AI Infrastructure news and analysis on Web Pulse: 17533 curated articles tracking the latest AI Infrastructure developments, tools, and research, updated continuously from vetted sources.
Palantir's forward deployed engineering (FDE) methodology, which embeds engineers directly with clients, is setting a standard for AI deployment success. Other companies are racing to adopt similar strategies, but replic…
Mini PCs with unified memory architectures, such as those using AMD's Strix Halo chip, can run 70-billion-parameter language models that exceed the VRAM capacity of discrete GPUs like the RTX 5090, but at significantly l…
NVIDIA is introducing a revenue-sharing and credit-support model for specialized AI cloud providers, financing GPU deployments to bypass hyperscaler custom silicon and secure distribution for inference workloads. The str…
ASUS gave a tour of its thermal testing lab in Taiwan, where it tests AI servers in environmental chambers that simulate years of thermal stress in compressed timeframes. The lab includes a walk-in chamber for full-rack …
The U.S. Department of Commerce loosened export controls on the United Arab Emirates, making it easier to export military items, AI chips, and commercial satellites. The UAE government and approved companies, including G…
Investors are selling off long-dated bonds tied to AI infrastructure as Big Tech's $159 billion borrowing binge in 2025-2026 tests market appetite. The selloff reflects growing selectivity about duration risk, with conce…
Japan-backed Rapidus aims to mass-produce 2 nm chips by 2027 at lower prices than TSMC, but TSMC's dominant market share, customer relationships, and manufacturing scale make it difficult for challengers to gain ground. …
Researchers have developed a new compression algorithm for decentralized AI training that achieves up to 99% compression without degrading convergence, enabling billion-parameter models to be trained on low-end GPUs with…
Microsoft has launched hosted agents for its Azure AI Foundry platform to general availability, offering a managed, framework-agnostic runtime for deploying AI agents across more than 20 Azure regions. The service suppor…
Elon Musk admitted on X that he was 'clearly wrong' about Anthropic, now calling the AI company 'obviously currently the leader in AI' and praising its Mythos/Fable model. The reversal came amid Anthropic's compute deal …
Goldman Sachs raised AMD's price target to $640, citing surging demand for AI chips driven by agentic AI systems. AMD stock has gained over 100% year-to-date as analysts project sold-out capacity and expanding market sha…
A developer released Agent OS, an open-source local-first AI project operating system that provides a harness around coding models. The system separates responsibilities between a Main Agent and a Coding Agent, with sand…
Databricks announced the Public Preview of Feature Views, a managed framework for building, serving, and governing ML features within its platform. The feature allows data scientists to define feature logic once and auto…
The Agentic AI Foundation, part of the Linux Foundation, announced the Model Context Protocol Associate (MCPA), the first official certification for the Model Context Protocol (MCP). The vendor-neutral credential tests u…
NVIDIA published a technical blog post explaining how kernel fusion in CUDA can optimize GPU code by combining multiple operations into a single kernel, reducing memory traffic and launch overhead. The post demonstrates …
AI companies' massive demand for RAM and storage components has drained consumer supply, causing shortages and price hikes across devices from Apple and Microsoft to Nintendo and Sony. The trend, dubbed 'RAMageddon,' thr…
The US Commerce Department reclassified the United Arab Emirates from export control groups D:3 and D:4 to Group A:5, allowing license-free access to advanced AI chips from Nvidia and AMD. The move, tied to the UAE's sta…
AI companies including Meta, SpaceX, and OpenAI are racing to release cheaper, faster models, intensifying competition in the AI market. This comes as memory chip makers like SK Hynix go public and raise billions to meet…
LTT Labs published a technical article explaining that large language models require significant VRAM beyond just storing weights, emphasizing the need for larger memory capacity for inference and quantization.
A new guide for AI model developers explains how hardware-aware design choices in large language models can improve throughput and interactivity without sacrificing accuracy, focusing on the trade-offs between model widt…