Artificial Intelligence
History of AI; Generative AI
C-CAT
History of AI
Timeline of AI Development
| Year | Event | Significance |
|---|---|---|
| 1943 | Warren McCulloch & Walter Pitts — mathematical model of a neuron | First mathematical neuron model |
| 1950 | Alan Turing — "Computing Machinery and Intelligence" — Turing Test | Foundation of AI |
| 1951 | Christopher Strachey — first AI program (checkers game) | First game-playing AI |
| 1956 | John McCarthy coined "Artificial Intelligence" at Dartmouth Conference | Birth of AI as a field |
| 1958 | Frank Rosenblatt — invented the Perceptron | First neural network |
| 1965 | DENDRAL — first expert system (chemical analysis) | First expert system |
| 1969 | Shakey — first general-purpose mobile robot (Stanford) | First mobile robot |
| 1972 | PROLOG — logic programming language for AI | AI programming language |
| 1980s | Expert Systems boom | Commercial AI era |
| 1997 | IBM Deep Blue defeated chess champion Garry Kasparov | AI beats human at chess |
| 2002 | First commercially successful robotic vacuum cleaner (Roomba) | Consumer AI robotics |
| 2005 | STANLEY — autonomous car won DARPA Grand Challenge | Autonomous vehicles begin |
| 2006 | Geoffrey Hinton — Deep Belief Networks | Deep learning renaissance |
| 2011 | IBM Watson won Jeopardy! | AI wins at language comprehension |
| 2012 | AlexNet — CNN revolution in computer vision | CNN breakthrough |
| 2016 | AlphaGo (DeepMind) defeated world Go champion | AI defeats human at complex game |
| 2017 | Transformer architecture introduced (Google) | Foundation of modern NLP |
| 2018 | BERT — bidirectional language model (Google) | NLP breakthrough |
| 2020 | GPT-3 — 175B parameters | Generative AI milestone |
| 2020 | Baidu LinearFold — predicts COVID RNA in 27 seconds (120× faster than other methods) | AI accelerates pandemic response |
| 2022 | ChatGPT launched — 1 million users in 5 days | Generative AI goes mainstream |
| 2023–2024 | GPT-4, Gemini — multimodal AI; Generative AI uses text, voice, images, video | Gen AI era |
AI Winters & Springs
1st AI Winter (1974–1980): Funding cuts due to overpromised results.
2nd AI Winter (1987–1993): Collapse of expert systems market, loss of interest.
AI Spring (2012–present): Deep learning revolution, big data, GPU computing.
Key Figures in AI
| Name | Contribution |
|---|---|
| Alan Turing | Turing Test, foundations of computation |
| John McCarthy | Coined "AI", invented LISP, organized first AI conference |
| Marvin Minsky | Co-founded MIT AI Lab |
| Claude Shannon | Information theory |
| Frank Rosenblatt | Perceptron |
| Geoffrey Hinton | Deep learning, backpropagation (Turing Award 2018) |
| Yann LeCun | Convolutional Neural Networks (Turing Award 2018) |
| Yoshua Bengio | Deep learning research (Turing Award 2018) |
| Andrew Ng | Popularized deep learning; Google Brain, Coursera |
Generative AI
What is Generative AI?
Generative AI (Gen AI) refers to AI systems that can generate new content — text, images, audio, video, code — that resembles but is distinct from their training data.
Key technologies:
- Large Language Models (LLM) — generate text (GPT, Llama)
Diffusion Models — generate images (DALL-E, Stable Diffusion)
- GAN (Generative Adversarial Networks) — generate realistic images/videos
Major Generative AI Products
| Product | Company | Capabilities |
|---|---|---|
| ChatGPT | OpenAI (Microsoft-backed) | Text generation, coding, Q&A |
| DALL-E | OpenAI | Image generation from text |
| Google Bard / Gemini | Text + integrated with Gmail, Google Lens | |
| GitHub Copilot | GitHub + OpenAI | Code generation, completion |
| Midjourney | Midjourney Inc. | High-quality image generation |
| Stable Diffusion | Stability AI | Open-source image generation |
| Claude | Anthropic | Conversational AI, long context |
| Llama | Meta | Open-source large language model |
How Generative AI Works
Training Data → Transformer Model → Fine-tuning (RLHF) → Prompt → Generated Output
| | |
(Text/Images) (Self-attention) (Reinforcement Learning
from Human Feedback)
Applications of Generative AI
| Sector | Application |
|---|---|
| Healthcare | Drug discovery, medical report generation |
| Manufacturing | Design optimization, defect detection |
| Software Development | Code generation, debugging, documentation |
| Financial Services | Automated report generation, risk analysis |
| Media & Entertainment | Script writing, personalized content |
| Advertising & Marketing | Ad copy, personalized campaigns |
Risks of Generative AI
- Deepfakes — fake videos/images of real people
- Misinformation — AI-generated false news articles
- Hallucination — AI confidently generates incorrect facts
Bias — training data biases reflected in outputs
- Copyright issues — AI trained on copyrighted content without consent
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