Key Reveals from Microsoft Azure Open-Source Day 2023

The tech giant released several updates from cloud-native apps to machine learning foundation models
Listen to this story

On March 7, Microsoft held Azure Open Source Day to showcase its dedication to open source and emphasize the potential of open source tools in creating intelligent applications with increased speed and flexibility. The tech giant released several updates from cloud-native apps to machine learning foundation models. 

The event kickstarted with a group of experts from Github, HashiCorp, Microsoft, and Redis participating in a panel discussion. They discussed the development of open source in software, how it impacts software supply chain and security, and how new AI capabilities may affect the future of open source.

Azure OSS Cloud Native’s corporate vice president Brendan Burns, vice president of communities of GitHub’s Stormy Peters, and director of Microsoft’s Open Source Strategy and Ecosystem Sarah Novotny were among the panelists.

AIM Daily XO

Join our editors every weekday evening as they steer you through the most significant news of the day, introduce you to fresh perspectives, and provide unexpected moments of joy
Your newsletter subscriptions are subject to AIM Privacy Policy and Terms and Conditions.

Key Takeaways from the Event

Microsoft launched a cloud-native application that helps people reunite with their lost pets using fine-tuned machine learning. The app rids you of the hassle of printing posters by using an advanced machine learning image classification model, fine-tuned by the images on your camera roll. This machine learning model has been trained to match the photo of a pet instantly, enabling you to connect with the owner as soon as you snap a picture of the found pet.

The .NET Blazor application is utilised as the frontend of the app, while the Python backend is responsible for handling its communication. To simplify the connectivity between microservices, the distributed application runtime (Dapr) is employed, which also provides helpful application programming interfaces (APIs). 


Download our Mobile App



For the backend, a pre-built vision model from Hugging Face is utilized, which is fine-tuned directly through Azure Machine Learning to enable model training and prediction. The entire app is deployed through Bicep templates and operates on Azure Kubernetes Service. The Kubernetes Event Driven Autoscaling (KEDA) is employed to facilitate autoscaling based on the volume of messages transmitted through Dapr.

Microsoft has also released a public preview of the Florence foundation model for their computer vision service. This model has undergone training with billions of text-image pairs and has been integrated into Azure Cognitive Service for Vision, enabling it to operate as a cost-effective, ready-for-production computer vision service.

The new features of Vision, which rely on the Florence model, can be tested by users through Vision Studio.

Developers can leverage the upgraded vision services to develop advanced, production-ready, ethical computer vision applications for diverse industries. This enhancement allows customers to conveniently convert, analyze, and connect their data to natural language interactions, providing valuable insights from their image and video content. This, in turn, facilitates accessibility, enhances search engine optimization (SEO), shields users from harmful content, improves security measures, and optimizes incident response times.

The vision service offers various features such as generating detailed captions, accessible alt-text, SEO, and intelligent photo curation for digital content. Additionally, it includes video summarisation, background replacement, and other features.

Focus on Machine Learning 

The technology behemoth has introduced the public preview of foundation models within Azure Machine Learning. It has inherent capabilities that empower users to construct and execute open-source foundational models on a large scale.

The Azure Machine Learning specialists can commence their data science projects effortlessly, fine-tuning and deploying foundation models obtained from various open-source repositories, starting with Hugging Face, via Azure Machine Learning components and pipelines. This service will furnish a comprehensive collection of popular open-source models via the built-in Azure Machine Learning registry, catering to multiple tasks such as natural language processing, vision, and multi-modality. 

Users can employ these pre-trained models directly for deployment and inferencing, while also being able to finetune supported machine learning tasks with their own data and directly import any other models from the open-source repository.

Here are a few more highlights from the event showcasing recent innovations and Microsoft’s contribution to open source:

  1. This month, Microsoft will be introducing a new feature in ACPT – Nebula – that enables data scientists to save checkpoint times faster than current solutions for distributed large-scale model training jobs with PyTorch. In testing, Nebula achieved a 96.9% reduction in single checkpointing time when saving medium-sized Hugging Face GPT2-XL checkpoints. It can significantly reduce checkpoint times, potentially by 95 percent to 99.9 percent, thus, reducing end-to-end training time in large-scale training jobs.
  1. Introduced new integrations with Azure Database for MySQL– Flexible Server and the Microsoft Power Platform, which simplify the development process and allow users to analyze data, automate processes, and build apps using low-code tools.

Sign up for The Deep Learning Podcast

by Vijayalakshmi Anandan

The Deep Learning Curve is a technology-based podcast hosted by Vijayalakshmi Anandan - Video Presenter and Podcaster at Analytics India Magazine. This podcast is the narrator's journey of curiosity and discovery in the world of technology.

Shyam Nandan Upadhyay
Shyam is a tech journalist with expertise in policy and politics, and exhibits a fervent interest in scrutinising the convergence of AI and analytics in society. In his leisure time, he indulges in anime binges and mountain hikes.

Our Upcoming Events

24th Mar, 2023 | Webinar
Women-in-Tech: Are you ready for the Techade

27-28th Apr, 2023 I Bangalore
Data Engineering Summit (DES) 2023

23 Jun, 2023 | Bangalore
MachineCon India 2023 [AI100 Awards]

21 Jul, 2023 | New York
MachineCon USA 2023 [AI100 Awards]

3 Ways to Join our Community

Telegram group

Discover special offers, top stories, upcoming events, and more.

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Subscribe to our Daily newsletter

Get our daily awesome stories & videos in your inbox
MOST POPULAR

Council Post: The Rise of Generative AI and Living Content

In this era of content, the use of technology, such as AI and data analytics, is becoming increasingly important as it can help content creators personalise their content, improve its quality, and reach their target audience with greater efficacy. AI writing has arrived and is here to stay. Once we overcome the initial need to cling to our conventional methods, we can begin to be more receptive to the tremendous opportunities that these technologies present.