As large language models scale to longer contexts, loading the growing KV cache during attention computation becomes a critical bottleneck. Previous work has sh...
One key challenge in designing resilient large-scale wireless ad hoc networks is to understand how random node failures affect fundamental network performance. ...
LLM inference is still evaluated mainly as a model or software problem: accuracy, latency, throughput, and hardware utilization. This is incomplete. At deployme...
Graph processing systems are essential for analyzing large-scale data with complex relationships, yet most existing frameworks rely on statically provisioned cl...
On-disk graph-based vector search (GVS) has become the dominant approach for serving large-scale vector databases at high recall, but prior systems struggle to ...
We introduce the State Twin: a typed, in-memory, replayable replica of an on-chain automated market maker (AMM) pool that serves as a substrate for agentic reas...
Overview Many educational resources exist outside of IBM Vault to help users get the most value out of their secrets‑management experience. From developer docs...
Abstract This article explores the integration of AI technologies into Agile frameworks, focusing on large-scale applications such as the Scaled Agile Framewor...
The RISC-V Vector Extension~(RVV) is a cornerstone for supporting compute throughout in scientific and machine learning workloads. Yet compiler support and perf...
Mixture-of-Experts (MoE) serving relies on wide expert parallelism (EP) to aggregate the memory capacity and bandwidth of many GPUs within one inference instanc...
Compound LLM training workloads-such as knowledge distillation and multimodal LLM (MLLM) training-are gaining prominence. These typically comprise heterogeneous...
Traditional federated learning (FL) relies on a central aggregator server, which can create performance bottlenecks and privacy risks. Decentralized mix-and-for...
Edge computing faces unprecedented resource orchestration challenges from multi-dimensional heterogeneity across device architectures, diverse task requirements...
Dubai, UAE, May 11 th 2026, CyberNewswire Dubai‑founded OTT Cybersecurity LLC also unveils the Agent Trust Protocol ATP, the first open cryptographic standard f...
Cloud database systems, particularly their middleware and query execution layers, use sorting as a core operation in query processing, indexing and join executi...
Byzantine Reliable Broadcast (BRB) is a fundamental primitive in distributed computing and cryptographic systems. Reducing the communication complexity of BRB p...
Open source software is a foundational pillar of modern technology. From operating systems and databases to cloud infrastructure and developer tooling, it is em...
If you’ve spent any time working with AI coding agents, you know the routine. You describe what you want. The agent generates code that looks right. You run it....
Overview DevOps interviews often focus on real‑world problem solving rather than textbook definitions. To help candidates prepare, a GitHub repository — devops...
'Advancing Collective Defense with Project Glasswing Category: Security
Each year during Red Hat Summit, we recognize Red Hat Certified Professionals who make a difference in their organizations by demonstrating enthusiasm, commitme...
As AI compute and storage have evolved to become abstracted, multi‑tenant, and automated, AI infrastructure now demands accelerated networking that delivers the...
It’s no secret – the tech industry is rapidly adopting agentic software development to convert business processes into fully autonomous, agentic workflows. Whil...
Reactive support models can be a liability when a single misconfiguration can stall a global rollout or an essential production upgrade. To address this, Red Ha...
At Red Hat, we’ve always known that “open” is a team sport. While our technology provides the foundation, our partners act as the ultimate force multipliers—bui...
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Integración tango‑integration‑interapis Tolola.tech En tolola.tech terminamos recientemente el proyecto tango‑integration‑interapis: una integración entre el s...
A small internal tool was built over a weekend. An engineer used an AI coding assistant to generate most of the backend. A simple interface was added, a few API...
Security has long been the last item on the checklist. Code gets written, reviewed, merged—and then, somewhere down the line, a security team takes a look. That...
Stencil computations are a fundamental kernel in scientific computing, critical for simulations in domains such as fluid dynamics and climate modeling. However,...
Modern large language model workloads put increasing demands on parallel compute capability and on-chip memory capacity, while also stressing fine-grained data ...
Large Language Models (LLMs) continue to demonstrate superior performance with increasing scale, yet training models with billions to trillions of parameters re...
Summary Akamai has mitigated a local privilege escalation vulnerability in the Akamai Guardicore Platform Agent for macOS and Linux. Fixed versions have been a...
Overview The recent release of A2UI Agent-to-User Interface by Google introduces a standardized, open-source protocol for how AI agents render user interfaces....
As investment in AI-focused accelerators grows and their deployment in supercomputing facilities expands, understanding whether these architectures can efficien...
A previously undocumented Linux implant codenamed Quasar Linux RAT QLNX is targeting developers' systems to establish a silent foothold and facilitate a broad r...
Long-context training of large language models (LLMs) is commonly distributed with Context Parallelism (CP) and Head Parallelism (HP), but existing training sys...
AI-RAN consolidates AI services and Radio Access Network (RAN) functions onto a unified, GPU-accelerated infrastructure at the network edge. However, compute sh...
Large Language Models (LLMs) are transforming recommendation from ranking into a generative task, but industrial deployment remains limited by the high latency ...
2026-05-07 3 min read Announcement This afternoon we sent the following email to our global team. One of our core values at Cloudflare is transparency, and we b...
Let’s unpack the uncomfortable truth: most Retrieval‑Augmented Generation RAG systems in production today are fragile, expensive, and deceptively incomplete....
The default reaction to vibe coding has been alarm — a default assumption that letting AI write large chunks of an application is going to flood production with...
Evaluative claims about LLM infrastructure -- ``workload X is fastest on hardware Y with software Z'' -- depend on a complex configuration space spanning hardwa...
Agentic reinforcement learning (RL) has emerged as a key driver for improving the multi-step reasoning and tool-use capabilities of LLMs. However, its efficienc...
Spatio-temporal Bayesian inference drives environmental and health sciences using latent Gaussian models. Integrated Nested Laplace Approximations (INLA) enable...
Hybrid parallelism underpins large-scale LLM training across tens of thousands of GPUs. At such scale, hardware failures on individual devices lead to performan...
We present TACO, a toolsuite for the development and automatic verification of fault-tolerant and threshold-based distributed algorithms. Our toolsuite implemen...
