Khorus: Building an Orchestration Layer for AI Intelligence

AI Agents in Go: Exploring Agent-to-Agent (A2A) Protocols in AI Ecosystems In multi-agent systems, effective communication is what transforms isolated algorithms into coordinated intelligence. Agent-to-Agent (A2A) protocols define the structured way autonomous agents exchange information, make requests, and respond to one another. Much like human communication relies on shared languages and rules, agents rely on these protocols to ensure that messages are understood consistently across systems. By defining message formats, interaction patterns, and behavior expectations, A2A protocols enable agents to collaborate, negotiate, and act toward shared goals without central control. This structured communication allows systems to scale, adapt, and interoperate across diverse environments; from AI marketplaces and IoT networks to digital identity frameworks. In this post, I’ll walk you through how I built a simple customer profile generating agent. The agent uses Gemini AI to generate a target consumer profile based on a business idea. I designed the profiling logi https://lnkd.in/gUzerk7i

SECO expands Edge AI portfolio with six new industrial applications 🤖 The move is intended to strengthen the company’s Edge AI ecosystem and support faster deployment in production environments. 💬 Fausto Di Segni, Head of IoT and AI at SECO, said the company was focused on simplifying AI deployment at the edge. “By combining a growing portfolio of validated applications with the Clea Framework and the resources of our Developer Centre, we help companies accelerate their AI journey from concept to production, while ensuring full compatibility with existing ecosystems.” You can find out more here👉 https://lnkd.in/e2QTGHAD #IoTInsider #iot #tech #technology #AI #Industrial

Paul Williamson, who runs the IoT business at Arm, believes the next wave of AI innovation will happen “at the edge – in the devices, interfaces, and systems that bring intelligence closer to where data is created.” #arm #edge #ai #tech #internetofthings #artificialintelligence #edgecomputing #news #technology https://lnkd.in/dqUhudrH

Most companies talk about AI transformation. Keen Labs just proved it's possible. ConnectM just spun off their AI and energy tech division into a standalone powerhouse called Keen Labs—and the numbers are staggering: → Revenue exploded from $2.2M to $19.1M in just 4 years → That's an 80% compound annual growth rate → Focus areas: AI, industrial IoT, battery systems, distributed energy Here's what makes this different: They didn't just build another AI chatbot. They solved real enterprise problems in mobility, logistics, and energy transition—markets that desperately need innovation. The timing couldn't be better. While everyone's debating AI's potential, smart companies are already capturing massive value by: ✓ Targeting underserved industrial markets ✓ Combining AI with physical infrastructure (IoT + batteries) ✓ Building for the energy transition mega-trend ✓ Focusing on enterprise customers with real budgets This isn't just a spin-off story. It's a blueprint for how to build AI businesses that actually generate revenue. The companies winning in AI aren't the ones with the flashiest demos—they're the ones solving expensive problems for customers who can pay. What's your take? Are we finally seeing AI move from hype to real business value?

🌍 World Quality Week 2025 | Think Differently: Technology as the Catalyst for Quality Transformation Embracing a new perspective on Quality involves reimagining technology's role beyond monitoring to actively shaping performance. The evolution is evident: a shift from reactive to proactive quality management, driven by data, intelligence, and connectivity. 🚀 Key Technologies Revolutionizing Quality: • Artificial Intelligence (AI) and Machine Learning (ML): Predictive analytics and intelligent automation preempt issues. Advanced AI generates test cases and makes real-time quality decisions. • Internet of Things (IoT): Smart sensors and connected systems provide immediate insights throughout production, ensuring ongoing compliance and traceability. • Cloud-Based QMS: Global team unification on cloud platforms enables accessible, scalable, and auditable quality data worldwide. • Immersive Technologies (AR/VR): Virtual training and inspections empower teams to learn, simulate, and problem-solve in innovative ways. • Blockchain: Transparent records redefine data integrity and trust in intricate supply chains. • Digital Twins and Simulations: Virtual replicas aid in testing, predicting, and refining products before production. • Advanced Data Analytics: Natural language queries and augmented analytics transform data into actionable insights for quicker, smarter decisions. With the convergence of these technologies, Quality transcends a mere checkpoint to become a continuous, intelligent assurance system. 💡 Thinking differently means witnessing technology enhance user experiences by enabling prediction, prevention, and protection of crucial elements: patients, products, and the essence of trust. #WorldQualityWeek #ThinkDifferently #QualityByDesign #AIinQuality #DigitalTransformation #ProactiveQuality #ContinuousImprovement #InnovationInQuality

On November 4, during the 2025 World Conference on Innovation and Development in the Display Industry in Sichuan, BOE successfully hosted the themed matching session on "Integration of AI and Display," highlighting how artificial intelligence is shaping the future of the display industry.   "BOE has cultivated deep roots in Chengdu for many years and has actively contributed to the ongoing rise of the display industry.   We've launched the BOE AI factories, milestones that showcase our commitment to using AI to upgrade industries.   These efforts reflect BOE's belief in long-term investment and our strong resolve to empower the display industry with AI, supporting the broader vision of new industrialization." — Dr. Jiang Xingqun, Senior Vice President, Co-CTO of BOE.   Looking ahead, the future of AI-powered displays must be one of open collaboration and shared progress. BOE will continue advancing our "Empower IoT with Display" strategy, working hand-in-hand with global partners to build an AI+ Display ecosystem and promote high-quality development of China's next-generation display industry. #BOE #BOEOnSite #WCIDDI #AI

AI learns. IoT senses. But together, they can reason. Today, at the Summit of Things, Dr. Scott Gerard will explore the evolution of AI, from rule-based reasoning to data-hungry learning systems. He'll also discuss why neither approach alone is enough for the connected world we’re building. Through concepts like neural-symbolic computing and physics-informed neural networks, Dr. Scott shows how hybrid intelligence can enable smarter, more context-aware IoT systems that understand why, not just what. If your organization is working toward intelligent automation, this is a session that connects the dots between theory and application. 🔗 Join the conversation: https://hubs.ly/Q03PqD9b0 #AIoT #EdgeComputing #Sponsored

The future of AI is open, efficient, and happening at the Edge. Our own Abdel Younes, Senior Director, Machine Learning Frameworks and Billy Rutledge, Director at Google Research, explore how the new Synaptics Torq™ platform—featuring Google’s open-source Coral NPU—is redefining what’s possible for AI-native compute at the Edge. The post dives into how openness, scalability, and real-world efficiency are breaking down the barriers that have held back #Edge AI innovation. Together, we’re enabling developers to build the next generation of intelligent, context-aware devices powered by Synaptics Astra™ AI-Native compute. Read the full blog: https://bit.ly/47tTMRR #EdgeAI #AI #SynapticsAstra #Innovation #OpenSource #IoT #Collaboration

MDC Trends: How the Industry Will Change in the Next 5 Years In 2026, Machine Data Collection (MDC) is more than just a tool—it's the foundation of smart manufacturing. Over the next five years, the way we collect, analyze, and use data from machines will completely change the industry, how decisions are made, and how profitable companies are. 1. The Internet of Things is Everywhere By 2025, we are already good at putting IoT devices into every part of production. This includes machines, tools, inventory, and even smart devices that workers can wear. For example, smart sensors that can calibrate and check themselves. This helps to reduce downtime. 2. Edge-to-Cloud Data Architecture Old cloud-only systems can't handle the huge amounts of data we have today. The new "edge-to-cloud" model is a hybrid system that spreads out the work. Quick decisions happen at the edge, while more complex analysis takes place in the cloud. This is already being proven by industrial systems that use cyber-physical designs. They show that this model works well for real-time analysis on a large scale. 3. AI-Powered Maintenance Widespread predictive maintenance uses Artificial Intelligence (AI) and robotics to find equipment problems before they get worse. 4. Federated Learning for Secure AI Sharing raw industrial data between factories or companies can cause privacy problems. Federated learning solves this. The AI models are trained on local devices, and only the knowledge is shared, not the raw data. This lets companies work together without risking their intellectual property or security. 5. Digital Twins and Blockchain for Trust Using Digital Twins with blockchain makes them effective tools for diagnosis, tracking the origin of products, and secure self-running control. 6. Agent-based AI for Strategic Management New agent-based AI systems don't just guess what will happen—they make decisions and act on their own. They can change strategies in real time. For example, in data centers, agent-based AI can change production flows or schedule maintenance without needing a person to do it. This reduces downtime and makes the system more stable.

Thrilled to see Branden Kappes, our CEO at Contextualize, speaking at 2025’s Internet of Things for Manufacturing Symposium hosted by Georgia Tech. The IoTfM 2025 is a gathering of some of the world’s leading minds in digital manufacturing. Other companies speaking include leaders from Ford, Lockheed Martin, and Oak Ridge National Laboratory. At Contextualize, we are rethinking how industrial organizations connect R&D, production, and supply-chain data through our Carta platform, which transforms distributed data into a unified, semantically structured knowledge base that accelerates learning cycles, minimizes redundant data collection, and strengthens operational resilience. The result is an AI ready data infrastructure designed to scale and adapt with emerging technologies. Georgia Tech continues to lead the charge in bridging academia and industry, and we are honored to contribute to that mission at Contextualize. If you’re attending, let’s connect and explore how unified knowledge can accelerate your digital transformation journey and unveil innovations that were previously unattainable. #IoTFM2025 #AIManufacturing #KnowledgeUnification #GeorgiaTech #SmartManufacturing #Contextualize #AI #Manufacturing