Raspberry Pi has recently introduced the AI HAT+, designed to improve the performance of artificial intelligence applications, offering two performance options: a 13 TOPS model priced at $70 and a 26 TOPS model priced at $110. Both devices are equipped with Hailo AI accelerators specifically designed for efficient machine learning tasks.

Features and Advantages

1. Integrated Design: The Hailo-8 chip is directly integrated onto the PCB, simplifying the installation process and improving thermal management, making it particularly suitable for high-demand tasks like real-time image processing and running multiple neural networks simultaneously.
2. Local Execution of Large Language Models (LLMs): With its high computing power (up to 26 TOPS), the AI HAT+ can efficiently handle intensive inference tasks, enabling faster responses and real-time language processing without relying on cloud services. This capability allows for privacy-focused edge AI applications, as LLMs can run directly on the device.
3. Enhanced Performance: The AI HAT is equipped with a neural processing unit (NPU) or a dedicated AI accelerator, significantly boosting the Raspberry Pi’s ability to handle machine learning and deep learning tasks. This enables more efficient LLM inference, delivering faster processing speeds than using the CPU alone.
4. Energy Efficiency: Running LLMs is resource-intensive and can lead to high power consumption. The AI HAT is designed to be energy-efficient, allowing the Raspberry Pi to perform these tasks without excessive power usage, which is especially beneficial in low-power environments or projects with energy consumption concerns.
5. Edge AI Capabilities: With the AI HAT, Raspberry Pi devices can run LLMs directly at the edge, enabling real-time natural language processing (NLP) without needing to send data back to a cloud server. This is crucial for privacy-sensitive applications or situations where internet connectivity is limited.
6. Scalability: The AI HAT supports scalable AI applications, allowing multiple Raspberry Pi devices to run LLMs across a network, facilitating the development of low-cost, scalable AI solutions applicable in real-world scenarios such as chatbots, assistants, or localized AI systems.
7. Real-Time Applications: The AI-optimized hardware of the AI HAT enables the Raspberry Pi to be used in real-time applications, such as voice assistants or interactive robots, where quick responses to natural language queries are essential. LLMs can process and understand user inputs rapidly, making interactions more seamless.

Conclusion

The launch of the Raspberry Pi AI HAT+ makes it possible to efficiently handle large language models on low-cost, compact devices, making AI more accessible at the edge and opening up new use cases in real-time, low-power environments.

Photo Credit: Raspberry Pi