Elevators that respond to voice commands, cameras that notify store managers when to restock shelves and video streams that keep tabs on everything from cash register lines to parking space availability. These are a few of the millions of scenarios becoming possible thanks to a combination of artificial intelligence and computing on the edge. Standalone edge devices can take advantage of AI tools for things like translating text or recognizing images without having to constantly access cloud computing capabilities.
At its Ignite digital conference, Microsoft unveiled the public preview of Azure Percept, a platform of hardware and services that aims to simplify the ways in which customers can use Azure AI technologies on the edge – including taking advantage of Azure cloud offerings, such as device management, AI model development, and analytics. For example, a company may want to set up a system to automatically identify irregular produce on a production line so workers can pull those items off before shipping.
Azure Percept Vision and Azure Percept Audio, which ships separately from the development kit, connect to Azure services in the cloud and come with embedded hardware-accelerated AI modules that enable speech and vision AI at the edge, or during times when the device is not connected to the internet. That is useful for scenarios in which the device needs to make lightning-fast calculations without taking the time to connect to the cloud, or in places where there is not always reliable internet connectivity, such as on a factory floor or in a location with spotty service.
In addition to announcing hardware, Microsoft says it is working with third-party silicon and equipment manufacturers to build an ecosystem of intelligent edge devices that are certified to run on the Azure Percept platform.
Making AI at the edge more accessible
The goal of the Azure Percept platform is to simplify the process of developing, training and deploying edge AI solutions, making it easier for more customers to take advantage of these kinds of offerings.
For example, most successful edge AI implementations today require engineers to design and build devices, plus data scientists to build and train AI models to run on those devices. Engineering and data science expertise are typically unique sets of skills held by different groups of highly trained people.
The hardware in the Azure Percept development kit uses the industry standard 80/20 T-slot framing architecture, which the company says will make it easier for customers to pilot proof-of-concept ideas everywhere from retail stores to factory floors using existing industrial infrastructure, before scaling up to wider production with certified devices.
As customers work on their proof-of-concept ideas with the Azure Percept development kit, they will have access to Azure AI Cognitive Services and Azure Machine Learning models as well as AI models available from the open-source community that have been designed to run on the edge.
In addition, Azure Percept devices automatically connect to Azure IoT Hub, which helps enable reliable communication with security protections between Internet of Things, or IoT, devices and the cloud. Customers can also integrate Azure Percept-based solutions with Azure Machine Learning processes that combine data science and IT operations to help companies develop machine learning models faster.
In the months to come, Microsoft aims to expand the number of third-party certified Azure Percept devices, so anybody who builds and trains a proof-of-concept edge AI solution with the Azure Percept development kit will be able to deploy it with a certified device from the marketplace.
Security and responsibility
Because Azure Percept runs on Azure, it includes the security protections already baked into the Azure platform.
Microsoft also says that all the components of the Azure Percept platform, from the development kit and services to Azure AI models, have gone through Microsoft’s internal assessment process to operate in accordance with Microsoft’s responsible AI principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.
The Azure Percept team is currently working with select early customers. Ultimately, Microsoft hopes to enable the development of an ecosystem of intelligent edge devices that can take advantage of Azure services in the same way that the Windows operating system has helped enable the personal computer marketplace.