AI is moving out of the cloud and into your pocket. Qualcomm’s new AI200 and AI250 chips signal a major shift in the AI ecosystem. Instead of relying on massive cloud GPUs for inference, these processors are built to run AI models directly where data is created — on the edge. Each rack of 72 chips acts like a mini data center, using Qualcomm’s Hexagon architecture to deliver high-performance computing with far greater energy efficiency. The result: AI that is faster, cheaper, and far more distributed. This could redefine how we think about smart devices and industrial automation. From factory sensors to self-driving cars, intelligence is no longer centralized — it’s embedded everywhere. The future of AI will not be owned by the biggest data centers, but by the smartest edges. How do you see decentralized AI changing your industry’s infrastructure strategy? #AI #EdgeComputing #Semiconductors #Qualcomm #FutureOfWork #TechInnovation

The I4.0 Technology Areas, Rearrange into the Following Groups: 1.Cloud Computing 2.Cognitive Computing 3.Internet of Things 4.Machine-to-Machine (M2M) 5.Mobile Technologies 6.Augmented Reality 7.Simulation 8.Additive Manufacturing 9.Advanced Robotics #Cloud #Computing #cognitive #Internetofthings #Machinetomachine #M2M #Mobile #Technology #Augmented #Reality #Simulation #Additive #Manufacturing #Advanced #Robotics #Automation #AI #Artificial #Intelligent #Internet #4IR #Industrial #Revolution

🌍 From Transistors to Cloud, Embedded to Infinity ♾️ Technology has evolved from microscopic silicon gates to vast, intelligent cloud ecosystems. What once fit on a circuit board now spans continents by connecting devices, data, and decisions in real time. As we move deeper into the era of embedded intelligence, the boundaries between hardware and software are dissolving. The next wave isn’t about scale, but it’s about synergy: where sensors think, systems adapt, and intelligence becomes ambient. We’re not just optimizing machines anymore. We’re engineering consciousness into computation. #ThoughtLeadership #EmbeddedSystems #CloudComputing #AI #EdgeAI #DigitalTransformation #FutureOfTech

“Our predictive maintenance is too slow.” “Our proprietary data isn’t secure in the cloud.” Great! Agreed. But what are you doing about it? For too many manufacturers, that’s where the revolution stalls—at the point of easier said than securely executed. You have to compromise: either you get slow, high-latency cloud AI, or you get security with zero real-time insight. The core problem is relying on external systems for internal critical processes. We built Oxmaint's Local AI platform to make real-time, end-to-end process optimization as secure as it should be. Powered by NVIDIA GPUs and Local LLMs, we eliminate the compromise. When your advanced AI agents and sensor data all reside inside your firewall, drawing from the same secure infrastructure, automating workflows across your entire plant doesn't have to be a risk anymore. Now, real-time insights flow instantly to your control systems and #ERP—not in seconds, but in milliseconds. This isn't just fast; it’s anticipatory. Join our LinkedIn Live Webinar to see the Live Demo: ⚡ No More Latency: Process thousands of sensor signals per second to achieve true, millisecond-level predictive maintenance. 🔒 No More Compromise: Your proprietary data and LLMs stay locked in your secure perimeter. 🔗 No More Checklists: Go from anticipating a fault to logging an automatic work order in one seamless, automated flow. How long will cloud latency cost you in downtime next year? And is that compromise worth the risk to your proprietary data? Secure Your Spot! WEBINAR REGISTRATION LINK: https://lnkd.in/gbHqbwMn #LocalAI #Manufacturing #Industry40 #NVIDIA #Oxmaint #PredictiveMaintenance #AIinManufacturing #Maintenance

Advanced Micro Devices (AMD) has announced an ambitious long-term outlook, forecasting that its profit will triple by 2030, driven by accelerating demand for chips that power artificial intelligence (AI), cloud computing, and advanced data centers. The semiconductor giant expects to capture a significant share of the rapidly expanding data center market, which it estimates could reach a staggering $1 trillion valuation by the end of the decade. #AMD #DataCenter #Semiconductors #ChipMarket #ArtificialIntelligence #TechNews #AIChips #DataCenters #MarketForecast #TechIndustry #AIRevolution #Innovation #FutureOfTech #BusinessNews #TechGrowth #AIHardware #Computing #HighPerformanceComputing #TechTrends #InvestmentNews #AIInfrastructure #DigitalTransformation #DataEconomy #ChipManufacturing #TechnologyLeadership https://lnkd.in/exvzvmaj

Nvidia H100 GPUs Launch into Space: Crusoe & Starcloud Pioneer Solar-Powered AI Compute Cloud Data Centers #Nvidia #H100 #AI #SpaceTech #CloudComputing #SolarPower #DataCenters #Innovation #FutureOfAI #TechTrends”

The concept of Digital Twins #DigitalTwin A Digital Twin is a dynamic digital representation of a real-world entity — such as a building, bridge, metro line, factory, or even an entire city — that uses real-time data, sensors, and AI to mirror the behavior and condition of its physical twin. With advancements in AI, cloud computing, and 5G, digital twins are evolving into cognitive twins — capable of learning autonomously and supporting automated decision-making for smart infrastructure.

Machine vision has quietly become one of the most transformative tools in modern manufacturing. What started as a niche inspection technology is now embedded across production lines, logistics hubs, and even maintenance operations. As 2026 approaches, vision systems are evolving fast, smarter sensors, faster edge computing, better software, and a growing focus on reliability. The question isn’t whether to invest, but what kind of system will still make sense three years from now. https://lnkd.in/eeFMzpdB

🚀 Call for Papers | Special Issue in Electronics #Cloud Computing and #Distributed Systems for Big #Data 🔗https://lnkd.in/d-cemipP The explosive growth of data from sensors, devices, and online systems demands robust, scalable architectures. This Special Issue focuses on the intersections of cloud computing, distributed systems, and big data analytics — exploring how these domains merge to manage, process, and derive insight from massive data sets. Submission Deadline: 15 April 2026 Guest Editor: Shan Jiang #CloudComputing #DistributedSystems #BigData #DataAnalytics #EdgeComputing #Serverless #DataSecurity #ScalableSystems #CloudArchitecture #DataEngineering #MDPI #ElectronicsJournal #CallForPapers #OpenAccess #ResearchOpportunity

𝗛𝗼𝘄 𝗗𝗼𝗲𝘀 𝗜𝗻𝘁𝗲𝗹 𝗖𝗼𝗿𝗲 𝗨𝗹𝘁𝗿𝗮 𝗕𝗿𝗶𝗻𝗴 𝗔𝗜 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗘𝗱𝗴𝗲?  AI workloads are no longer staying in the cloud. Real-time analytics, vision inspection, and intelligent automation now need to happen right at the edge, close to where data is created. In our latest blog, we break down: ✅ How Intel® Core™ Ultra processors bring built-in AI acceleration to edge computing through Intel® AI Boost and Intel® Edge AI Suites. ✅ How Premio’s BCO-500-MTL Series transforms this technology into a compact, fanless industrial solution for low-latency AI workloads at the edge. Read full blog: https://lnkd.in/gq6HSG3X