Speakers
Description
A dynamic demonstration showcasing cutting-edge solutions for the seamless management and deployment of Artificial Intelligence (AI) models within automotive-grade environments. This presentation will highlight an innovative approach to integrating and orchestrating AI capabilities directly on in-vehicle systems.
What You Will Experience:
This session will provide a live, in-depth look at a robust system designed for building, deploying, and managing AI models on AutoSD images. Attendees will gain insights into:
Automated Image Construction: Witness how specialized image building tools can create AutoSD images capable of hosting sophisticated AI models within a QM environment. This streamlines the process of preparing automotive platforms for AI integration.
Secure AI Model Execution: Explore the integration of a powerful runtime environment that enables AI models to operate securely and efficiently within the QM environment, crucial for safety-critical automotive applications.
Centralized AI Model Management: Discover how a distributed system management framework is leveraged to provide comprehensive control over AI models. This includes capabilities for:
Real-time Status Monitoring: Observe the health and status of AI model instances across connected nodes.
Dynamic Model Listing: See how deployed and available AI models can be quickly cataloged and identified.
On-Demand Model Provisioning: Understand the process of pulling and preparing new AI models for deployment.
Interactive AI Inference: Participate in a live demonstration of interacting with a deployed AI model, sending prompts, and receiving real-time responses, showcasing the responsiveness and practical application of the integrated AI.
Key Technical Highlights (Demonstrated Live):
The demonstration will involve a practical walkthrough, illustrating how to:
Prepare and Run the Automotive Image: Building AutoSD images with integrated AI runtime capabilities. Launching and connecting to the live virtualized automotive environment.
Monitor and Manage AI Services: Using command-line tools to inspect the status of nodes and AI-related units. Listing available and deployed AI models within the system.
Deploy and Utilize AI Models: Initiating the download and preparation of new AI models. Activating AI model serving units. Interacting with a running AI model by sending prompts and observing the generated output.
Why This Matters: This demonstration provides a compelling vision for the future of AI in automotive systems, enabling: Faster iteration and deployment of AI-powered features. Enhanced security and isolation for AI workloads. Efficient management of diverse AI models across vehicle fleets. The foundation for true software-defined vehicles with dynamic AI capabilities.
Any other info we should know?
System Requirements:
Linux with at least 25GB of free space.
Python 3.12 or higher installed.
Experience level –
Intermediate - attendees should be familiar with Linux & Containers basics.
Session author's bio
Automotive IoT evangelist and a firm believer of open source technologies impact on our lifestyle.
| Please confirm that there are included headshots of all speakers in their profiles | Yes |
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| Level of Difficulty | Intermediate |
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| In Person Attendance | In-person |