Site icon Zasus

HP & NVIDIA Developer Challenge: Transform Industries Through AI – Build, Innovate, Deploy with HP AI Studio and NVIDIA

1_healthytip
HP & NVIDIA Developer Challenge: Transform Industries Through AI – Build, Innovate, Deploy with HP AI Studio and NVIDIA

Welcome to the HP AI Studio & NVIDIA Developer Challenge! 

We’re thrilled you’re joining us to build innovative, open-source AI solutions that could transform industries. Before registering, please review the hardware requirements below to ensure you have the necessary setup for a smooth and successful hackathon experience. 

This competition is open to U.S. residents only and entitlements of HP AI Studio are limited to the first 1,000 eligible participants

Why HP AI Studio for Local AI Development?

HP AI Studio is a secure, collaborative workspace with containerization for local development, empowering teams to quickly get started with pre-configured workspaces. Co-engineered with NVIDIA and integrated with NVIDIA NGC libraries, HP AI Studio provides seamless on-prem access to optimized AI tools, ensuring maximum performance, security, and flexibility for local AI workflows. 

At its core, HP’s AI Workstation portfolio—including HP mobile and desktop workstations powered by NVIDIA RTX GPUs—delivers unmatched performance for local AI creation. By eliminating reliance on cloud infrastructure, HP AI Studio enables fast, secure, and cost-efficient AI development, right on your own hardware. Together, HP and NVIDIA are redefining how AI is developed—locally, securely, and without compromise.  

Your insights matter! As you explore HP AI Studio, we’d love to hear your feedback on how we can make it even better for local AI development. Share your thoughts, challenges, and ideas in Discord to help shape the future of AI innovation.

We can’t wait to see what you create!

 

HARDWARE REQUIREMENTS 

A Windows 10 (build 19041 and higher) or 11 or Linux Ubuntu 22.04 OS. WSL 2 (Windows Subsystem for Linux) must be enabled on setups running Windows OS. Refer to WSL Recommended Setup for more details. 

  • CPU: Intel Core™ i5 12th gen or AMD Ryzen™ 9 or higher processors 
  • GPU: NVIDIA® GPU card with CUDA® Compute capability driver version 528.89 or newer. For best performance we recommend working on the latest stable version. 
  • Storage: Minimum 50 GB of available storage 
  • VRAM: Minimum 8GB 
  • RAM: Minimum 16GB 

 

WHY JOIN?

  • Build cutting-edge AI apps: Gain hands-on experience with HP AI Studio, boosting your skills and resume. 
  • Make a real-world impact: Develop open-source AI solutions that could transform industries and benefit society. 
  • Shape the future of AI tools: Provide valuable feedback on HP AI Studio, influencing product roadmap and features as an early adopter. 
  • Test drive cutting-edge technology: Be among the first to explore HP AI Studio’s capabilities for local, on-premise AI development. 
  • Collaborate and connect: Join a vibrant community of talented developers from around the world. Share ideas, learn from each other, and build lasting connections. 
WHAT TO EXPECT

We’re excited for you to explore HP AI Studio, an evolving platform designed to power local AI development. This competition is open to U.S. participants only and limited to 1,000 accounts. 

This is your opportunity to influence product development—your participation will help shape the future of AI Studio. As we continue refining the experience, expect some bumps along the way. We recommend focusing on available AI Studio tools and limiting workspace image customizations to pip libraries as Linux package updates will not persist in the container in the current version of the software.

Your insights matter! Share local AI tips, challenges, feedback, and share ideas to help us improve through the Discord channel.

Build with us and be part of the future of local, on-prem AI development on HP AI Studio. We can’t wait to see what you create! 

Be sure to keep an eye on updates throughout the hackathon to incorporate the newest features. 

WHAT TO BUILD

Develop an AI-powered web app using HP AI Studio tools

  • 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 to the custom workspace to fit your needs. 

 Important Note:

  • apt-get packages can be installed via the terminal within a workspace (e.g., sudo apt-get install libjpeg-dev libpng-dev libtiff-dev for OpenCV support). 
  • However, these will not persist in this version of AI Studio. 
  • To avoid having to repeat Linux package updates each time a workspace is restarted, 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 leaving 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 maximum of one of the following categories: 

 
Working with HP AI Studio

Getting Started

 Get Access: After registration, check your email for HP AI Studio access credentials. If you experience any access issues, refer to the support email provided in your entitlement email. Need help? Ping the HP team in Discord for tips and questions about the hackathon. 

Join HP’s AI creator community to stay current on AI Studio updates, demos, tools, and news. After installation, submit support tickets in-app for technical support.

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

Use AI Studio Tools: Leverage the full suite of HP AI Studio tools and resources for streamlined AI development.

Workspace Customization: If modifying your workspace, limit changes to pip libraries, as Linux package updates within a running container will not persist.

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.

Deployment: Deploy models to Swagger through AI Studio for standardized API access.

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

Head over the What to Submit tab for specifics.

Exit mobile version