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2,492 papers
Praktisch nutzbare Künstliche Intelligenz entstand aus dem Bündnis kluger Köpfe mit den rechentechnischen Fähigkeiten Boolescher Automaten – natürliche Intelligenz dagegen aus Selbstorganisation und Evolution. Dieser zweite Weg rückt mit dem neuromorphen Rechnen zunehmend wieder in das Blickfeld von Wissenschaft und Pr...
This study examines real-time monitoring and automatic management of passenger flow on metropolitan escalators using artificial intelligence and computer vision technologies. The aim is to develop the conceptual foundations of an automatic hazard detection system based on deep learning algorithms (CNN, YOLO, transforme...
Centralized cloud architectures increasingly struggle to meet the latency, data-sovereignty, and bandwidth demands of industrial AI workloads. This paper presents Hybrid Edge AI Node, a distributed processing architecture that unifies six previously separate research threads — hierarchical edge orchestration, hierarchi...
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For four decades, deep artificial neural networks have relied on continuous vector spaces, dense floating-point General Matrix Multiplications (GEMM: hl+1 = σ(Wlhl + bl)), and gradient-based backpropagation. While effective in data centers, this paradigm incurs severe thermodynamic, memory bandwidth, and numerical stab...
Exact (symbolic, no sampling) Weingarten calculus for networks of Haar-random SO(m) matrices, via two structurally independent computation engines (a "cut and glue" symbolic surgery engine, and a "direct index sum" engine using union-find and bucket elimination). This is the reusable computational core extracted from a...
ABSTRACT This study develops a defense-oriented framework for infrastructure-aware c5i service orchestration across tactical edge, regional compute, and military data centers within an integrated military C5I environment. The research addresses the engineering problem of maintaining mission information advantage when p...
This comprehensive foundational curriculum module examines the cyber-physical systems architecture, state estimation theory, and feedback control loops of modern autonomous systems within the Prep4Uni open STEM curriculum. Core Thematic & Pedagogical Foundations: Systems-Level IDEF0 Functional Modeling: Deconstructs au...
This survey reviews the technical evolution, system architectures, and deployment challenges of LLM-driven UAVs across perception, planning, control, multi-agent coordination, and edge–cloud computing, and separates semantic-reasoning latency, control timing, power, task outcomes, hardware, and validation settings to a...
Paper I of the Guarino Infrastructure Dependency Metric (GIDM). First revision, 20 September 2026. DOI 10.5281/zenodo.22864280. Infrastructure fails in chains. The February 2021 freeze in Texas began at frozen wellheads, ran through load-shed gas processing plants, took 61,800 MW of generation offline, and ended in boi...
This paper develops the next foundational layer of the AASC formalism: the exact structure of admissibility once non-degenerate determinate construction has already incurred the kernel roles of Admissibility, Standing, Reference, and Irreversibility. Its central contribution is to distinguish three questions that are o...
Exact (symbolic, no sampling) Weingarten calculus for networks of Haar-random SO(m) matrices, via two structurally independent computation engines (a "cut and glue" symbolic surgery engine, and a "direct index sum" engine using union-find and bucket elimination). This is the reusable computational core extracted from a...
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
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.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
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