Welcome to the HP AI Studio & NVIDIA Developer Challenge!
🎉 We’re excited to invite you to the HP AI Studio & NVIDIA Developer Challenge, an incredible opportunity to build innovative, open-source AI solutions designed to transform industries. Before you dive in, let’s make sure you’re set up for success by reviewing the essential hardware requirements for a smooth hackathon experience.
🚨 Important Note: This competition is open only to U.S. residents, and entitlements for HP AI Studio are limited to the first 1,000 eligible participants. Don’t miss your chance to be one of them!
Why Choose HP AI Studio for Local AI Development?
HP AI Studio provides a secure, collaborative workspace tailored for local AI development. With containerization, it empowers teams to quickly initiate projects using pre-configured environments. Co-engineered with NVIDIA, HP AI Studio integrates seamlessly with NVIDIA NGC libraries, ensuring on-prem access to optimized AI tools for maximum performance, security, and flexibility in your local AI workflows.
At the heart of HP’s AI Workstation portfolio—featuring HP mobile and desktop workstations powered by NVIDIA RTX GPUs—lies unmatched performance for local AI creation. By reducing reliance on cloud infrastructure, HP AI Studio allows for fast, secure, and cost-effective AI development right on your own hardware. Together, HP and NVIDIA are redefining how AI is created—locally, securely, and without compromise.
Your insights are invaluable! As you explore HP AI Studio, we welcome your feedback on how we can enhance it for local AI development. Share your thoughts and ideas in our Discord community to help shape the future of AI innovation. We can’t wait to see what you create! 🚀
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Hardware Requirements
To ensure your setup is ready for AI development, please meet the following hardware requirements:
- Operating System: Windows 10 (build 19041 and higher) or 11, or Linux Ubuntu 22.04. If using Windows, ensure WSL 2 (Windows Subsystem for Linux) is enabled.
- CPU: Intel Core™ i5 12th gen or AMD Ryzen™ 9 or higher.
- GPU: NVIDIA® GPU card with CUDA® Compute capability driver version 528.89 or newer. For optimal performance, use the latest stable version.
- Storage: Minimum 50 GB of available storage.
- VRAM: Minimum 8 GB.
- RAM: Minimum 16 GB.
Why Join the Challenge?
Participating in the HP AI Studio & NVIDIA Developer Challenge offers numerous benefits:
- Build Cutting-Edge AI Applications: Gain hands-on experience with HP AI Studio, enhancing your skills and bolstering your resume.
- Make a Real-World Impact: Develop open-source AI solutions that can transform industries and bring societal benefits.
- Shape the Future of AI Tools: As an early adopter, your feedback will influence the product roadmap and future features of HP AI Studio.
- Test Drive Cutting-Edge Technology: Be among the first to explore the capabilities of HP AI Studio for local, on-premise AI development.
- Collaborate and Connect: Join a vibrant community of talented developers from around the world. Share ideas, learn from one another, and forge lasting connections.
What to Expect
We’re thrilled for you to explore HP AI Studio, a dynamic platform designed to empower local AI development. This challenge is limited to U.S. participants and capped at 1,000 accounts, so seize this unique opportunity to influence product development. Your participation will help shape the future of AI Studio.
As we continue to refine the experience, expect some bumps along the way. Focus on the tools available in AI Studio, and please limit workspace image customizations to pip libraries, as Linux package updates will not persist in the current version.
Your input is essential! Share your local AI tips, challenges, and feedback through our Discord channel.
Build with us and be part of the evolution of local, on-prem AI development on HP AI Studio. Stay tuned for updates throughout the hackathon to incorporate the newest features!
What to Build
To participate, consider developing an AI-powered web app using HP AI Studio tools. Here are some guidelines:
- Explore example AI Studio projects on GitHub for inspiration and sample code on registering models with MLflow.
- Utilize AI Studio workspace images or create a custom image by modifying pip libraries or providing a requirements.txt file tailored to your needs.
Important Note:
- You can install apt-get packages through the terminal in a workspace (e.g.,
sudo apt-get install libjpeg-dev libpng-dev libtiff-devfor OpenCV support). However, these will not persist in the current version of AI Studio. - To avoid repeating Linux package updates each time a workspace restarts, use existing AI Studio workspace images.
- If your project requires Linux package updates (e.g., libjpeg-dev), we are documenting steps to re-install, or you can leave the workspace running until the model is registered.
- Pip libraries added through the customization feature will persist across sessions.
Your solution should showcase HP AI Studio’s capabilities while addressing real-world industry challenges in a designated category.
Working with HP AI Studio
Getting Started
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Get Access: After registration, check your email for HP AI Studio access credentials. If you experience access issues, refer to the support email provided. Need help? Ping the HP team in Discord for tips and questions about the hackathon.
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Join HP’s AI Creator Community: Stay updated on AI Studio developments, demos, tools, and news. After installation, submit support tickets in-app for technical support.
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Start Building: Follow our 45-minute tutorial to create your first project. Check the resource library on GitHub for sample projects and product overviews to get up to speed quickly.
- Find Inspiration: Explore example projects and code samples on the Resources tab to spark new ideas.
Development Best Practices
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Use AI Studio Tools: Leverage the full suite of HP AI Studio tools and resources for streamlined AI development.
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Workspace Customization: If modifying your workspace, limit changes to pip libraries, as Linux package updates within a running container will not persist.
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Model Management: Use MLflow in AI Studio to register models for local deployment, organize artifacts, and set hooks to track performance via the monitor tab.
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Deployment: Deploy models to Swagger through AI Studio for standardized API access.
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Application Development: Build an industry-specific AI web app that tackles real-world challenges. Create a ‘demo’ folder in MLflow to generate and store artifacts. Web files in the demo folder will automatically deploy in Swagger. Alternatively, create the web app outside of AI Studio, locally host the web app server, and point your web app to the Swagger endpoint.
- Deployment Options: Publish your web app for local inference.
What to Submit
For specifics on submission requirements, head over to the "What to Submit" tab.
Embark on this journey with us and unleash your creativity in the world of AI!
