Qualcomm AI Hub

What is Qualcomm AI Hub?

Qualcomm AI Hub is a comprehensive platform designed to facilitate the deployment and optimization of AI models on Qualcomm devices. It serves as a central repository for optimized open-source and licensed models, allowing developers to seamlessly integrate AI capabilities into their applications. The platform aims to accelerate the adoption of on-device AI by providing the necessary tools and resources for model compilation, profiling, and deployment.

How does Qualcomm AI Hub work?

Qualcomm AI Hub streamlines the process of bringing AI models to edge devices. Here’s a breakdown of its functionality:

• Model Submission: Users can submit their own pre-trained models to the platform.
• Compilation: The platform converts trained models and optimizes them for on-device deployment. This involves selecting a target device and runtime environment.
• Profiling: Once compiled, the model can be run on a physical device to analyze its performance. Key metrics such as compute unit utilization, latency, and memory consumption are tracked.
• Deployment: Finally, the compiled model can be downloaded, integrated into an application using provided sample apps, and deployed on the target device.

Key Features of Qualcomm AI Hub

• Optimized AI Models: Access a wide range of pre-optimized AI models tailored for Qualcomm devices.
• Model Compilation: Easily convert and optimize models for on-device deployment by selecting the target device and runtime.
• Performance Profiling: Gain insights into model performance on actual devices, including compute unit utilization, latency, and memory metrics.
• Ecosystem Support: Leverage an ecosystem of model makers, cloud providers, runtime environments, and SDK partners to create end-to-end machine learning solutions.
• Runtime Support: Support for various runtime environments, including LiteRT and ONNX Runtime.
• Device Compatibility: Compatible with a range of Qualcomm devices, including the Snapdragon® 8 Elite.

Use Cases

Qualcomm AI Hub supports a variety of use cases across different industries:

• Mobile: Enabling intelligent connections and personalized applications on mobile devices.
• Compute: Leveraging AI for powerful devices in computing environments.
• Automotive: Transforming the automotive industry with AI-powered mobility solutions.
• IoT: Deploying real-time AI on various IoT devices for enhanced user experiences.

Why Choose Qualcomm AI Hub?

• Simplified Deployment: The platform simplifies the process of deploying AI models on Qualcomm devices, saving developers time and effort.
• Optimized Performance: Models are optimized to run efficiently on Qualcomm hardware, ensuring optimal performance.
• Comprehensive Ecosystem: Access a wide range of tools and resources to support the entire AI development lifecycle.
• Broad Compatibility: Supports various devices, runtimes, and AI models, making it a versatile solution for different applications.

Supported Models and Services

Qualcomm AI Hub features models from various sources, including:

• Mistral: Explore models from Mistral AI.
• Tech Mahindra: Check out Tech Mahindra’s IndusQ 1.1B.
• Preferred Networks: Learn more about PLaMo 1B by Preferred Networks.
• Granite: Integrate Granite‑3B‑Code‑Instruct into applications.
• G42: Access G42’s Jais 6.7B.
• Llama: Try out Llama3.2, an open-source AI model that can be fine-tuned and deployed anywhere.
• Roboflow: Explore Roboflow’s computer vision solutions.
• Amazon SageMaker: Train, fine-tune, and deploy models on edge devices using Amazon SageMaker.
• Dataloop: Utilize Dataloop’s automated pipeline for data curation.
• Edge Impulse: Create AI applications with hardware-aware AI model optimizations.
• AlwaysAI: Build on-device computer vision workflows and optimize with Qualcomm AI Hub.
• EyePop.ai: Build and train custom vision models with EyePop.ai and run inference on-device.

How to Get Started with Qualcomm AI Hub

1. Log in: Access the platform via the Qualcomm AI Hub website.
2. Submit a model: Bring your own trained model to the platform.
3. Compile: Convert and optimize your model for on-device deployment.
4. Profile: Run the compiled model on a physical device to analyze its performance.
5. Deploy: Download the compiled model and integrate it into your application.

Who is Qualcomm AI Hub for?

Qualcomm AI Hub is ideal for:

• AI developers looking to deploy models on Qualcomm devices.
• Mobile, compute, automotive, and IoT developers seeking to integrate AI capabilities into their applications.
• Organizations aiming to optimize AI performance on edge devices.

By leveraging Qualcomm AI Hub, developers can efficiently deploy and optimize AI models on Qualcomm devices, unlocking new possibilities for on-device AI applications. The platform's comprehensive features and ecosystem support make it a valuable resource for anyone working in the field of edge AI.