment, and performance of cloud-based AI systems, especially scalability, system intelligence, and efficiency, and the challenges, such as latency problems in distributed computing systems, data privacy and security, and resource allocation, are indicated.
This study offers new means to design a resilient multi-agent system that is able to resist emergent threats by formalizing trust as a dynamic security vector and introduces an Agentic Trust Dynamics Theory as a conceptual theory to model the evolution, loss, and impact of trust on emerging security vulnerabilities in...
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The effectiveness of Management Information Systems (MIS) in elementary schools has become an important issue as educational governance increasingly requires efficient, accurate, transparent, and data-based management. This study aims to systematically examine the effectiveness of MIS implementation in elementary schoo...
This study develops a rule-based parts of speech tagging tool specifically for those people who want to learn or research on Bengali grammar and proposes and endeavor to implement this tool with an intent to achieve higher accuracy by optimizing memory overhead.
The Dark Forest hypothesis is usually presented as a general consequence of uncertainty, technological asymmetry and catastrophic vulnerability. This paper asks a narrower question: under which combinations of beliefs, capabilities, signalling conditions and network incentives does a Dark Forest actually emerge? A Dark...
The Dark Forest hypothesis is usually presented as a general consequence of uncertainty, technological asymmetry and catastrophic vulnerability. This paper asks a narrower question: under which combinations of beliefs, capabilities, signalling conditions and network incentives does a Dark Forest actually emerge? A Dark...
Dark Forest arguments commonly reduce interstellar strategy to a bilateral encounter between two persistent civilisations. A galaxy, however, is an open population in which civilisations enter, disappear, form selective relationships and occupy a spatially constrained network. This paper develops a continuous-time Gala...
Dark Forest arguments commonly reduce interstellar strategy to a bilateral encounter between two persistent civilisations. A galaxy, however, is an open population in which civilisations enter, disappear, form selective relationships and occupy a spatially constrained network. This paper develops a continuous-time Gala...
Reliability Beyond Accuracy in Crop Classification Benchmarks (Supplementary Materials)Introduction: Near-perfect crop-label accuracy can conceal uncertainty, perturbation sensitivity, and weak explanations. This study evaluates these reliability dimensions without treating benchmark classification as agronomic recomme...
Education Innovation
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
A Blog post by NVIDIA on Hugging Face
A Blog post by IBM Research on Hugging Face
A new machine-learning approach broke records for weather forecasting for an important time frame in emergency planning.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
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