Small Language Models: The Future of Edge Tech

AI Without Compromising Privacy 🚀🔒 Federated Learning is transforming how industries like healthcare, finance, and IoT build smarter models—without exposing sensitive data. At ATS Management LLC, we design secure federated learning architectures, enable privacy-preserving training, and accelerate AI adoption while ensuring compliance. The future of AI is collaborative, decentralized, and privacy-first. Are you ready to unlock it? 🔹 #FederatedLearning #AI #MachineLearning #DataPrivacy #HealthcareAI #FinanceAI #IoT #DataSecurity #Innovation #ATSManagement

Welcome to the Era of 1-bit LLMs! The future of AI is becoming leaner, faster, and more accessible! As large language models (LLMs) continue to power breakthroughs in automation, customer support, healthcare, and more, one of the biggest challenges remains — computational cost and energy consumption. That’s where 1-bit precision fine-tuning comes in. By reducing model precision to its bare minimum while maintaining performance through techniques like error compensation and gradient scaling, we are opening doors to: Ultra-efficient AI that runs on edge devices Faster training with less memory Sustainable, low-power solutions for real-world applications From smarter customer support bots to AI assistants on smartphones and IoT devices — the era of 1-bit LLMs is set to redefine how we deploy and scale AI across industries. Let’s embrace this new frontier and innovate responsibly! reference - https://lnkd.in/dUMRiCen #AI #LLM #1bitAI #Quantization #EdgeAI #SustainableTech #MachineLearning #DeepLearning #CustomerSupport #Innovation #FutureOfAI

Edge AI vs Cloud AI, Trade-offs, Challenges, and the Future Every AI request, whether recognizing an image, translating speech, or running a recommendation, faces a key question: where should it be processed? Cloud AI: High computational power Low latency isn’t guaranteed, especially for real-time tasks Energy-intensive Data leaves your device → privacy concerns Edge AI: Computation happens directly on your device Real-time responses, critical for self-driving cars, AR/VR, and IoT sensors Energy-efficient, avoids sending huge amounts of data to the cloud Better privacy, data stays local But Edge AI has limitations: Smaller memory and compute capacity Harder to run massive models. Hardware varies across devices → optimization is complex This raises a big question for the AI community: Will the future of Edge AI rely on optimizing models to run efficiently on small devices, or will we keep designing new, specialized chips to handle bigger models at the edge? This reel visualizes cloud vs edge processing, highlighting latency, energy, and privacy differences. I’d love to hear your thoughts, model optimization vs hardware innovation: which path will dominate? and to what extent do you think we can optimize? Subscribe to My Channel for more: https://lnkd.in/dUFv9DBu #EdgeAI #CloudAI #AIHardware #MachineLearning #DeepLearning #NeuralNetworks #IoT #AIOptimization #RealTimeAI #DataPrivacy #AIExplained #FutureOfAI #HardwareAwareAI

🔷 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗔𝘀𝘀𝘂𝗿𝗮𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝗔𝗜 𝗳𝗼𝗿 𝟱𝗚 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 🔷 🤖 At RESI S.p.A., we are pioneering 𝗗.𝗔.𝗜.𝗠𝗢𝗡. (Dynamic Artificial Intelligence Monitoring), an ambitious project funded under the 𝗠𝗜𝗦𝗘 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗔𝗴𝗿𝗲𝗲𝗺𝗲𝗻𝘁𝘀 - 𝗦𝗲𝗰𝗼𝗻𝗱 𝗖𝗮𝗹𝗹, aimed at redefining how networks are monitored and optimized through advanced AI capabilities. 💡𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 𝗼𝗳 𝘁𝗵𝗲 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻: ✔️𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 - Spotting anomalies and critical events before they escalate ✔️𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 - Anticipating traffic patterns and potential bottlenecks ✔️𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 (𝗤𝗼𝗘) - Measuring user-centric performance with high granularity ☁️ By integrating cloud orchestration, IoT/M2M data, and machine learning models, the system enables predictive diagnostics, intelligent configuration, and seamless network evolution. 🤝 This initiative is carried out together with IPS S.p.A., NetResults, and the University of Bologna (Alma Mater Studiorum – Università di Bologna), combining academic and industry expertise to accelerate innovation in telecom service assurance. 🔗 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿 𝗺𝗼𝗿𝗲: https://lnkd.in/dghNMwCY #AI #5G #Telecom #ServiceAssurance #Innovation

Is the Transformer architecture dead? 🤯 Google DeepMind just unveiled a new AI model that's 2x faster and uses half the memory. Imagine the traditional Transformer as a hospital where every patient (or "token") goes through every single department, regardless of the ailment. MoR, or Mixture-of-Recursions, is a new kind of hospital. Its lightweight "router" intelligently triages each token, sending simple ones home quickly while routing complex ones for deeper, recursive passes. Here’s why it's a paradigm shift: Smarter, Not Bigger: Reuses a single set of shared layers, dramatically cutting down on parameters. Inference Efficiency: The result is up to 2x faster inference and a 50% reduction in memory usage. Democratizing AI: This efficiency could bring more powerful AI to resource-constrained devices, from mobile phones to IoT. This isn't just an optimization; it's a fundamental rethinking of how LLMs reason and use computational resources. What are your thoughts? Is this the beginning of the post-Transformer era, or just an exciting new path forward? Share your take below! 👇 #AI #MachineLearning #DeepLearning #LLM #MoR #Transformer #GoogleDeepMind #TechInnovation

Did you know that ~90% of the data companies collect is under-used or unused? That’s called dark data. 📂 We often focus on new tools or flashy dashboards, but some of the biggest gains come from activating the data we already have. Here are 3 powerful ways to turn dark data into true business impact: 📈 Discover what’s hiding: Audit sources like logs, emails, old files, IoT devices; there may be patterns, risks, or insights waiting. ⚡ Clean & Integrate smartly: Use AI/NLP or knowledge graphs to unify semistructured/ unstructured data so it can talk to your current systems. 🎯 Operationalize insights: Make dark-data driven decisioning real, like automating anomaly alerts, improving customer experience, optimizing operations. Dark data = lost potential. But with the right strategy, that “wasted” data becomes actionable intelligence. #AI #MachineLearning #FutureOfWork #SmartData #DataDriven #Innovation #TechTrends #BusinessGrowth

The upcoming industrial revolution, often referred to as Industry 4.0, is being driven by one crucial resource: data. 🚀 It's more than just a buzzword; data analytics is the engine driving this monumental shift. From predictive maintenance in manufacturing to hyper-personalized customer experiences in retail, data is empowering businesses to make smarter, data-driven decisions. This isn't just about efficiency; it's about gaining a competitive edge by transforming raw information into actionable insights. 📈 In the tech industry specifically, data analytics is creating a ripple effect. It's the foundation for advancements in AI, machine learning, and IoT, enabling us to build smarter products and services. Companies that harness the power of data will not only survive but thrive, leading the way in innovation and shaping the future of technology. What's your take on the role of data analytics in this revolution? Share your thoughts below! 👇 #DataAnalytics #BigData #Industry4 #DigitalTransformation #TechIndustry #FutureOfWork #AI #MachineLearning #DataScience #Innovation

🌍 AI Computing in 2025: Smarter, Greener, More Connected AI is evolving fast—showing human-like reasoning, energy awareness, and real-world adaptability. 🔹 Smarter AI: Moving beyond simple outputs, AI now handles ambiguity, explains decisions, and adapts to context. Avalue’s GPU Expansion Systems deliver the power needed for LLMs and conversational AI. 🔹 Sustainability First: AI is not only more efficient but also helps drive greener operations—from supply chain optimization to carbon management. At Avalue, we support this with low-power ePaper and durable HMI solutions. 🔹 AI + Edge + IoT: Their convergence enables real-time, decentralized intelligence across industries—factories, healthcare, retail, and more. ✨ At Avalue, we build AI-ready infrastructure to help businesses stay ahead. Explore more: https://lnkd.in/gsEjyHz9

🌍 Global Data & Analytics Trends in 2025 Data isn’t just numbers anymore—it’s the fuel behind every decision, innovation, and competitive edge. Here are 5 trends shaping the future right now: 1️⃣ AI Agents & Synthetic Data 🤖 – speeding up workflows while keeping data private & compliant. 2️⃣ Edge AI ⚡ – bringing real-time analytics closer to IoT & 5G devices. 3️⃣ Sovereign Clouds ☁️ – nations pushing for local data storage & control. 4️⃣ Data Infrastructure M&A 📈 – companies buying data firms to strengthen their AI pipelines. 5️⃣ AI + Automation ROI 💡 – measuring actual business impact, not just dashboards. 🔑 Why it matters: These shifts show where opportunities, risks, and next-gen jobs will emerge in data analytics & engineering. ✨ If you’re in this space, which of these trends excites you most? #DataAnalytics #DataEngineering #AI #EdgeAI #Automation #Cloud #TechTrends2025 #BigData #DataStrategy

How Nordic manufacturers are using AI to create better business outcomes? Manufacturers are moving beyond automation and experimenting with how to integrate AI into every layer of their operations. AI isn’t just about cost savings – it’s about reshaping how to work and compete at a global scale. We see four key areas where Nordic manufacturers can benefit from AI solutions: 1. Process Efficiency: AI transforms real-time data from IoT devices into actionable insights, enabling smarter operations and higher efficiency. 2. Data Integration and Governance: AI only delivers value when it has access to clean, structured, and well-governed data. Leading manufacturers are investing in unified data backbones to connect siloed systems and create a competitive advantage. 3. Autonomous Operations: Human–machine cooperation is becoming the norm, with AI agents handling decision-making and humans providing strategic oversight. 4. Cybersecurity: Modern factories are highly connected environments, and every device is a potential entry point. AI models can detect abnormalities faster than human teams, but it’s crucial to embed governance, security, and compliance into every AI project from day one. Interested in how AI can reshape your business? Read the full blog post by Victoria Palacin and Lars Pittman to discover more 👉 https://hubs.ly/Q03H0X0C0 #AI #Manufacturing #DigitalTransformation