The Era of Large Language Models
Transformer (2017)
Meaning: A new architecture using attention → focuses on most important words in a sentence.
Example: In "The cat sat on the mat," it learns "cat" is related to "mat," not just the next word.
LLMs (Large Language Models)
Meaning: Transformers trained on billions of words → can generate human-like text, code, or act as agents.
Examples: GPT-5, Claude, Gemini, Llama.
Embeddings
Meaning: Words → numbers that capture meaning.
Example:
- "King - Man + Woman ≈ Queen."
- Google uses embeddings to return results for "car repair" even if you typed "fix my vehicle."
RLHF (Reinforcement Learning with Human Feedback)
Meaning: Humans rate AI answers, so the model learns what sounds more natural/helpful.
Example: If GPT gives 3 answers, humans upvote the clearest one. Model learns to sound more human.
RAG (Retrieval-Augmented Generation)
Meaning: LLM searches external knowledge before answering.
Example: A company chatbot checks HR policies before answering employee questions → ensures accuracy.
Enterprise Examples:
- Healthcare: Summarizing doctor notes, generating insurance letters.
- Recruiting (MaximizeHire.ai): Parsing resumes, drafting interview reports.
- Retail (Walgreens): Chatbots answering prescription questions, summarizing product reviews.
The Car Analogy - Complete Picture
LLMs = A car that not only drives itself but also talks, plans the trip, and hires a driver.
It's the ultimate evolution - from manual control (classical ML) to self-learning (deep learning) to full autonomy with reasoning capabilities (LLMs).