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A critical look at the UK Government's AI opportunities action plan

The UK government’s recently announced AI Opportunities Action Plan marks an ambitious step forward in harnessing artificial intelligence to drive economic growth and societal progress. As the CEO of Civo, a UK-founded company committed to reimagining the cloud with sustainability, innovation, and sovereignty at its core, I welcome this bold vision.

Introducing the Time Series Buying Guide for IIoT

All machinery and equipment, including their controls and sensors, tell a story through the data they collect. This data, or Industrial Internet of Things (IIoT) data, provides a detailed narrative about the machines, offering actionable insights to improve operations. IIoT data empowers businesses to optimize and enhance industrial processes by detailing operational status, performance metrics, usage patterns, health diagnostics, and environmental conditions.

Monitoring a Low-Power Wireless Network Based on Smart Mesh IP

Monitoring IoT applications is essential due to their operation in dynamic and challenging environments, which makes them susceptible to various operational and connectivity issues. Application Performance Monitoring (APM) is the key to identifying and resolving these issues in real time, ensuring uninterrupted data flow and functionality. Moreover, the insights gained from APM can optimize device performance, ensure reliability, and reduce operational costs.

Reimagining Log Management Tools and Software: The Impact of AI and GenAI

Today’s distributed, cloud-native systems generate logs at a high rate, making it increasingly difficult to derive actionable insights. AI and Generative AI (GenAI) technologies—particularly large language models (LLMs)— are transforming log management tools by enabling teams to sift through this data, identify anomalies, and deliver real-time, context-rich intelligence to streamline troubleshooting.

Micro Lesson: Introduction to Sumo Logic Mo Copilot

The video introduces Sumo Logic's Mo Copilot, an AI-powered assistant that simplifies complex query creation using natural language, making it accessible for users of all skill levels. Mo Copilot enhances productivity by providing AI-driven insights and recommendations, allowing teams to detect and resolve incidents more efficiently. It consolidates logs into a unified view, improving collaboration and decision-making. Overall, Mo Copilot transforms the way security and development teams work with data.

Using AI for Troubleshooting: OpenAI vs DeepSeek

AI is now a go-to tool for everything from writing to coding. Modern LLMs are so powerful that, with the right prompt and a few adjustments, they can handle tasks almost effortlessly. At Coroot, we’ve been experimenting with AI for observability. Our goal is to make it useful in the final stage of troubleshooting—when we’ve already identified which service is causing issues, like Postgres, but finding the exact root cause is still tricky due to the many possible scenarios.

GenAI: A New Paradigm for Problem-Solving with Undefined Inputs

Traditional programming is built around well-defined inputs and deterministic logic. Developers write functions that take structured inputs, apply a predefined set of operations, and return a structured output. This model works well when the input space is predictable, but it struggles with problems where inputs are ambiguous, unstructured, or constantly evolving.

Delete Tweets to Improve Your Twitter Analytics: How a Clean Slate Can Boost Engagement

Social media analytics help businesses get to know their audience, improve messaging, identify influencers and boost engagement. Specifically, Twitter (X) analytics lets you follow key metrics such as tweet impressions, profile visits, mentions, follower growth and tweet engagement over time. However, old tweets that are no longer relevant or underperforming can negatively affect your Twitter analytics and hinder you from getting a clear picture of your current content performance.

Generative AI QE: Insights from testing Sumo Logic Mo Copilot

Generative AI is transforming industries by automating tasks and delivering AI tools, such as AI assistant Sumo Logic Mo Copilot, to enhance operational efficiency. But, these advancements also challenge traditional quality engineering (QE) methodologies. Unlike conventional software testing, AI models produce dynamic, context-sensitive outputs, requiring a new approach to validation and testing. At Sumo Logic, we faced similar challenges while testing Mo Copilot.