What is GPT?
GPT stands for "Generative Pre-trained Transformer." It's a family of large language models created by OpenAI that can generate human-like text based on input prompts.
Breaking Down the Name
Generative = creates new content. Pre-trained = learned from massive data before use. Transformer = the neural network architecture.
GPT-1 (June 2018)
- Parameters: 117 million
- Training: Books corpus
- Significance: Proved that pre-training on lots of text, then fine-tuning for specific tasks, worked surprisingly well
- Reception: Noticed by researchers, not the public
GPT-2 (February 2019)
- Parameters: 1.5 billion (10x larger)
- Training: Web pages (WebText dataset)
- Significance: Could generate coherent paragraphs; OpenAI initially withheld the full model, citing misuse concerns
- Headlines: "Too dangerous to release" sparked debate about AI safety
GPT-3 (June 2020)
- Parameters: 175 billion (100x larger than GPT-2)
- Training: Massive internet text, books, Wikipedia
- Significance: Could write essays, code, poetry; perform tasks with just instructions (no fine-tuning needed)
- Impact: Launched the API, enabling thousands of applications
ChatGPT (November 2022)
- Based on: GPT-3.5 (improved GPT-3)
- Key innovation: Fine-tuned for conversation using RLHF (Reinforcement Learning from Human Feedback)
- Impact: Fastest-growing consumer app in history; 100 million users in 2 months
- Significance: Made AI accessible to everyone; triggered the current AI boom
GPT-4 (March 2023)
- Parameters: Not disclosed (rumored ~1 trillion)
- New capability: Multimodal—can understand images, not just text
- Performance: Passes bar exam, scores well on SATs, writes better code
- Significance: Crossed threshold where AI became genuinely useful for complex professional tasks
Key Lessons from GPT's Evolution
- Scale matters — Bigger models with more data performed better at each step
- Emergent abilities — Capabilities appeared that weren't explicitly trained
- RLHF breakthrough — Human feedback made models much more useful and safe
- Access creates innovation — Opening the API led to countless applications
The Future
- GPT-5 and beyond in development
- Focus shifting to reasoning, reliability, and multimodal abilities
- Competitors (Claude, Gemini, Llama) driving rapid innovation
Summary
- • GPT evolved from 117M parameters (2018) to trillions (2023)
- • Each generation brought surprising new capabilities
- • ChatGPT's RLHF training made AI conversational and accessible
- • GPT-4 added vision and professional-grade reasoning