2026-09-15 17:00
Exploring model architectures: Dense vs. Mixture-of-Experts (MoE) 🤖 Dense models activate all parameters per token, ensuring consistency. In contrast, MoE models, like Nemotron 3.5 Lightning, only activate a subset for each token, enhancing capacity without using all parameters. ⚙️ The choice between these models impacts throughput, memory cost, and complexity, making it essential to consider deployment needs. Learn more about their performance and application scenarios! 📊 #MachineLearning...
Elizabeth Goodman
2026-09-15 16:55
NVIDIA's Vera Rubin platform is designed for power-efficient AI at scale, focusing on performance per watt. ⚡ Key features include the NVL72 core, which optimizes both large and small batch processing. Innovations like NVIDIA DSX MaxLPS software help manage power across racks, increasing GPU provisioning by 40% and boosting throughput by 35%. The Groq 3 LPX accelerator enhances low-latency performance through a deterministic execution model, allowing precise scheduling of data movements and...
Tanya Lenz
2026-09-15 16:55
🚀 For large-scale AI factories, maintaining continuous output is crucial for productivity. NVIDIA's NVLink 6 provides essential multi-layer resiliency, ensuring that workloads progress without interruption. This is vital as AI models grow and require robust network infrastructure to handle transient errors effectively. The Vera Rubin platform connects GPUs into a single compute unit, enhancing reliability and maximizing cluster productivity. Learn more about how NVLink 6 ensures optimal...
Elizabeth Goodman
2026-09-15 13:00
Kubernetes 1.36 addresses a critical issue for database backups. 🌐 Historically, restoring PostgreSQL clusters has faced challenges with volume consistency. When snapshots are taken of separate PersistentVolumeClaims (PVCs), they may not capture the same point in time, leading to potential restore failures. This inconsistency arises from the move to cloud-native environments, which lack the ‘consistency group’ feature found in traditional enterprise storage. As teams transition to Kubernetes,...
Shubham Pampattiwar
2026-09-14 19:41
🚀 The final installment of the IPsec series focuses on a fully quantum-safe tunnel using Cisco 8000 routers. It details the migration playbook and outlines the characteristics of a secure post-quantum tunnel. The article also highlights promising results for post-quantum certificates in TLS 1.3, addressing potential threats from quantum computers. 🔒🔗 #CyberSecurity #PostQuantum #TLS13 #Cisco8000 #IPsec
Julio Gomez
2026-09-14 16:39
🚀 Mixture of Experts (MoE) is transforming large-scale AI model training. Models like DeepSeek, Qwen, and Mixtral outperform dense models while reducing compute costs. 🔍 MoE uses conditional computation, activating only selected expert networks for efficiency. However, scaling MoE training poses challenges, such as token routing and expert dispatch. 📈 Recent advancements with JAX and NVIDIA Transformer Engine have improved MoE performance from 103 TFLOPS/GPU to 1,068 TFLOPS/GPU, highlighting...
Tanya Lenz
2026-09-14 13:01
🚀 Exciting progress in model quantization! The article discusses how the Llama 3.1 8B Instruct model was compressed from 14.9 GB to 8.0 GB using 8-bit integer (INT8) W8A8 quantization techniques, including SmoothQuant and GPTQ. This approach maintains accuracy while enhancing performance. #AI #Quantization #MachineLearning #DataScience #ModelOptimization
Sana Fayyaz
2026-09-11 12:00
AWS Lambda has enhanced its logging system to address security and operational challenges. The platform now uses eBPF and Rust to create a network flow log for every microVM, ensuring complete records of network activity for all tenants, even for brief workloads. This upgrade improves incident response and compliance while minimizing system overhead. The new system replaces an outdated architecture that struggled with Lambda's high request volumes. #AWS #Lambda #eBPF #CloudComputing #MicroVMs...
Prashant Kumar Singh
2026-09-10 16:55
🚀 Deploying a large language model is just the beginning. To ensure production readiness, teams must optimize for many concurrent users while maintaining responsiveness. 🔧 NVIDIA NIM provides a deployable microservice, offering a validated configuration and benchmarking capabilities. This enhances performance and ensures applications meet latency targets. 📊 A case study on Nemotron 3 Ultra shows NIM can deliver up to 2.5x higher throughput for agentic workloads, proving its effectiveness in...
Elizabeth Goodman
2026-09-09 20:31
🚀 Explore the benefits of Encode-Prefill-Decode (EPD) disaggregation for multimodal models! This technique optimizes inference by separating vision encoding from prefill and decode stages, significantly enhancing performance. With NVIDIA Dynamo, users can achieve up to 5x faster time to first token and 7x quicker end-to-end responses. However, EPD disaggregation is not always the best choice. It's ideal for image-heavy prompts and quantized mixture-of-experts models. #AI #MachineLearning...
Tanya Lenz
2026-09-09 16:45
ReSharper's recent launch of its out-of-process (OOP) architecture faced challenges with slower startup times on Windows. Initial profiling revealed that Microsoft Defender was scanning the ReSharper process longer than anticipated. This unexpected latency impacted user experience, prompting further investigation. Collaborating with Microsoft, JetBrains developed a tool for measuring Defender's impact, enhancing performance insights for its community. Learn more about their findings and...
Alexander Ulitin
2026-09-09 15:05
In part 3 of the series on local guardrail development, the focus is on deploying NeMo Guardrails on Red Hat OpenShift AI. The previous articles covered designing guardrail configurations and conducting manual testing. The second part emphasized rigorous testing against large-scale risk datasets. This series offers valuable insights for developers. 📊🔧 #NeMoGuardrails #RedHat #OpenShiftAI #TechDevelopment #DataSafety
Rob Geada
2026-09-09 13:00
Exciting advancements in real-time global illumination were showcased at ECCV 2026. A new generative method employs a single-step latent diffusion model for stable, high-quality lighting. ✨ This model eliminates the need for costly iterative processing and enhances temporal coherence for frame-by-frame generation. It effectively uses scene signals and lighting hints to improve rendering quality. 🖼️ Results show significant improvements in visual fidelity and stability compared to previous...
2026-09-09 10:39
JetBrains IDEs have evolved their support for WSL over the years, adapting to various architectures and entry points. Starting with the 2026.2 release, a unified entry point is introduced. In IntelliJ IDEA, WebStorm, and PhpStorm, projects in WSL will run in Native mode, ensuring smoother integration while maintaining performance. The article outlines the transition from earlier implementations, such as 9P protocol and Remote Development, to the current Native mode, highlighting improvements...
Kristina Pchelintseva
2026-09-09 03:32
📊 A recent CSA Research survey highlights that 76% of consumers prefer to buy in their native language, and 40% won’t purchase in another. This preference extends to how products communicate verbally. Explore how to personalize text-to-speech voices using Kubeflow Trainer on Red Hat OpenShift AI. #TextToSpeech #LanguagePreference #AI #RedHat #CustomerExperience
Dmytro Hryshchenko, Abhijeet Dhumal
2026-09-08 17:48
Exploring the ML-DSA-65 certificate, this article highlights its significant size compared to RSA-2048. Part 10 focuses on building the PKI externally and importing it into Cisco routers using PKCS#12. It also discusses the transition from PSK to ML-DSA signatures and analyzes the costs of post-quantum authentication. 🔐📡💻 #Cybersecurity #Cisco #PostQuantum #MLDSA #Networking
Julio Gomez
2026-09-08 14:20
Large language models (LLMs) face challenges with autoregressive decoding, as they rely heavily on memory bandwidth. Each token requires a full forward pass over billions of parameters, leading to inefficiencies. The article discusses the MTP training objective, which helps models like DeepSeek and Qwen predict multiple future tokens, enhancing data efficiency and quality. For more insights, check out the full article! 📈💡 #LLM #DataEfficiency #MachineLearning #FastMTP #RedHatDeveloper
Rahul Tuli
2026-09-08 12:34
Debugging Spring MVC can sometimes lead to unexpected HTTP 403 errors. 🛠️ When encountering these responses, it’s crucial to identify the required roles for the endpoint. IntelliJ IDEA offers inlays that simplify this process by displaying role-based requirements without modifying the SecurityConfig. You can also choose to unlock the endpoint temporarily for your debugging session. However, be cautious, as this action affects all requests to that URI, not just those from the IDE. 🔒...
Andrey Belyaev
2026-09-07 07:01
Large language models like Llama 3.1 8B require significant GPU memory, around 15 GB when using Bfloat16 (BF16) precision. This includes storage for 8 billion parameters and additional memory for key-value caches and activations during inference. W8A8 INT8 quantization offers a solution by reducing model size while maintaining performance and accuracy. 🔍💡📉 #MachineLearning #AI #ModelOptimization #Quantization
Sana Fayyaz
2026-09-07 03:00
🔍 Red Hat Advanced Cluster Security for Kubernetes offers an image scanning API crucial for CI/CD pipelines assessing vulnerabilities. 🚫 However, upgrades and restarts can cause downtime, disrupting essential build processes. This article outlines a reference architecture that resolves this issue by utilizing two Central service instances along with a client-side failover mechanism. #Kubernetes #RedHat #DevOps #Cybersecurity #HAScanning
Johannes Malsam
2026-09-05 15:00
Building trust in agentic retrieval-augmented generation (RAG) is crucial for effective information retrieval. RAG allows systems to refine user queries and choose diverse data sources. This flexibility can uncover evidence that standard searches miss, but it also demands a clear record of decisions made during the process. 📊🔍 Transparency is essential. Users need to see what was searched, what was accepted, and what could not be verified. This helps build trust in the system's answers. #RAG...
Jeremy Daly
2026-09-04 14:00
Evaluating AI agents is essential to ensure consistent performance. A team tests agents with representative questions, recording their responses to approve changes. However, updates can lead to unforeseen issues that may only surface through user feedback. To maintain quality, a repeatable evaluation system is crucial. This system should define correct behavior, separate results from processes, and focus on real user tasks. #AIEvaluation #ProductQuality #TechDevelopment #AI #UserFeedback 🤖🛠️📊
Jeremy Daly
2026-09-04 07:01
Unlock the power of automation with Ansible! 🔒✨ The article discusses how to integrate AI-assisted workflows into firewall management. It highlights the ability to manage access requests, such as allowing app-client-01 to connect to the database on port 5432. Explore how Ansible can streamline these processes effectively. #Ansible #Automation #Cybersecurity #AI #FirewallManagement
Michal Zdyb
2026-09-03 18:30
🚀 New advancements in GPU inference! An article details how the cold start time for GPU models has been reduced from 8 minutes to under 1 minute. This improvement involves identifying and addressing six bottlenecks during the startup process. Key findings include that for a 64 GB model, 65% of time is spent recompiling CUDA kernels, while for a 203 GB model, 92% of time is spent on downloading weights. Many of these issues can be fixed with configuration changes. Optimizations can...
Sajjan Gundapuneedi
2026-09-03 18:30
Understanding production token optimization is crucial for scaling enterprise AI applications. Many teams mistake rising API bills as the core issue, but it’s more about efficient token management. Token optimization involves tackling distributed systems and hardware utilization challenges. The article discusses how systems like Concierge and Pathfinder faced bottlenecks due to autoregressive costs. It highlights the importance of recognizing that a token is not merely a word, with providers...
Boris Chabeda
2026-09-03 17:56
🚀 Amazon has introduced P-EAGLE, a new speculative decoding algorithm designed to enhance LLM inference. This innovation builds on EAGLE-3 by incorporating parallel drafting, which aims to improve efficiency in processing. Discover how P-EAGLE is set to advance speculative decoding technology in the latest update. #TechInnovation #MachineLearning #Amazon #SpeculativeDecoding #AI
Helen Zhao, Megan Flynn, Dipika Sikka
2026-09-03 17:34
PhiloLabs conducted an experiment using AI coding agents to build a 3D version of San Francisco’s Union Square in just two hours. 🏙️💻 The project utilized real-world data and resulted in a detailed scene with buildings, storefronts, and moving pedestrians. The total cost for the API calls was approximately $33. To identify visual flaws, the agents created 147 comparison sheets, allowing for a detailed review of the model. They produced nine reports to address issues like proportions and...
Amanda Caswell
2026-09-03 03:01
🚀 Migrating to Red Hat OpenShift Virtualization can modernize your infrastructure without disrupting existing network settings. However, traditional systems often face challenges in maintaining connectivity for imported VMs and ensuring multi-tenant isolation. The article highlights solutions using BGP and EVPN to streamline these processes. #RedHat #OpenShift #Virtualization #Networking #BGP #EVPN
Miguel Duarte de Mora Barroso, Valentino Uberti
2026-09-02 16:04
🚀 In the latest installment of the AI model co-design series, the focus is on accelerating LLM inference using speculative decoding. This technique enhances efficiency by predicting multiple tokens in one go while ensuring accuracy. Five guidelines are provided for selecting draft length and mechanisms to optimize performance. For deeper insights into model design choices and their impact on throughput, check out previous posts in the series. #AI #MachineLearning #LLM #SpeculativeDecoding...
Tanya Lenz
2026-09-02 15:29
🔍 Vercel has developed a new public prompt file, design.md, after running over 200 agent tests. This file aims to help agents create web pages that align with Vercel’s brand, even without internal code access. 🔧 Their testing revealed that encoding human judgment in agent guidance can reduce recurring failures, but it's not a complete solution. For example, in a six-page test, failures decreased by 57% with design.md loaded. 📊 Vercel's initiative highlights the challenge of transferring...
Meredith Shubel
2026-09-01 20:49
🌐 Discover how Cisco is advancing key exchange methods in routers! The article details the process of transitioning from classical key exchange to PPK and finally to the hybrid ML-KEM-768 on Cisco 8000 routers using IOS XE 26.2. It highlights a phased rollout strategy across hub and spokes, demonstrating zero outages during the implementation. #Cisco #KeyExchange #CyberSecurity #Networking #TechUpdate
Julio Gomez
2026-09-01 17:00
AI is transforming cybersecurity with adaptive agentic systems that enhance coordination and efficiency. Security teams are integrating these systems to identify gaps in defenses, but many still rely on predefined workflows. Continuous offense-defense testing is essential for improving coverage and validating detections against real-world activities. NVIDIA and CrowdStrike have developed an advanced system using NVIDIA Nemotron models, achieving better accuracy at a lower cost. This approach...
Michelle Horton
2026-09-01 14:00
In the evolving landscape of application development, the role of agents in creating and maintaining state is changing. 🌐 Traditionally, applications needed a place to store their state, but now, the focus is on how agents build, deploy, and maintain this state efficiently. As seen with Kimi from Moonshot AI, agents not only develop applications but also keep them running over time. 🔧 This raises questions about the economics of persistence, especially when dealing with millions of...
Max Liu
2026-09-01 07:01
Discover how to enhance your streaming retrieval-augmented generation (RAG) pipeline with OpenShift AI. The previous article outlined a single Ray Data script that handles parsing, chunking, embedding, and writing to Milvus. However, this monolithic approach has a drawback: if a parsing error occurs, you must restart the entire process. Learn more about optimizing your RAG workflow! 🚀💻 #OpenShiftAI #DataPipeline #RAG #TechInnovation #RedHatDeveloper
Ana Biazetti, Saad Zaher
2026-09-01 03:01
Discover the latest in Red Hat OpenShift scaling solutions! This article explores the MachineSet Autoscaler with KEDA, a metrics-driven method for scaling individual MachineSets based on external or custom signals. Previously, we discussed the Cluster Autoscaler, a built-in, Kubernetes-native approach. Learn how these options can enhance your compute infrastructure! 💻📈 #RedHat #OpenShift #KEDA #Autoscaling #CloudComputing
Ramon Gordillo Gutierrez, Jose Ortiz Padilla
2026-08-31 20:04
Connecting AI agents to tools can be complex, especially for organizations with numerous resources. Agentic Resource Discovery (ARD) aims to simplify this by allowing agents to search registries dynamically, rather than relying on pre-defined connections. This initiative, highlighted by AWS, is a collaboration between experts from Google, Microsoft, and others. While the Model Context Protocol (MCP) facilitates connections, it assumes prior knowledge of server locations, which can hinder...
Amanda Caswell
2026-08-31 16:00
🚗✨ Adapting perception stacks for different vehicle types is crucial in autonomous driving. The NVIDIA Omniverse NuRec enables developers to use existing real-world data to prepare software for vehicles that may not yet exist. By reconstructing real-world drives, NuRec allows for rendering new camera views tailored to specific vehicle configurations. This process helps identify potential weak spots and gaps in data collection. Learn how to follow four key steps for effective carline...
Michelle Horton
2026-08-31 15:00
AI coding agents incur costs before writing code due to token usage on source files, ticket descriptions, build logs, and more. While teams often manage costs through model choice and prompt length, the output format from development tools also impacts token expenses. Using formats like Token-Oriented Object Notation (TOON) can reduce unnecessary repetition in data representation, leading to cost savings for teams. #AICoding #TokenCosts #DevelopmentTools #TechInsights #SoftwareEngineering 💻📊🔧
Prasenjit A. Sarkar
2026-08-31 13:00
📢 The article discusses the importance of a structured development lifecycle for coding agents. It highlights how skills, configurations, and rules files shape the output of these agents. However, many teams neglect testing, leading to issues when updates occur. Introducing the Context Development Lifecycle (CDLC) with four phases: Generate, Evaluate, Distribute, and Observe. This framework encourages thorough evaluation and testing, ensuring quality and effectiveness. Don't overlook the...
Ankit Jain
2026-08-31 10:44
🔍 In a recent evaluation of LLMs for coding, two models, Claude Opus 4.7 and Gemini 3.5 Flash, solved the same number of tasks but differed significantly in their approaches. While Opus required more steps and was costlier per run, Gemini was more efficient. This highlights the importance of evaluating not just the outcome but also the execution process. An advanced evaluation pipeline was created to analyze functional outcomes and execution efficiency, ensuring a comprehensive understanding...
Dmitry Savelev