Machine Learning is a branch of AI where systems learn from data to improve performance without being explicitly programmed.
What is Machine Learning?
Machine Learning (ML) is a subfield of artificial intelligence where algorithms learn patterns from data to make predictions or decisions.
Types of learning
- Supervised: Learning from labeled examples (classification, regression)
- Unsupervised: Discovering structures in unlabeled data (clustering)
- Reinforcement: Learning by trial-and-error with rewards (RLHF for ChatGPT)
- Self-supervised: Used by LLMs (next word prediction)
Machine Learning and LLMs
Large Language Models (LLMs) like GPT-4 and Claude use Deep Learning, an advanced form of ML:
- Pre-training: Learning from billions of texts
- Fine-tuning: Adaptation to specific tasks
- RLHF: Alignment with human preferences
Impact on visibility
Understanding ML helps optimize for AI:
- Models learn recurring patterns on the web
- Quality content is favored by algorithms
- Structured data helps learning
- Consistency and repetition reinforce associations