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The amount of compute happening at the edge is growing fast due to the amount of data generated by edge devices and processes. Many edge computing deployments are now also moving to incorporate AI. Businesses are looking to automate for multiple reasons: to achieve pricing competitiveness, to relieve the effects of labor shortages, to expand innovation, to add efficiency, to improve time to market, and to deliver new services.
However, working at the edge is often complex and challenging for a variety of reasons:
Difficulty building performant edge AI solutions with high return on investment (ROI) across a range of use cases.
The diversity of edge hardware, software, and power requirements.
Lack of secure and cost-effective methods to move and utilize high data volumes required by AI at the edge while maintaining low latency.
Increasingly complex operations management of distributed edge devices and applications at scale.
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In response to these challenges and opportunities, Intel announced its new Edge Platform, a modular, open software platform enabling enterprises to develop, deploy, run, secure, and manage edge and AI applications at scale with cloud-like simplicity. Together, these capabilities are intended to accelerate time-to-scale deployment for enterprises, contributing to improved total cost of ownership (TCO).
Use Cases
Example use cases for the new platform include defect detection and preventive maintenance in industrial facilities, frictionless checkout and inventory management in retail, and traffic management and emergency safety in smart cities/transportation. These use cases typically require advanced networking and AI analytics at the edge with low latency, locality, and cost requirements coupled with a mix of on-premises analytics with aggregation and placement of some AI processing in the cloud to manage global deployment locations.
The open, modular Intel Edge Platform looks to enable ready-made solutions across industries. By leveraging Intel’s edge experience and broad ecosystem to make the most in-demand edge use cases available, enterprises can purchase a complete solution or build their own in existing environments. Enterprise developers can build edge-native AI applications on new or existing infrastructure and manage edge solutions end-to-end for their specific use cases. The platform provides infrastructure management and AI application development capabilities that can integrate into existing software stacks via open standards.
About Edge-Native Infrastructure:
The platform’s edge infrastructure has a built-in OpenVINO AI inference runtime for edge AI as well as a secure, policy-based automation of IT and OT management tasks. Intel’s OpenVINO has evolved over the past five years to help developers optimize applications for low latency, low power, and deployment on existing hardware specifically at the edge, enabling standard hardware already deployed to run AI applications efficiently without costly upgrades or refactoring.
The platform has a single dashboard that enables IT and DevOps personnel to provision, onboard and manage a fleet of edge nodes, including edge servers, industrial controls, HMI devices and others. This is accomplished securely and remotely with zero touch, across day 0/1/2 operations. Closed-loop automation enables operators to leverage policies and observability to trigger business logic from operational alerts at the edge, optimizing operations across the network and improving TCO. Deep, heterogeneous hardware awareness allows resource allocation for optimal efficiency, as well as zero-trust security features co-developed for Intel architecture.
About Edge AI + Applications Capabilities:
The platform is designed to provide enterprise developers with access to powerful AI capabilities and tools, including:
Finely tunable application orchestration for remotely placing latency-sensitive workloads on the right device for best application performance.
Powerful low-code to high-code AI model/app development with hybrid AI capabilities from the edge to cloud.
A range of horizontal edge services like data annotation services that leverage Intel Geti to build AI models, as well as vertical industry-specific edge services to improve results in common industrial use cases using video and time series information and digital twin capabilities to track and manage environments.
Edge Platform will come to market with industry leaders and broad ecosystem support that includes Amazon Web Services, Capgemini, Lenovo, L&T Technology Services, Red Hat, SAP, Vericast, Verizon Business, and Wipro.