Why Microcontrollers are a good AI companion
This YouTube video discusses the implications of artificial intelligence (AI) on microcontroller projects and programming in general. Key takeaways include:
AI and Rules:
- AI excels at finding rules (pattern recognition), not defining them. Humans define rules through strategic decision-making and choices, a process AI currently cannot replicate. This is a crucial distinction, emphasizing the human element in high-level decision-making and strategy.
- Three types of rules: Created rules (ethical, legal, etc.), discovered rules (physical laws), and formulas (mathematical equations). AI’s strength lies in discovering rules from data.
- AI’s two phases: Training (learning rules from data) and inference (applying learned rules). Training is resource-intensive; inference is relatively efficient.
AI and Programming:
- AI as a new compiler: AI can automate parts of programming by generating code based on prompts (a new programming language). However, writing effective prompts requires human skill and understanding of the problem.
- AI’s role in automating existing processes: AI can learn rules from past transactions to automate business processes without writing conventional code. This saves time and resources in implementing existing rules.
- Challenges of replacing conventional programming with AI: AI systems are not always predictable, may “hallucinate” (produce incorrect outputs), and pose challenges for testing and ensuring compliance with regulations.
A Hybrid Approach:
- AI agents as orchestrators: A blend of AI and conventional programming is suggested. AI agents can decide which conventional systems are needed, generate specifications, and manage the execution, while existing systems handle the precise, predictable tasks. This combines AI’s pattern recognition with the reliability of conventional programming.
- N8n and similar frameworks: These tools facilitate the integration of AI agents with existing business systems.
Microcontrollers and AI:
- Practical application: The video demonstrates a project using an ESP32-CAM, a cloud AI service (ChatGPT API), and a motion sensor to control a cat water fountain. Only when a cat is detected does the pump activate. This illustrates how microcontrollers can connect AI to the physical world.
- Future potential: The presenter envisions future applications like automated garage door opening based on license plate recognition or preventing pets from entering a cat door with undesirable items.
Overall:
The video argues that AI won’t replace programmers entirely but will significantly change the nature of programming. The future likely involves a hybrid approach, leveraging AI’s strengths in pattern recognition and automation while relying on conventional systems for precision, reliability, and compliance. Microcontrollers will play a crucial role in bridging the gap between AI and the physical world.