Infrastructure & Hardware

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Showing 1–30 of 222
  • ITmedia AI+ · JA Infrastructure & Hardware
    キオクシア「設備投資を急がねば……」 2027年分は完売、メモリ供給追い付くか
    Kioxia says 2027 capacity is sold out, will build a new fab
    Memory chipmaker Kioxia disclosed that its entire 2027 production capacity is sold out. To meet booming AI-driven memory demand, it will spend just under 500 billion yen a year on a new plant. The question is whether memory supply can catch up with demand.
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  • Data Center Dynamics · EN Infrastructure & Hardware
    What could 1,000x more reliable quantum computation unlock?
    What 1,000x more reliable quantum computing could unlock
    An opinion piece in DCD asking what becomes possible if quantum computation becomes 1,000x more reliable. It argues readers should start treating quantum computing as one element of the broader data center ecosystem. (Based on the excerpt only; detailed arguments not verified.)
    Read original (Data Center Dynamics) ↗
  • Data Center Dynamics · EN Infrastructure & Hardware
    Beyond the grid: the maintenance challenges putting the data center boom at risk
    Maintenance gaps that could put the data center boom at risk
    An opinion piece in DCD arguing that, beyond grid constraints, building maintenance challenges could put the data center boom at risk, and that maintenance needs more attention. (Based on the excerpt only; details not verified.)
    Read original (Data Center Dynamics) ↗
  • Data Center Dynamics · EN Infrastructure & Hardware
    Sponsored: One security strategy. Four different data center realities.
    Sponsored: data center security should differ by site
    This sponsored piece argues that the strongest data center security strategies do not deploy identical controls everywhere. It makes the case for matching security controls to each facility's different reality.
    Read original (Data Center Dynamics) ↗
  • The Register (Data Centre) · EN Infrastructure & Hardware
    Google's AI satellite sends a very expensive haiku to Earth
    Google's orbital AI datacenter prototype beams a costly haiku to Earth
    Google Machine Learning
    An experimental orbital datacenter prototype from Google used its TPU to produce poetry and sent a haiku back to Earth. The Register calls it a very expensive haiku.
    Read original (The Register (Data Centre)) ↗
  • Data Center Dynamics · EN Infrastructure & Hardware
    Europe’s AI ambitions are hitting a power bottleneck
    Europe's AI ambitions hit a power bottleneck
    Data center demand is surging, but outdated grid infrastructure is stopping Europe from making full use of renewable energy. The article says this is creating a power bottleneck for Europe's AI ambitions.
    Read original (Data Center Dynamics) ↗
  • Hacker News (Front Page) · EN Infrastructure & Hardware
    Serbia just elected the world's brainiest parliament
    Science: Serbia's new parliament billed as world's brainiest
    Reinforcement Learning
    A Science article calling Serbia's newly elected parliament the world's brainiest hit the Hacker News front page. It seems to focus on lawmakers' credentials, but no excerpt was available, so figures are unconfirmed.
    Read original (Hacker News (Front Page)) ↗
  • The Register (Data Centre) · EN Infrastructure & Hardware
    Backbone of a beast – charting Nvidia's rise to networking titan
    How Nvidia's Mellanox bet made it a networking titan
    NVIDIA Reinforcement Learning
    Nvidia's $6.9B bet on Mellanox made it bigger than Cisco, and helped make it the world's most valuable company. The Register charts the rise of its networking business.
    Read original (The Register (Data Centre)) ↗
  • Simon Willison's Weblog · EN Infrastructure & Hardware
    dbreunig/nesformer
    Emulating an NES 6502 CPU inside Qwen3.5-4B's weights
    Neural Network
    Inspired by Divyansh Agrawal, Drew Breunig baked a working Nintendo Entertainment System 6502 CPU emulator into the weights of Qwen3.5-4B, so NES ROMs such as Super Mario Bros run inside the model, very slowly. In a Hacker News comment he shared the Opus 5.5 prompts used to build it.
    Read original (Simon Willison's Weblog) ↗
  • NVIDIA Developer Blog · EN Inference & Efficiency
    Build a Validated Kubernetes Runtime for NVIDIA Dynamo
    NVIDIA details how to build a validated Kubernetes runtime for Dynamo
    Generative AI Inference Machine Learning NVIDIA Reinforcement Learning from Human Feedback (RLHF)
    Teams building AI applications need a repeatable path from a model configuration to a working inference endpoint. NVIDIA walks through building a validated Kubernetes runtime for Dynamo, its distributed inference framework, aiming to standardize how a chosen model setup becomes a running inference service and to cut operational effort.
    Read original (NVIDIA Developer Blog) ↗
  • NVIDIA Developer Blog · EN Inference & Efficiency
    Run AI Models for Edge Application Development with Just a Few Commands
    NVIDIA shows how to run AI models for edge app development in a few commands
    AI Agents Generative AI Inference Machine Learning NVIDIA
    An NVIDIA developer blog post explains how to run AI models for edge application development with just a few commands. It frames the topic around AI expanding beyond the data center, as developers build agents that act at the edge, such as monitoring driver attention and cabin conditions.
    Read original (NVIDIA Developer Blog) ↗
  • arXiv cs.CL (Computation and Language) · EN Inference & Efficiency
    Flide: Accelerating Decision Inference with Exact State Forking
    Inference Meta Reinforcement Learning Software Engineering
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Gradient Descent on Two ReLU Neurons: Global Landscape and Bifurcation Dynamics
    Deep Learning Neural Network
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    SATFRONT: Detecting Atmospheric Fronts with Satellite Data using Machine Learning
    Deep Learning Machine Learning Neural Network
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • Data Center Dynamics · EN Infrastructure & Hardware
    Data center mooted in Glasgow by Scottish automotive firm
    Scottish automotive firm floats Glasgow data center plan
    A Scottish automotive company is sounding out the local council about building a data center near Cowlairs Park in Glasgow.
    Read original (Data Center Dynamics) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    The Knowledge Layer Model (KLM): Evidence-Visible AI Output, Routing Diagnostics, and Negative Results
    Deep Learning Inference Software Engineering
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    GhostPrefix: Synchronization-Free Universal Prefix Attacks for ASR Manipulation
    Retrieval-Augmented Generation (RAG) Speech Processing
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN Training & Fine-tuning
    When Does Jacobian Fine-Tuning Stabilize Neural PDE Emulators?
    Fine-tuning Neural Network
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    TurnTurk-GPT: Text-Based Turn-Taking Prediction for Turkish
    Fine-tuning GPT Speech Processing
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Agents & Tool Use
    SecPO: Principled Adversarial Training for Prompt Injection Security
    AI Agents Meta Reinforcement Learning from Human Feedback (RLHF) Speech Processing
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    DAMI: Dual-Axis Memory Initialization for Enhanced Long-Context Retrieval in Gated Linear Attention
    Deep Learning Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • Data Center Dynamics · EN Infrastructure & Hardware
    Modular data center provider DXN loses neocloud customer contract
    Modular data center firm DXN loses neocloud customer contract
    Modular data center provider DXN lost a neocloud customer after the customer cancelled the deal following a shift in its business. The company was still paid for work already completed.
    Read original (Data Center Dynamics) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Infrastructure & Hardware
    Prune Gradually, Adapt Sparsely: Efficient Pruning of Large Language Models at Extreme Sparsity
    Inference Llama Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    When Is a Game a Markov Decision Process? Correspondences Between Game Theory and Reinforcement Learning
    Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    Optimizing Stochastic Policy Geometry for Few-Step Flow Reinforcement Learning
    Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • Data Center Dynamics · EN Infrastructure & Hardware
    DayOne signs MoU with Sembcorp to integrate power and energy solutions across APAC data centers
    DayOne signs MoU with Sembcorp on APAC data center power
    DayOne signed an MoU with Sembcorp to integrate power and energy solutions across its APAC data centers, as part of the company's Bring Your Own Power initiative.
    Read original (Data Center Dynamics) ↗
  • Data Center Dynamics · EN Infrastructure & Hardware
    Sponsored: The new age of contractual risk allocation in data center development
    Sponsored: new age of contractual risk allocation in DC development
    A sponsored piece on how hyperscale and AI-driven demand is reshaping contractual liabilities across the data center development stack.
    Read original (Data Center Dynamics) ↗
  • NVIDIA Developer Blog · EN Agents & Tool Use
    Build Specialized Agents on a Stack You Control with NVIDIA NemoClaw
    NVIDIA: build specialized agents on a stack you control with NemoClaw
    AI Agents Deep Learning Generative AI NVIDIA
    An NVIDIA developer blog post says an autonomous agent needs a model, a harness, and domain-specific tools. To deploy agents more securely, developers need a runtime that enforces policy, and the post presents NemoClaw as a way to build on a stack you control.
    Read original (NVIDIA Developer Blog) ↗
  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    Binary Sparse Codes: Where are we on Energy Efficient Representations?
    Deep Learning Meta
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    ReX-GG: a LLM Ensemble Pipeline for Relation-extraction and Graph Generation
    Machine Learning Neural Network Retrieval-Augmented Generation (RAG) Software Engineering
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗