The manual management of AI models is rapidly becoming obsolete. The rise of sophisticated AI systems, incorporating multi-modal capabilities and IoT integration, has created significant AI orchestration challenges. Intelligent automation is now crucial, transforming complex manual processes into streamlined, self-optimizing ecosystems. #AgenticAI empowers autonomous agents to manage infrastructure and processes, dynamically allocating resources, orchestrating data pipelines, and even switching between models (#LLMSwitching) for optimal performance. The primary advantage is an adaptive and resilient AI landscape. Systems become proactive, featuring predictive maintenance, automated retraining, and real-time performance monitoring. This frees up valuable human capital, allowing teams to focus on innovation and strategic initiatives. Businesses experience significant benefits, including reduced operational costs, accelerated deployment cycles, and enhanced system reliability. Scalability is dramatically improved, and #IoTAutomation enables AI agents to control and optimize connected devices, creating a truly integrated and responsive environment. At AgentNexus, we are at the forefront of advanced intelligent automation, recognizing its critical role in the future of #AIOchestration. We are developing a comprehensive framework where multi-modal, IoT-integrated agents act as architects of efficient and self-managing systems. This approach unlocks the full potential of AI, enabling organizations to achieve unprecedented levels of automation and optimization. Explore how these principles can redefine your #DevOpsAI strategy and accelerate your transition towards autonomous, high-performing AI. We invite you to consider your current orchestration challenges and explore how intelligent automation can provide effective solutions.
How #AgenticAI transforms AI management with intelligent automation.
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✨ Digital Twins in the realm of GenAI ✨ As Communications Service Providers (CSPs) evolve toward delivering more innovative products and enhancing customer experiences with greater agility, the need for flexible and scalable OSS/BSS systems becomes increasingly critical. These systems must adapt swiftly to dynamic business requirements and support rapid service deployment. Digital Network Twins (DNTs) are emerging as a pivotal technology in this transformation, especially within the OSS/BSS domain. With the advent of 5G, IoT, and other next-generation technologies, the orchestration processes have grown significantly more complex. This complexity demands faster rollout capabilities, making the role of DNTs even more vital and challenging. In this context, Generative AI (GenAI) is positioned as a key enabler in CSPs’ digital transformation journeys. GenAI enhances the capabilities of Digital Network Twins by automating design, simulating network behaviors, and optimizing operations. It empowers CSPs to: 👉 Rapidly model and deploy network configurations. 👉 Generate synthetic data for training and testing. 👉 Simulate real-world scenarios for predictive insights. 👉 Interact with network models using natural language interfaces. In this article, I’ve highlighted several impactful use cases of Digital Network Twins and explored how GenAI is playing a transformative role in shaping the future of agile, intelligent, and customer-centric network operations. #OSS #Automation #GenAI #MachineLearning #AI #CSP
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AI Everywhere: Europe’s Time to Shine ✨❤️🇪🇺👇 "Industrial AI market: 10 insights on how AI is transforming manufacturing" The global #industrialAI market reached $43.6 billion in 2024 and is expected to grow at a CAGR of 23% to $153.9 billion by 2030, according to the Industrial AI Market Report 2025–2030(published August 2025). Although #Industrial #AI spending today only represents 0.1% of revenue, most manufacturers now have a CEO-driven AI strategy with several industrial AI focus areas emerging: industrial data management/architectures, AI for quality & inspection, edge AI, industrial copilots, and employee training and upskilling, along with the first trials of agentic AI. Industrial AI operates under different rules than consumer AI. Whereas GenAI dominates consumer and office adoption for text and images, most industrial value comes from sensor time-series, machine vision, and simulations that must run reliably at the edge and integrate with OT systems. As a result, explainability, safety, and payback discipline drive what gets deployed. Thanks again to Knud Lasse Lueth and IoT Analytics for the full article with a lot more background and insights via the link below 🙏💡👇 https://lnkd.in/eWthU9Vk #semiconductorindustry #semiconductor #technology #tech #embedded #it #computing #geopolitics #chip #aiot #automation #iot #innovation #llm FBDI e.V. - Fachverband Bauelemente Distribution 🤩❤️💚
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🚀 Embracing the Power of #DigitalTwin & #AI in 2025! 🌐✨ 🎯🎯🎯🎯 At the recent Future Digital Twin & AI USA 2025 event in Houston 🇺🇸, industry leaders spotlighted how Digital Twins are transforming business intelligence from static dashboards to dynamic decision-making engines that interact in real-time with people, processes, and technology. 🤖💡 🎯🎯🎯 Imagine clicking a button and instantly influencing IoT devices out in the field based on AI-enhanced digital twin insights — that’s not the future, it’s happening now! 💥 The magic lies in combining edge computing, cloud-enabled hardware, and software to create virtual replicas that update in real-time. This reduces latency, boosts responsiveness, and scales predictive capabilities like never before. 🌩️⚡ 🎯🎯 🌱 From manufacturing shop floors optimizing operations, to agricultural digital twins revolutionizing crop management (92% accuracy in simulated environments! 🍓), to aerospace manufacturing augmenting human inspectors — the possibilities are endless! ✈️🏭 🎯 🔗 Yet, less than expected are fully leveraging this synergy between AI and digital twins. If you’re not integrating AI to unlock the full power of your digital twin strategy, there’s a huge gap in competitive advantage waiting to be filled. 📊🚀 💡 As generative AI reshapes USD standards, the edge-enabled digital twin ecosystem is poised to go out of this world. 🌍🌌 Questions on how to future-proof your enterprise with these game-changing innovations? Let’s connect! 🤝🔍 #FutureTech #Industry40 #EdgeComputing #AIInnovation #DigitalTransformation #IoT
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🚀 AI automation trends in 2025 are not just buzz—they’re reshaping industries with hyperautomation and AI agents that learn and adapt! ✨ Here’s why this matters: • AI-driven automation could add $13 trillion to the global economy by 2025 (McKinsey) 🌍 • Hyperautomation blends AI, RPA & machine learning to automate complex workflows end-to-end • Predictive analytics & IoT integration enable smarter, real-time decision-making • AI agents are evolving into autonomous collaborators, handling multi-step tasks across sectors like finance, healthcare, and logistics Imagine AI not just doing tasks but thinking and adapting alongside your team. The future is about humans + AI agents working side-by-side to unlock unprecedented productivity and innovation. How is AI automation transforming your business? What’s your biggest challenge or win with AI agents so far? Share below! 👇 What are your thoughts? Share in the comments! 💬 #AI #Innovation #AIAutomation #DigitalTransformation #EnterpriseAI
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⚙️Optimizing Tomorrow: The Evolving Consistency of Digital Twins for industries of the future In modern industries, Digital Twins (DTs) is a pivotal innovation that integrates technology to its fullest. As a virtual replicas of physical systems, DTs are meant to act as the data analytics platform, providing insights into the system they are replicating based on the need of the application and the industry. As an analytics platform layer, DTs need to be clearly defined by their need. Else, the platform would not be effective as an analytics layer within the system that it is deployed in. However a clear definition is one half of the battle. For DTs to be effective, "consistency" is a critical factor. These digital models need to be accurately aligned with their real-world counterparts, directly impacting efficiency and reliability. Research has made strides to highlight key dimensions of DT consistency, from model and data synchronization to real-time interaction. Looking ahead, the future of Digital Twins promises exciting advancements to further solidify this consistency: Real-time Dynamic Updates & Self-Healing: Imagine DTs that not only maintain perfect synchronization but can also autonomously correct deviations, enhancing overall system resilience. Enhanced Connectivity: Innovations like edge-cloud collaborative computing will enable low-latency data exchange, ensuring seamless and rapid communication between physical and virtual entities. AI-Driven Predictive Intelligence: Expect sophisticated AI models, including reinforcement learning, to anticipate issues and trigger autonomous adjustments, making operations more proactive and efficient. Secure & Collaborative Ecosystems: Integrating blockchain will bolster secure decision-making, while Federated learning will facilitate distributed optimization, improving adaptability across complex manufacturing environments. Each industry must develop it’s own consistency standard for DTs to be widely adopted. A good example is the built environment. DTs used in the built environment, be it for operational monitoring, energy modelling, even for sustainability analysis all follow the ASHRAE Guideline 14 which states a digital model must be at least 85% calibrated to reality for it to be a useable and accurate. While not explicitly about DTs, the guideline’s principles describing virtual model accuracy is highly relevant to DTs as virtual replicas and hence. This highlights the need for consistency metrics for DTs in every industry that wishes to deploy them. These advancements are crucial for ensuring Digital Twins remain highly consistent, driving a new era of resilient and efficient smart systems in all industries. #DigitalTwin #SmartSystems #Industry4 #AI #IoT #Innovation
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Which AI trends are driving change in manufacturing in 2025? Learn more in this week's virtual conference: https://lnkd.in/dPJBDibF click subscribe! According to IoT Analytics new Industrial AI Market Report 2025–2030, the market reached $43.6B in 2024 and is forecasted to grow 3.5x by 2030, fueled by developments in GenAI, edge computing, and scalable data infrastructure. Here are 8 key insights from the IoT Analytics research: ✔ Industrial AI spending remains low but rising quickly: US manufacturers invest just 0.1% of revenue into AI, but large firms are now scaling ✔ Most large manufacturers now have CEO-led AI strategies – a very different picture to what we observed when we last looked at our 2021 Industrial AI Market Report. ✔ Quality & inspection leads as the top use case, with vision systems seeing the strongest ROI ✔ Scalable data architectures and DataOps are becoming strategic imperatives ✔ Training and upskilling are emerging as critical AI enablers across operations and IT ✔ Industrial copilots (=GenAI assistants embedded in manufacturing software) are becoming standard features ✔ Edge AI is gaining traction due to latency and cost concerns, powered by new chipsets and orchestration platforms ✔ Domain-specific foundation models are emerging to “speak the language of engineering” Read more: https://lnkd.in/eBSy7jvw ⁉What Industrial AI topics are currently top of mind for you or your organization? ✅ Subscribe to #global5gevolution newsletter https://lnkd.in/ge9gsyjE ✅ Or subscribe #global5gevolution YouTube https://lnkd.in/g8M7YvKq ✅ Follow us Kaneshwaran Govindasamy & Global 5G Evolution 𝗦𝘂𝗽𝗽𝗼𝗿𝘁 𝘁𝗵𝗲 𝗚𝗹𝗼𝗯𝗮𝗹 𝟱𝗚 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆! Your support helps us continue delivering the latest insights, research & conference discussions. Every contribution enables us to sustain & grow this platform for the benefit of all members 𝗖𝗵𝗼𝗼𝘀𝗲 𝘆𝗼𝘂𝗿 𝘄𝗮𝘆 𝘁𝗼 𝘀𝘂𝗽𝗽𝗼𝗿𝘁: 👉Small monthly recurring donation: https://lnkd.in/e4MAD7pN 👉One-time donation: https://lnkd.in/eitCeewX #IndustrialAI
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🚀 The AI Tsunami is Transforming Data Science! (5 Trends You Can't Ignore) The future is now! The data science landscape is shifting *fast*, and 2025 is shaping up to be a pivotal year. Here are 5 trends I'm watching closely: 1. 🤖 Agentic AI: The Rise of Autonomous Co-Workers. Forget chatbots. Think AI *agents* managing complex workflows end-to-end. Collaborative AI networks are already transforming operations. #AgenticAI #AIAgents 2. 📊 Augmented Analytics: Democratizing Data. AI is leveling the playing field! Anyone can now leverage advanced analytics for faster, data-driven decisions. Think streamlined insight, empowered teams. #AugmentedAnalytics #DataDemocracy 3. ⚡️ Edge + IoT: Real-Time Revolution. Billions of IoT devices feeding real-time data! Edge computing delivers lightning-fast insights *at the source*. Imagine instant optimization in retail, manufacturing, and more. #EdgeComputing #IoT #RealTimeData 4. 🔧 MLOps Evolved: AI for AI. MLOps platforms are getting smarter, using AI to optimize the entire model lifecycle. Data scientists can finally focus on creativity & strategic impact! #MLOps #AIforAI 5. 🔍 Open-Source Reasoning: The Next Frontier. Open-source AI models like DeepCogito v2 are challenging proprietary solutions, offering transparency and customization crucial for enterprise adoption. #OpenSourceAI #ResponsibleAI The demand for data science talent is soaring! It's not just about analysis anymore—it's about building intelligent, autonomous systems. Which trend is most transformative in your view? Let's discuss! 👇 #DataScience #ArtificialIntelligence #MachineLearning #AI2025 #TechTrends #Innovation #Analytics #DataAnalytics
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Its been long since I shared something...got some time today to reflect and this is what I could reimagine how technology change but fundamentals do not. The Future of Manufacturing Ecosystems As I was reflecting on my digital transformation journey for 25+ years across industries, I find manufacturing and TowerCo to be among the most interesting transformations. One truth stands out: the foundations we built yesterday are shaping the opportunities of tomorrow. Manufacturing is no longer about isolated automation — it’s about ecosystems where AI, GenAI, and Agentic AI converge with IoT and advanced analytics to create intelligent, sustainable, and resilient operations. Digital operations are redefining how businesses operate — smarter, faster, and greener. From real-time monitoring and predictive analytics to generative AI–driven design, autonomous agentic systems, integrated value chains, and lifecycle optimization, the future belongs to those who see digital not as a project, but as a continuous evolution. The guiding principles remain powerful: ✅ Vertical Integration – linking shop-floor data to enterprise intelligence ✅ Horizontal Integration – connecting supply chains into digital networks ✅ Lifecycle Integration – embedding sustainability and efficiency from design to decommissioning ⚡ The next leap is clear: leveraging AI, GenAI, and Agentic AI to not only optimize assets but to reimagine manufacturing ecosystems — greener, smarter, and more human-centric. 👉 Because while machines predict and automate, it is human vision that defines purpose. #FutureOfManufacturing #DigitalTransformation #AI #GenAI #AgenticAI #IoT #Sustainability #Leadership
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⚙️ The Symbiotic Relationship: AI & Data Centers 🤝 Core Interdependence ➡️ AI Runs on Data: The precision and usefulness of AI are fueled by vast amounts of high-quality data. ⬅️ AI Optimizes Data Centers: AI itself is used to make data centers more efficient through predictive maintenance and dynamic management. 🏗️ Data Centers: The AI Backbone Modern data centers are the essential infrastructure for AI, providing: 💻 Massive Computing Power: Housing GPU-accelerated servers for real-time data processing. ⚡ High-Speed Connectivity: Advanced networking for seamless data flow between AI clusters and clouds. 🛡️ Security & Resilience: Secure, resilient systems that keep AI applications running 24/7. 🔥 Evolving for AI Demands 📶 High Density: New facilities are designed for rack densities exceeding 100kW to handle intense AI workloads. 🎯 Purpose-Built: Next-gen data centers feature architectures specifically built for AI model training and inference. 🌐 The Rise of Edge Computing The convergence of AI, 5G, and IoT is pushing compute power closer to users. Edge data centers in smaller cities are vital for ultra-low-latency services in: 🎮 Gaming 🏥 Telemedicine 🏙️ Smart Cities 🔮 Strategic Importance Data centers are now the cornerstone of learning, intelligence, and innovation. With strategic investments, India is positioned to lead the world's digital future.
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𝐀𝐈 𝐈𝐬𝐧’𝐭 𝐒𝐜𝐢-𝐅𝐢 𝐀𝐧𝐲𝐦𝐨𝐫𝐞: 𝐈𝐦𝐚𝐠𝐞𝐆𝐫𝐚𝐟𝐢𝐱’𝐬 𝐏𝐥𝐚𝐲𝐛𝐨𝐨𝐤 𝐟𝐨𝐫 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐞𝐝 𝐌𝐚𝐢𝐧𝐭𝐞𝐧𝐚𝐧𝐜𝐞 & 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐓𝐰𝐢𝐧𝐬 For years, AI sounded like something out of a sci-fi script. But in boardrooms of manufacturers and chemical plants, the conversation has shifted from “𝑊ℎ𝑎𝑡 𝑖𝑠 𝑖𝑡?” to “𝐻𝑜𝑤 𝑠𝑜𝑜𝑛 𝑐𝑎𝑛 𝑤𝑒 𝑚𝑜𝑛𝑒𝑡𝑖𝑧𝑒 𝑖𝑡?" At #ImageGrafix, our job was to turn complex #IIoT jargon—#sensors, #digitaltwins, #predictiveanalytics— into stories that decision-makers could relate to. - We showed how a pump failure predicted by a sensor saved millions in unplanned downtime. - We reframed “Digital Twins” from a buzzword into a boardroom tool for CAPEX protection and ESG compliance. - We made AI about resilience and ROI, not robots and hype. How we told the story mattered as much as the technology itself The takeaway? AI in maintenance isn’t sci-fi...it’s survival. And the right Company doesn’t just sell software; 𝐢𝐭 𝐬𝐞𝐥𝐥𝐬 𝐜𝐞𝐫𝐭𝐚𝐢𝐧𝐭𝐲 𝐢𝐧 𝐚 𝐯𝐨𝐥𝐚𝐭𝐢𝐥𝐞 𝐰𝐨𝐫𝐥𝐝. ImageGrafix Asset Management and IOT Solutions Hexagon Asset Lifecycle Intelligence Gaurav Singh Deepak Sethia Ashwini T Spandan Basu ↗️ #ImageGrafix #Hexagon #KingdomofSaudiArabia #AI #DigitalTwins #ConnectedMaintenance #IIoT #IndustrialSoftware
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