How AIOps transforms cloud operations for smart manufacturing and connected vehicles

The professional monitoring industry is undergoing a fundamental transformation. Traditional signal-based workflows are challenged by the growing volume of video data and the demand for real-time verification. Parks Associates’ latest white paper, “How to Scale Live Video Monitoring? Empowering NextGen Operators with Cloud Video AI,” explores how cloud architecture and AI are reshaping monitoring operations, improving accuracy, and supporting scalability. As industry professionals prepare for TMA OPSTech 2025, this research provides critical context for understanding the technologies and strategies shaping the future of professional monitoring. Read the research Written in partnership with 3dEYE Inc.: https://lnkd.in/dhNWenzJ #VideoMonitoring #AI #CloudSecurity #SmartMonitoring #TMAOPSTech2025 #3dEYE

Hitachi has expanded its alliance with Google Cloud to develop AI agents leveraging Gemini, empowering frontline workers across sectors like energy and manufacturing with no-code tools for operational transformation. The new “Agent Factory” accelerates AI agent development using Hitachi’s domain knowledge and Google Cloud’s AI technology. GlobalLogic, a Hitachi company, is driving deployment and adoption, promoting democratization and sustainability in social infrastructure. https://lnkd.in/e_9tTv4c #Hitachi #AI #GCP

The global AI data center market is accelerating, driven by generative AI, cloud expansion, and rising compute demand. Our latest infographic highlights key growth drivers, technical challenges, and global capacity distribution from power efficiency to emerging regional hubs. Riding this wave of AI-driven growth, Bitdeer AI is expanding globally with next-generation AI data centers that fuel the future of intelligent computing. Take a look at the full chart below💡. #AIDatacenter #AIInfra #AICloud

AI Observability isn’t a new silo — it’s an evolution. It extends your enterprise observability into the world of AI, covering three essential layers: 1. Infrastructure Observability — ensuring uptime, utilization, and cloud service health. 2. LLM Observability — measuring latency, throughput, token cost, and error rates. 3. Agent Observability — the next frontier, where APM meets AI. Every AI Agent is essentially an application powered by an LLM, which means: Agent Observability must be an extension of APM (Application Performance Monitoring). Just as APM tracks system performance and traces, Agent Observability tracks reasoning quality, workflow tracing, and semantic accuracy — ensuring reliability, trust, and accountability in AI-powered systems. When you unify metrics, traces, and logs across these three layers, you move from system uptime to AI outcome assurance. #AIObservability #AgenticAI #GenerativeAI #AgentObservability #AIGovernance #AIOpsX

Nokia's Q3 profit jumps past expectations driven by AI and cloud services. Shares hit 3-year high as data center strategy pays off, with CEO predicting AI "supercycle" ahead. https://lnkd.in/d3PgjfwM

Source: https://lnkd.in/dWbPVr8b 🚀 AI’s next big leap isn’t in the cloud—it’s at the edge! 🔧 Industrial use cases demand agentic architectures to cut latency and boost throughput. Think XR glasses analyzing defects or voice-activated maintenance via SLMs. ⚙️ But LLMs? They’re still a work-in-progress—need guardrails, testing, and deterministic outputs. 💡 Key takeaway: Edge AI isn’t just about power—it’s about trust. Engineers must balance innovation with security, data locality, and real-world validation. Let’s rethink how we deploy AI in the industrial world. 🌍 #EdgeAI #IndustrialTech

🌐 𝐙𝐞𝐧𝐥𝐚𝐲𝐞𝐫 𝐥𝐚𝐮𝐧𝐜𝐡𝐞𝐬 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐈𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞 — 𝐀𝐈 𝐚𝐭 𝐠𝐥𝐨𝐛𝐚𝐥 𝐬𝐜𝐚𝐥𝐞! Unveiled at Tech Week – Cloud & AI Infra Show, Zenlayer Distributed Inference enables enterprises to deploy high-performance AI inference instantly across a hyperconnected cloud, tackling GPU inefficiencies, latency gaps, and complex orchestration challenges. 𝐊𝐞𝐲 𝐡𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: 🔹 Global Edge Infrastructure: Real-time AI experiences delivered anywhere in the world. 🔹 Optimized Performance: Scheduling, routing, networking, and memory management maximize efficiency. 🔹 Elastic GPU Access & Automated Orchestration: Scale inference across 300+ PoPs with minimal latency. 🔹 Broad Model Support & Monitoring: Streamlined deployment for AI providers and enterprises. 🔹 Cost-Effective & Scalable: Reduce idle GPU waste and deliver consistent, low-latency results globally. 𝐑𝐞𝐚𝐝 𝐌𝐨𝐫𝐞 : https://lnkd.in/dGQK_b2m   #AI #EdgeComputing #DistributedInference #HyperconnectedCloud #Zenlayer #DigitalTransformation #ArtificialIntelligence #CloudInfrastructure #RealTimeAI #Innovation

How AI Agents Automated Shipping Operations From 30 Minutes to 10 Seconds Traditional shipping workflows rely on human coordination, manual validation, and repetitive data checks, slowing down operations and increasing costs. At Quixas Technology, we built a multi-agent AI system that transforms this process into a fully automated workflow, from planning to compliance, in just 10 seconds. Here’s how: 5 specialized AI agents collaborate like a digital operations team Orchestrated through LangGraph and LangChain Powered by Google Cloud & FastAPI Result: 95% automation rate, 1000+ requests/day, and real-time decision-making This is how we’re redefining what “operational efficiency” truly means. Explore how multi-agent AI can transform your industry. Visit our website https://vist.ly/4ai5t #QuixasTechnology #AgenticAI #AIInnovation #AIAutomation #IntelligentAutomation #DigitalTransformation #AIEngineering #WorkflowAutomation #TechForBusiness #OperationalExcellence

📍 The Hidden Layer of AI: Latency > Location Everyone’s talking about capacity. No one’s talking about distance. According to IDC and Gartner, latency-sensitive AI workloads, from real-time risk scoring to autonomous systems and AR/VR are reshaping the geography of data infrastructure. The future isn’t just hyperscale. It’s hyper-local. AI inference doesn’t wait for data to travel halfway across the world. In this era, milliseconds = money. 💡 The next big competition won’t be for megawatts, but for milliseconds. The real winners will be those who can build smaller, faster, distributed nodes, edge facilities sitting within 10 ms of the end user. As AI scatters the cloud, the new infrastructure race begins: From scale → to proximity. #42UClub #AI #EdgeComputing #Latency #Cloud #DigitalInfrastructure #DataCenters Source IDC FutureScape: Worldwide Cloud 2025 https://lnkd.in/d32n9sx4 Gartner: Edge Computing for AI and Real-Time Systems, 2025 Outlook https://lnkd.in/dCWuv7TB

The AI ecosystem has entered a phase of unprecedented consolidation, one in which a handful of companies control not only the flow of algorithms and data but also the very hardware and financial arteries that power them.  AI’s future is being shaped by an intricate web of alliances where chips, cloud, and capital converge. The new power isn’t just intelligence, it’s who controls the machines that make intelligence possible. #AI #Ecosystem #anshumansharma