Federal And Aerospace AI Suite#
Attention
Federal And Aerospace AI Suite is currently a preview release!
The suite is a comprehensive set of resources designed to accelerate the development and deployment of edge AI solutions across federal and aerospace domains, as well as demonstrate Intel’s integrated AI acceleration and real-time performance on Intel® Core™ Ultra Series 3 and Intel® Core™ Series 2 processors in defense-focused use cases.
It aims at providing a foundation for evaluating, benchmarking, and validating from handheld systems to avionics, drones, urban air mobility, space, and ground station infrastructure. In its initial, preview version, it offers the Handheld Multi-Modal application and a system blueprint to enable its full performance and capabilities. The application is optimized for AI inference on portable devices, focusing on SWaP-C compliance (Size, Weight, Power, and Cost). It also helps meet certification, ruggedness, and interoperability requirements that are important for field hardware use.
How to use the Federal And Aerospace Suite#
1. Install the Edge Node Infrastructure Blueprint#
The most efficient way to deploy the Handheld Multi-Modal app is to use the preconfigured Edge Node Infrastructure Blueprint system. To learn how to do it, refer to:
Optionally, to learn more about customizing and optimizing Operating System images, refer to:
Image Composer Tool documentation - Infra developer composes a slim, Intel-tuned Ubuntu based image for the target use case.
2. Deploy the application#
Once your system is installed, you can deploy the Handheld Multi-Modal app:
Deploy the Handheld Multi-Modal application - User runs the multi-modal handheld app (speech + chat) on Intel XPUs.
3. Run benchmarks#
To benchmark application performance, use either a curated or more comprehensive approach, with the following solutions, respectively:
Visual Pipeline And Platform Evaluation Tool (curated)- User replays workloads in VIPPET and inspects performance in Grafana.
Edge Workloads and Benchmarks (comprehensive) - User gets a unified performance and power report across AI, vision, media and GenAI workloads.
4. Use AI agent to develop your solution#
Agent skills for Infrastructure blueprint - Infra developer uses agent skills to build OS image, curate packages and tune target system.
Agent skills for DLStreamer - App developer scaffolds a working DL Streamer pipeline with agent assistance.