Autonomous Driving is a competitive market with complex security and processing challenges. This article highlights how we met concerns and constraints when developing a cloud-based Autonomous Driving re-simulation solution.
In this blog post, we want to share a Microsoft manufacturing customer’s journey that started off by setting up with them the core piece for their software development: a monolithic repository — or monorepo for short.
Microsoft CSE was involved in the process of a smart factory transformation in the automotive space, leveraging Microsoft technology, building an Industrial Internet of Things solution for factory automation.
The promise of being able to standardize on Kubernetes as a platform is attractive as it offers unique solutions to many of the challenges companies face. This post talks about the Azure Service Operator open source project that helps customers deploy Azure Resources using Kubernetes definitions
Movies and TV shows require multiple takes per scene and may have a substantial amount of archival footage as a result. Here, we use Azure Cognitive Services and custom code to develop a multi-model Machine Learning (ML) solution to automatically detect discardable footage to save media companies manual archiving hours and storage space.
Media companies capture footage filmed for the entire day in what's known as ‘digital dailies’. When talking about terabytes and petabytes of content, storage costs can be a factor. Lets explore Machine Learning approaches to identify which content can be archived or discarded which will save on those storage costs.
During pandemics, the ability to let people know if they have been exposed to a contagious disease is essential for public health practitioners. This is known as contact tracing and the COVID-19 pandemic is no exception. In this post, I describe the journey of our Microsoft team to deploy an exposure notification server on Azure.
This blog post proposes a methodology to disambiguate misspelled entities by comparing the search retrieval performance with different custom search analyzers in a search engine.
A scenario commonly encountered in public safety and justice is the need to collect and index digital data recovered from devices, so that investigating officers can perform evidence-based analysis. We recently built an advanced evidence analysis platform that uses Azure AI services for automated labelling of media and documents.
With distributed tracing handled by Azure Functions, Azure Event Hubs, and Azure Application Insights behind the scenes, Azure Application Insights provides useful monitoring visualizations of the system that helped us easily understand system performances and troubleshoot failures.
