Foundational AI Concepts
Welcome! This deck introduces foundational essential AI concepts for engineers and learners, helping build a shared vocabulary for designing intelligent systems.
Why Learn AI Foundational Concepts?
- Engineers must communicate clearly
- Concepts span across ML, NLP, and agentic systems
- Foundation for designing scalable AI
Understanding these terms helps teams collaborate and innovate effectively in AI-driven environments.
Key AI Categories
- Generative AI and NLP
- Transformers and LLMs
- Agentic architectures and APIs
Transformers & LLMs
- Transformers enable parallel processing
- LLMs generate human-like text
- Context windows and tokenization matter
These models power tools like ChatGPT and are central to generative AI.
Prompt Engineering
- Zero-shot vs. few-shot prompting
- Chain-of-thought reasoning
- Role of temperature and max tokens
Prompt design influences model behavior—critical for accuracy and relevance.
RAG vs Fine-Tuning
- RAG: Combines retrieval with generation
- Fine-tuning: Customizes model behavior
- Trade-offs in flexibility and control
Choose the right strategy based on your data, use case, and performance needs.
Model Context Protocol (MCP)
- MCP enables external tool access
- Used in agentic workflows
- Supports real-world actions like booking or emailing
MCP is a bridge between AI models and external systems—key for building intelligent agents.
Designing APIs for AI
- REST vs. GraphQL
- Authentication and security
- API design for agentic systems
APIs must be robust and secure to support AI-driven automation and decision-making.
Limits of AI
- AGI is still aspirational
- Bias and hallucination risks
- Importance of human oversight
AI is powerful but not perfect—ethical design and human-in-the-loop systems are essential.
Final Takeaways
- Master foundational concepts
- Build with clarity and purpose
- Stay updated with evolving tools
These concepts are your toolkit for navigating and contributing to the future of AI.
Foundational AI Concepts – Recorded Sessions
Ages 5–8
Foundational AI Concepts — Ages 5–8
Simple stories and examples introducing core AI ideas in a playful way.
Ages 9–11
Foundational AI Concepts — Ages 9–11
Concept-first explanations with relatable real-life examples.
Ages 12–16
Foundational AI Concepts — Ages 12–16
Clear breakdowns of LLMs, prompts, and systems thinking for teens.