This article provides a detailed overview of AI in the Qualcomm Innovators Development Kit, which helps students to make powerful applications for future work.
QIDK helps both students and developers to prototype and build applications that mainly work with the Snapdragon SoC.
This Free Google course offers the best AI course to learn without any disturbance. You do not need any special experience to learn this course; you just want one phone and a strong Wi-Fi connection.
This free course also provides a hands-on lab session that helps you learn the step-by-step process of the QIDK course.
Let’s go to see other factors of QIDK in the below section.
What is AI on Qualcomm Innovators Development Kit(QIDK):-
It is a famous platform mainly designed to test all the applications of AI. It helps developers and researchers to build and test all AI applications more effectively.
It is mainly focused on areas where AI is used. It is particularly involved in areas like edge computing and on-device AI.
It is also useful for developers for testing, optimization, and building, etc of AI applications.
Duration of AI on Qualcomm Innovators Development Kit(QIDK)-
It takes only 3-4 hours to complete the course and you understand the full things about it.
Topics Covered in the AI on Qualcomm Innovators Development Kit(QIDK):-
- Introduction of AI on Qualcomm Innovators Development Kit(QIDK)
- Importance of on-device AI inference
- AI architecture of Qualcomm including the AI engine
- Definition of Stack of AI and Neural Processing SDK of Qualcomm
- The workflow of SDK neural processing includes conversion of the model, quantization of the model, and execution of the model.
- It provides proper sample solutions of QIDK, tools, and their alignment with the workflow of AI.
- Qualcomm Neural Processing SDK for easy setup of SNPE.
- Model conversion of QIDK including replacement operators, the accuracy of the model, and precision of the mixed model.
- End-to-end solutions and hands-on practice for computer vision and natural processing of language.
- Workflow of AIMET(AI Model Efficiency ToolKit, post-training of quantization(PTQ), and their results.
- Quantized model of pre-trained 8-bit with model Zoo of AIMET.
An overview of how AI can be utilized, effectively used and developed on the QIDK:-
Here are 6 steps of how effectively AI is used and developed on the QIDK.
- Platform overview- it contains 2 overviews, two of which are prototyping tools and the other is Edge of AI Focus. It allows developers to create fine AI applications for realistic hardware environments. It directly enables AI processing on the device because sometimes the application has critical conditions like low latency, data privacy, and real-time decision-making habits.
- Hardware Capabilities- it contains 3 steps to define hardware capabilities. Snapdragon SoC means it is known for integrating CPU, GPU, and DSP cores all this work to optimize performance. Hexagon DSP is a powerful feature that accelerates the workload of AI with neural network operation. AI Accelerator (NPU) orks to boost the performance of AI tasks while the power consumption is minimum.
- Software and Tools- it contains 3 steps where software and tools are defined. Qualcomm AI Stack works to build and deploy AI models using libraries and tools and also supports like TensorFlow Lite, ONNX, and PyTorch. Neural Processing SDK works to optimize and run machine learning models on Qualcomm. Model Optimization applied quantization and pruning on models to enhance performance without any accuracy.
- Use Cases– it has 4 steps where some cases used to work. Computer Vision works to provide video analysis and real-time images for applications like object detection. Natural Language Processing like chatbots and voice assistants. Robotics and Drone systems to make sensor data at the edge. IoT Applications require low latency for detective and predictive maintenance.
- Benefits of Using QIDK– it has 3 steps having some benefits. Low Latency reduces responses of time for solutions. Data Privacy works to secure data without transmitting any external services. Energy Efficiency is used for power efficiency for devices of mobile and battery.
- Development Workflow– it has 4 steps for development. Model Training uses popular Frameworks of AI for cloud platforms. Model Conversion uses tools to convert and optimize models for execution. Deployment and Testing work to test the performance, benchmarking, and refinement of QIDK. Iterative Optimization works to balance speed, accuracy, and power consumption of both models and software.
Course Objective of QIDK:-
Here, you get ideas about why we are taking this course and how it is beneficial for our future.
And is there any scope in the field of AI on QIDK?
How its model, application, and other features work.
- It provides proper ideas about learning the tools of QIDK and how to utilize them.
- For rapid app development learn SNPE Docker, and PySNPE.
- Here, you also understand how to follow such sample Android applications for prototyping applications of AI.
- You can also discuss the working process of Qualcomm Neural Processing SDK with the key aspects and with practical work.
- You can also learn how to use a model of QIDK when some operators are not supported by the Qualcomm Neural Processing SDK.
- After quantization, you have to understand and learn how to use mixed precision to attain better accuracy in SDK.
- For improved performance of the app, you have to leverage AIMET and post-training quantization.
Importance of AI on Qualcomm Innovators Development Kit(QIDK):-
Here are key points highlighting the importance of AI on QIDK.
- It can perform real-world problems and reduce dependence on the cloud.
- Enhance the privacy and security of data.
- It directly processes the data on the device.
- It provides power efficiency for Mobile and IoT Devices.
- It optimizes the performance of QIDK.
- It allows to work faster and provides more efficient execution to AI models.
- It provides innovative ideas for faster and quicker testing of tools and models.
- It supports various machine learning frameworks and model optimization tools.
- It also supports a wide range of applications for work.
- It also uses smart home devices and other devices to run AI at the edge.
- It reduces expenses while transferring data and cloud infrastructure.
- It also helps startups and opens new opportunities for smaller tech companies.
- It is mainly designed to handle complex AI models.
- Developers can easily create AI solutions using QIDK.
Why you should take this course of QIDK?
This course is designed by experienced developers for learning to learn new things about QIDK and gain more knowledge of SDK, models, and its different applications. Where you have to perform certain tasks.
The course material is from highly educated developers. They mainly do this for freshers who have no idea about QIDK. But they want to know about QIDK and learn details about it.
You can learn this course everywhere by just using the phone and with a strong WiFi connection. https://academy.qualcomm.com/course-catalog/AI-on-QIDK.
Conclusion:-
You can learn this free AI course of QIDK on the eLearning platform. You can learn this amazing course at your own pace according to your comfort. It brings innovative and new ideas to solve real-world problems.
After enrolling you can easily learn this course at your home or any other place. It makes a perfect bridge for developers to support both advanced hardware and comprehensive software.
You can also learn another free course on the same platform. There are many courses available for free learning. It makes a powerful environment for developers to harness the potential of AI on edge devices.
I hope you like this article and the article on the AI of QIDK help a lot to gain proper ideas and details about QIDK. So, you can understand what is QIDK and how it will be used in the future.
