General-Purpose Systems
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Azure Linux 4.0 is Microsoft's first general-purpose Linux
Azure Linux 4.0 is Microsoft’s first general-purpose Linux Microsoft’s in-house Linux, the distribution that grew out of CBL-Mariner, just hit public preview as a general-purpose cloud OS you can run on any Azure VM. Here is why that is a real step in Microsoft’s Linux journey, not just a version bump. Microsoft shipped Azure Linux 4.0 into public preview at Build 2026, and for the first time you can run it on any Azure virtual machine, not just as the host underneath Azure Kubernetes Service.
Composable function systems as a general-purpose rendering framework
arXiv:2606.02226v1 Announce Type: new Abstract: Function systems exist as a natural language for the meshless creation and manipulation of complex objects while maintaining minimal memory on the Graphics Processing Unit (GPU) or Central Processing Unit (CPU). This paper proposes a new method for general-purpose (non-fractal) visualizations and simulations with function systems and introduces Quibble, a metaprogramming framework for composing such systems on the GPU. We also discuss several...
Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models
Announce Type: replace Abstract: Background: Oral diseases affect nearly 3.5 billion people worldwide, yet the comparative clinical potential of large-scale AI models in dentistry remains poorly understood. Three distinct model categories have emerged: language-generative models, discriminative vision foundation models, and dental-specific foundation models, with no unified review examining their relationships and collective limitations. Methods: Following PRISMA-ScR guidelines, we...
Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models
Announce Type: new Abstract: Background: Oral diseases affect nearly 3.5 billion people worldwide, yet the comparative clinical potential of large-scale AI models in dentistry remains poorly understood. Three distinct model categories have emerged: language-generative models, discriminative vision foundation models, and dental-specific foundation models, with no unified review examining their relationships and collective limitations.
Characterization of Multi-Model Agentic AI Systems on General Tasks via Trace-Driven Simulation
new Abstract: Agentic AI completes tasks through iterative planning, tool use, and reasoning based on observed outcomes. Despite its popularity, its system-level behavior remains poorly understood, particularly for complex datasets and agent architectures-owing to highly non-deterministic execution, prohibitive evaluation costs, and limited visibility into proprietary models. This paper presents GAIATrace, the first token-level trace dataset of two state-of-the-art agentic systems...
Scheduling Analysis of UAV Flight Control Workloads on PREEMPT_RT Linux Using a Raspberry Pi 5
arXiv:2604.19275v2 Announce Type: replace Abstract: Modern UAV architectures increasingly aim to unify high-level autonomy and low-level flight control on a single General-Purpose Operating System (GPOS). However, complex multi-core System-on-Chips (SoCs) introduce significant timing indeterminism due to shared resource contention. This paper performs an architectural analysis of the PREEMPT RT Linux kernel on a Raspberry Pi 5, specifically isolating the impact of kernel activation paths...
Large Language Lovers: Lived Experiences of Negotiating Agency and Platform Control in AI Companionship
Announce Type: replace Abstract: Individuals are turning to increasingly anthropomorphic, general-purpose chatbots for AI companionship, rather than roleplay-specific platforms. However, not much is known about how individuals perceive and conduct their relationships with general-purpose chatbots. We triangulated community discussions on Reddit (41k+ posts and comments), survey responses (n=43), and semi-structured interviews (n=13) which revealed internal dynamics, external influences, and...
Comparing ML-Specific and General Python Code Smells Across Project Characteristics
arXiv:2606.01882v1 Announce Type: new Abstract: Machine learning systems consist of general-purpose code as well as machine-learning-specific code. While ML-specific code smells have been identified, their connection to project characteristics and their interaction with overall code quality are not well understood.
Agentic Physical AI toward a Domain-Specific Foundation Model for Energy Systems: A Case Study on Nuclear Reactor Control
arXiv:2512.23292v5 Announce Type: replace Abstract: The prevailing paradigm in AI for physical systems: scaling general-purpose foundation models toward universal multimodal reasoning, confronts a barrier at the control interface. Frontier vision-language models achieve only 50-53% accuracy on basic quantitative physics tasks, behaving as approximate guessers that preserve semantic plausibility while violating physical constraints. Safety-critical control demands outcome-space guarantees...
Agentic Physical AI toward a Domain-Specific Foundation Model for Energy Systems: A Case Study on Nuclear Reactor Control
arXiv:2512.23292v4 Announce Type: replace Abstract: The prevailing paradigm in AI for physical systems: scaling general-purpose foundation models toward universal multimodal reasoning, confronts a barrier at the control interface. Frontier vision-language models achieve only 50-53% accuracy on basic quantitative physics tasks, behaving as approximate guessers that preserve semantic plausibility while violating physical constraints. Safety-critical control demands outcome-space guarantees...