Infrastructure & Hardware

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Showing 31–60 of 149
  • Data Center Dynamics · EN Infrastructure & Hardware
    DCD Intelligence: Data Center Workforce Survey Results 2026
    DCD 2026 workforce survey: data center growth outpaces talent
    DCD Intelligence published its 2026 Data Center Workforce Survey, reporting that data center growth is outpacing the supply of talent. The findings point to skilled staffing for operations and maintenance as a constraint even as capital spending accelerates.
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  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    Rank and computation of the pathlifting Jacobian of a DAG ReLU network
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  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Selection Is Retrieval, Abstention Is Not: On-Device Tool Routing over 70 Korean-English Actions
    Neural Network Reinforcement Learning Software Engineering
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    Learning to Program Adaptive Non-Local Observables for Machine Learning
    Machine Learning Neural Network Reinforcement Learning
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  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    DyMT-ESB: Dynamic Multi-Turn Evaluation of Social Bias in User-LLM Interactions
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Weakening Neurons: An Input-Output Functionality in Transformers with Outsize Influence
    Deep Learning Reinforcement Learning Transformer
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  • arXiv cs.AI (Artificial Intelligence) · EN Funding & M&A
    Hypothesis-Driven Autonomous Materials Synthesis with Multimodal LLM Agents
    AI Agents
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  • arXiv cs.LG (Machine Learning) · EN Inference & Efficiency
    Peak-Aware Short-Term Load Forecasting Across Distribution Grid Aggregation Levels
    Inference Machine Learning Reinforcement Learning
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  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    The evolution of sex for artificial intelligence: a population-genetic framework for multigenerational model populations
    Retrieval-Augmented Generation (RAG)
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  • arXiv cs.AI (Artificial Intelligence) · EN Infrastructure & Hardware
    TRIPROBE: Probing Task Separability Beyond Classification for XAI
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  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    VoiceTrace: A Benchmark and Retrieval Framework for Who-Said-What Speech Retrieval
    Embeddings Reinforcement Learning Speech Processing
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  • Data Center Dynamics · EN Infrastructure & Hardware
    Serverfarm expands North American data center development fund to $3.89 billion
    Serverfarm expands North American development fund to $3.89bn
    Serverfarm has expanded its North American data center development fund to $3.89 billion after closing an additional $895 million. The raise adds to the steady accumulation of capital earmarked for North American data center construction.
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  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Planning or Improvisation? Stress-Testing the Poetry Planning Site on Open Models and Open Cross-Layer Transcoders
    Claude Neural Network
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  • Data Center Dynamics · EN Infrastructure & Hardware
    Microsoft files to build data center campus in Prince William County, Virginia
    Microsoft files for data center campus in Prince William County, VA
    Microsoft
    Microsoft has filed to build a data center campus in Prince William County, Virginia, proposing two buildings outside Gainesville. The filing extends the company's buildout in Northern Virginia, already the densest data center cluster in the US.
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  • Data Center Dynamics · EN Infrastructure & Hardware
    AWS “unable to restore access” to data centers hit by Iran strikes
    AWS says it cannot restore access to data centers hit by strikes
    AWS said it is unable to restore access to data centers damaged by Iranian strikes, with the damage exceeding what its availability zone design was built to withstand. The account underscores the limits of redundancy assumptions under armed conflict.
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  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Market Signal Injection: Adversarial Context Manipulation of LLM Pricing Agents
    AI Agents Machine Learning
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  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    Attention Dispersion as a Diagnostic Signal for Hallucination in Large Language Models
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  • ITmedia AI+ · JA New Model Releases
    北海道、データセンター事業者向けの「お願い」表明 AI向けに立地推進の裏で懸念も
    Hokkaido asks data center firms to adopt clean power, coexist locally
    Hokkaido published its stance on data center siting on September 15, asking operators to adopt decarbonized, energy-efficient technology and to coexist with host communities. The prefecture is promoting data centers for AI and chips, but flags power procurement strain and resident concerns over waste heat, noise and landscape.
    Read original (ITmedia AI+) ↗
  • ITmedia AI+ · JA Safety & Evaluation
    OpenAI、AI安全性でAnthropic、Google DeepMindと協議中──Bloomberg報道
    OpenAI in AI safety talks with Anthropic and Google DeepMind
    Anthropic Google NVIDIA OpenAI
    OpenAI policy chief Chris Lehane said the company has spent weeks in AI safety talks with rivals Anthropic and Google DeepMind, arguing no antitrust exemption is needed. FTC chair Andrew Ferguson said he would treat such requests with deep suspicion, as rival bills on superintelligence and narrow exemptions surface in Congress.
    Read original (ITmedia AI+) ↗
  • ITmedia AI+ · JA Infrastructure & Hardware
    富士通、国産CPU「モナカ」販売 スパコン技術を結集した“小さなチップ”に託す「3兆円のAIビジネス」の行方
    Fujitsu to ship MONAKA, its Fugaku-derived AI CPU, from November
    Fujitsu said on Sept 14 it will sell FUJITSU-MONAKA, a domestically designed AI CPU, and the Fujitsu MONAKA Server from November, targeting data center operators and financial customers first. Derived from the A64FX Fugaku supercomputer chip, it anchors a 3 trillion yen AI business goal for fiscal 2035.
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  • The Register (Data Centre) · EN Infrastructure & Hardware
    Higher-enriched uranium for datacenters has DoE all aglow
    US DoE backing aims to speed HALEU supply for datacenter reactors
    The Register reported on HALEU, the higher-enriched uranium fuel behind small modular reactors pitched for datacenter power. Production remains slow, but Nusano says federal backing from the US Department of Energy could accelerate output, eventually.
    Read original (The Register (Data Centre)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    Bridging the Gap Between Homogeneous and Heterogeneous Asynchronous Optimization Is Surprisingly Difficult
    Machine Learning
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  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    Det-LIME: Detector-Aware, Multi-Instance Local Interpretable Model-Agnostic Explanations for Automated Marine Mammal Detection
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  • arXiv cs.AI (Artificial Intelligence) · EN Inference & Efficiency
    JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management
    Inference Machine Learning Neural Network Quantization Software Engineering
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  • arXiv cs.AI (Artificial Intelligence) · EN Inference & Efficiency
    Coupled Calibration and Learning: Mitigating Teacher Bias in LLM Distillation without Target-Domain Reward Feedback
    Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • NVIDIA Developer Blog · EN Inference & Efficiency
    Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each
    NVIDIA compares dense and MoE models on active parameters and throughput
    Generative AI Inference Mixture of Experts (MoE) NVIDIA
    NVIDIA published a guide to choosing between dense and Mixture-of-Experts models. Using Nemotron 3.5 Lightning, it shows how a 30B model can activate only 3B parameters per token while keeping the larger model's capacity, and maps active parameters to throughput.
    Read original (NVIDIA Developer Blog) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    Tables Decoded: DELTA for Structure, TARQA for Understanding
    Reinforcement Learning Software Engineering
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  • NVIDIA Developer Blog · EN Infrastructure & Hardware
    How NVIDIA NVLink 6 Delivers Multi-Layer Resiliency for AI Factories
    NVIDIA details NVLink 6's multi-layer resiliency for AI factories
    Generative AI NVIDIA
    NVIDIA outlined how NVLink 6 builds resiliency across multiple layers for AI factories. Because every GPU in a training cluster moves in lockstep, one failure can stall the job; NVLink 6 adds redundancy and recovery from the link layer up to keep training running.
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  • NVIDIA Developer Blog · EN Infrastructure & Hardware
    How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin
    NVIDIA on Groq 3 LPX deterministic execution on Vera Rubin
    Generative AI Inference NVIDIA
    NVIDIA described how deterministic execution in Groq 3 LPX delivers power-efficient, high-interactivity inference on Vera Rubin. With power the defining constraint for AI factories, fixed execution timing cuts idle waits while preserving responsiveness.
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  • arXiv cs.AI (Artificial Intelligence) · EN Infrastructure & Hardware
    Learning-Guided Planning in Large Dynamic Action Spaces: Budgeted Tree Search for One-to-Many Mobile Charging
    Deep Learning Neural Network
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