👁️ What if every camera could become an intelligent eye? That is the promise of Computer Vision + AI. With an AI Box, intelligence can move closer to the camera — enabling video streams to be analysed locally for events, patterns and actionable insights. From security & surveillance to retail, transportation, infrastructure and smart cities, the evolution is happening: Camera → AI Box → Computer Vision → Insight → Action At Transline, we are bringing together CCTV, Biometrics, AI, Computer Vision and Edge AI through our technology ecosystem and NETRA stack. The future isn't just about capturing more video. It's about understanding what the video means. See. Understand. Respond. The camera is becoming a sensor. The AI Box is becoming the brain. And Computer Vision is becoming the intelligence layer. 👁️🧠 #ComputerVision# #AI# #EdgeAI# #AIBox# #VideoAnalytics# #CCTV# #Biometrics# #NETRA# #ArtificialIntelligence# #DigitalIndia#

Security arrangements at the Red Fort have been stepped up ahead of the Independence Day celebrations, with a multi-layered anti-terror response plan, more than 1,000 CCTV cameras and AI-based video analytics, a senior police officer said on Friday. Security agencies have also carried out mock drills and held advance liaison with various stakeholders to improve coordination during the event. Deputy Commissioner of Police (North) Raja Banthia said the arrangements were aimed at ensuring security while causing minimum inconvenience to people attending the celebrations. Prime Minister Narendra Modi will unfurl the national flag and address the nation at the Red Fort on Saturday. #RedFort# #IndependenceDay# #IndependenceDay2026# #DelhiPolice# #ITCard#

🌐 Microsoft brought 11 papers to NSDI 2026, the frontier of large-scale networked systems. This digest spans concrete advances for AI infrastructure: 4x throughput from KV-cache reuse, 3.2x over RDMA with CXL memory, and more. Title: Microsoft at NSDI 2026: Advances in large-scale networked systems URL: 📝 Overview NSDI is a leading venue for sharing new research on the design and operation of cloud, AI, and distributed application infrastructure. This post highlights Microsoft's 11 accepted papers spanning datacenter networks, wide-area networking, AI systems, and cloud infrastructure. ❓ Challenges Solved As AI workloads surge, scaling datacenter network, memory, and CPU resources while preserving reliability and cost efficiency keeps getting harder. The papers tackle that frontier from both production operation and research angles. 💡 Key Research Contributions ・DroidSpeak reuses KV caches across same-architecture language model variants for up to 4x throughput with minimal impact on output quality ・SONiC DASH SmartSwitch redesigns cloud network offloading and is deployed at scale in Azure, significantly improving power and space efficiency (community award winner) ・Octopus, a CXL disaggregated memory pod, achieves RPCs 3.2x faster than in-rack RDMA and 2.4x faster than CXL switches on three-server prototypes ・HarvestContainers dynamically harvests cores from latency-sensitive containers, using up to 75% of spare CPU while keeping tail latency within 4% of standalone 🎯 Use Cases It informs design decisions for faster LLM serving, memory disaggregation, container resource utilization, and network-protocol verification across cloud and AI infrastructure. 📊 Other Results ・Eywa used LLM-based model generation to find 33 bugs (16 previously unknown) in protocol implementations ・ForestColl generates theoretically optimal collective-communication schedules in polynomial time ・AVA is a video-analytics benchmark reaching 75.8% accuracy on 10+ hour videos ・KRAKENGUARD provides fine-grained eBPF isolation for multi-tenant security #NetworkedSystems# #AIInfrastructure#