Build Your Intelligent Edge

on YouTube ↗31m

" summary

Shows how to deploy cloud‑trained machine‑learning models to edge devices by packaging them as IoT Edge containers that run locally and sync when connectivity returns. Demonstrates this on ~2,000 coffee machines using Azure services—device twins and DPS provisioning, IoT Hub, Stream Analytics and Cosmos DB—for telemetry, plus gateways that speak Modbus and legacy OT to allow offline analytics, tolerate intermittent satellite links, and resume batched uploads without losing model state.

AI-written summary · about

" chapters (8)

1. 0:00Intelligent edge solutions
2. 3:30Open source at Microsoft
3. 7:55Cloud security for devices
4. 12:08Device provisioning
5. 17:54Data storage and analytics
6. 23:20Real-time device communication
7. 27:54Developer tools
8. 30:14Cost and business for edge

" related talks

• 49mEnable IoT with Edge Computing and Machine LearningJared Rhodes · Update Conference Prague 2018
• 27mFrom Edge to Enterprise: Intelligent IoT ArchitecturesSaravanan Ganesan · Software Architecture Conference 2026
• 57mWhy should you care about edge computing?Glenn F. Henriksen · NDC London 2019
• 45mFrom Data to AI on The EdgeHenk Boelman · Build Stuff 2020
• 32mExtending machine learning to industrial IoT applications at the edge with AWSIan Perez Ponce · Arm AIoT Dev Summit 2019
• 43mCloud Computing: Connect,process and earn money -living on the edgePaweł Fiderek · 4Developers 2020
• 42mBuilding IoT solutions using Azure IoT EdgeEdwin van Wijk · Future Tech 2019
• 41mCloud Computing: The Edge talks - long road into the CloudRafał Warzycha · 4Developers 2020