Lenny's Reads An AI Glossary
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Jun 24, 2025 Dive into the fascinating world of AI terminology with simple explanations for terms like LLM, transformer, and hallucination. Discover what models really are and learn about pre-training, fine-tuning, and reinforcement learning from human feedback. Unpack the revolutionary impact of transformers and how prompt engineering enhances output. Explore the differences between AGI and ASI, why models hallucinate, and the significance of synthetic data. This insightful discussion makes complex concepts accessible for everyone.
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Model and Transformer Basics
- A model is a computer program that mimics the human brain to process input and generate responses.
- Transformers enable models to consider all words simultaneously, improving understanding and enabling large, powerful AI systems.
How AI Training Works
- Training AI involves feeding huge datasets and adjusting model weights to improve next word predictions.
- This method underpins models' abilities to understand grammar, reasoning, and context.
Types of AI Learning
- Supervised learning trains models on labeled data, while self-supervised learning uses AI-generated labels.
- Unsupervised learning lets models find patterns without guidance, useful for clustering and anomaly detection.