Embedded artificial intelligence refers to the technology of running artificial intelligence algorithms on embedded devices. Embedded devices often have storage, computing power, and energy consumption constraints, so AI algorithms need to be optimized to reduce resource requirements and improve performance. Embedded artificial intelligence can realize real-time environment awareness, human-computer interaction and decision-making control without networking.
There are many technologies involved in embedded artificial intelligence, mainly including the following aspects:
- Fast matrix multiplication and approximate matrix multiplication to reduce the complexity and storage of matrix operations.
- Fast convolution algorithm and approximate convolution algorithm are used to reduce the complexity and storage amount of convolution operations.
- Model compression and quantization to reduce the number and accuracy of model parameters and improve the speed of model inference.
- Neural network architecture search for automated design of efficient neural networks for embedded devices.
- Embedded development tools for deploying and running AI models on different embedded platforms.
Embedded AI has several advantages and challenges:
Advantage:
- The power of artificial intelligence can be realized without relying on the cloud, improving the security and privacy of data.
- AI capabilities can be implemented in offline or low-bandwidth environments, improving application reliability and flexibility.
- It can be analyzed and reasoned locally when the data is generated, which improves the real-time and efficiency of the application.
Challenge:
- It is necessary to ensure the performance and accuracy of artificial intelligence algorithms under the conditions of limited storage, computing power and energy consumption.
- The compatibility and portability of AI algorithms need to be realized on a variety of embedded platforms.
- It is necessary to realize the adaptability and scalability of artificial intelligence algorithms under changing application scenarios and needs.
Embedded AI is suitable for the following areas:
- Smart homes and the Internet of Things, such as smart speakers, smart cameras, smart light bulbs, etc., can realize functions such as voice recognition, face recognition, and scene recognition.
- Smart cars and driverless cars, such as self-driving cars, drones, robots, etc., can realize functions such as road condition recognition, obstacle detection, and path planning.
- Smart medical and health, such as smart watches, smart glasses, smart blood pressure monitors, etc., can realize heart rate monitoring, vision detection, blood pressure measurement and other functions.
- Intelligent education and entertainment, such as smart toys, smart teaching aids, smart game consoles, etc., can realize language learning, knowledge quizzes, game interaction and other functions.