We're only just starting to understand the true potential of technology at the intersection of Artificial Intelligence, MLOps (Machine Learning & DevOps), Cloud Computing and Edge Computing - but the possibilities are endless.
For the past few years, our AI Engineers, Data Scientists and Cloud Advocates at Microsoft have been working with the University of Oxford to further the development of these technologies and further the practical application of these in the world.
The collaboration has resulted in the University of Oxford offering specific courses on AI and Cloud/Edge computing - and on the development of the AI Edge Engineer Learning Path on Microsoft Learn.
The interplay between AI, cloud, and edge is a rapidly evolving domain. Currently, many IoT solutions are based on basic telemetry. The telemetry function captures data from edge devices and stores it in a data store. Our approach extends beyond basic telemetry. We aim to model problems in the real world through machine learning and deep learning algorithms and implement the model through AI and Cloud on to edge devices. The model is trained in the cloud and deployed on the edge device. The deployment to the edge provides a feedback loop to improve the business process (digital transformation).
In the AI Edge Engineering learning path, we take an interdisciplinary engineering approach. We aspire to create a standard template for many complex areas for deployment of AI on edge devices such as Drones, Autonomous vehicles etc. The learning path presents implementation strategies for an evolving landscape of complex AI applications. Containers are central to this approach. When deployed to edge devices, containers can encapsulate deployment environments for a range of diverse hardware. CICD (Continuous integration - continuous deployment) is a logical extension to deploying containers on edge devices. In future modules in this learning path, we may include other techniques such as serverless computing and deployment on Microcontroller Units.
The engineering-led approach underpins themes / pedagogies for engineering education such as
Ultimately, AI, cloud, and edge technologies deployed as containers in CICD mode can transform whole industries by creating an industry-specific, self-learning ecosystem spanning the entire value chain. We aspire to design such a set of templates/methodologies for the deployment of AI to edge devices in the context of the cloud. In this learning path, you will:
Produced in partnership with the University of Oxford – Ajit Jaokar Artificial Intelligence: Cloud and Edge Implementations course
Now, we're bringing together the team at Microsoft and the academics at University of Oxford that worked to build this learning path - and you can meet them and find out more about this free Learning Path, as well as some of the amazing applications of these technologies, at our event on 1st October.
Mumbai Tel Aviv Berlin London NYC Seattle 10.30pm 8pm 7pm 6pm 1pm 10am
You can receive an event reminder by registering here http://aka.ms/aiedge-register
Watch on demand NOW!
You must be a registered user to add a comment. If you've already registered, sign in. Otherwise, register and sign in.