LLM

Opinion

Resilient AI at Scale: Designing Cross-Region Disaster Recovery for Production LLM Systems
ByShivam Gupta July 1, 2026June 27, 2026

Recent large-scale disruptions, including regional cloud service degradation in the Middle East and widespread internet routing failures observed in late 2025, have reinforced a critical reality: failures are no longer confined to individual services or availability zones. Entire regions can become partially or fully unreachable with little warning. For AI platforms running Large Language Models,… … continue reading

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Standardizing AI at Scale: llm-d Joins the CNCF
ByDavid Rubinstein March 24, 2026

In a significant move toward solidifying the infrastructure for production-grade AI, the llm-d project is being contributed to the Cloud Native Computing Foundation (CNCF) as a Sandbox initiative. This commitment, spearheaded by a multi-vendor coalition including CoreWeave, IBM Red Hat, Google, and NVIDIA, aims to establish an open standard for distributed inference. By integrating llm-d into the cloud… … continue reading

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Groundcover launches observability solution for LLMs and agents
ByJenna Barron August 19, 2025

The eBPF-based observability provider groundcover today announced an observability solution specifically for monitoring LLMs and agents. It captures every interaction with LLM providers like OpenAI and Anthropic, including prompts, completions, latency, token usage, errors, and reasoning paths. According to groundcover, while LLMs can offer many benefits, they also introduce a lot of negatives: performance volatility,… … continue reading

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The crucial role of observability data lakes in LLM observability
ByKrishna Yadappanavar March 17, 2025March 17, 2025

The popularity of large language models (LLMs) has skyrocketed in recent years, fundamentally changing how businesses and individuals engage with technology. Models like ChatGPT are now widely integrated into various applications across industries, with many organizations exploring their use for customer service, content generation, code assistance, and more. However, this rapid adoption comes with its… … continue reading

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In-Depth | Latest News

Model choices: business use cases for SLMs and LLMs
ByTerrence Alsup August 15, 2024August 15, 2024

For many years, businesses and their data science teams valued accuracy above all else when it came to a model’s performance. Increasingly, however, other factors and trade-offs have come into play depending on the business context of models. From biases buried in training data to the costs associated with runtime and resourcing services underpinned by… … continue reading

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Surviving AI hype takes a human touch
ByBryce Maddock May 8, 2024May 3, 2024

We are in the midst of a massive AI hype cycle. As generative AI advancements have surpassed all expectations in the last few years, there have also been some AI rollouts within the tech industry that were not as effective as initially hoped. Deploying generative AI within organizations in an impactful way will require a… … continue reading

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Nokia Bell Labs’ AI solution uses text prompts to manage networks
ByJakub Lewkowicz November 2, 2023

Nokia has introduced the “Natural-Language Networking” AI solution that uses natural language processing and AI/ML models to interpret text or speech requests and then automatically allocate the correct network resources. These networks will understand the intentions of users and have the intelligence to act upon them autonomously, according to Nokia in a post. “Operators won’t… … continue reading

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