.png)
The AI Evolution Timeline
From the philosophical foundations in the 1950s to the current era of generative models and autonomous agents, tracing the history of Artificial Intelligence.
1950
🔥 The Turing Test
Alan Turing proposes the "imitation game," creating the benchmark for machine intelligence: the ability to exhibit human-like behavior.
1956
🔥 Birth of "AI"
The term "Artificial Intelligence" is coined by John McCarthy at the Dartmouth Workshop, officially launching the field of study.
1966
🔥 ELIZA
Joseph Weizenbaum creates ELIZA, an early natural language processing (NLP) program that simulates a conversational therapist.
1970s - 1980s
⚙️ The First "AI Winter"
A period of reduced research funding and interest, triggered by overly ambitious promises and limited computational power.
1986
⚙️ Backpropagation
The rediscovery and popularization of the backpropagation algorithm enables deep neural networks to learn efficiently.
1997
⚙️ Deep Blue vs. Kasparov
IBM's chess computer defeats the reigning world champion, marking a pivotal moment for machine strategic ability.
2011
⚙️ Watson Wins Jeopardy!
IBM's question-answering system demonstrates advanced natural language processing by beating top human contestants.
2012
⚙️ The Deep Learning Boom
AlexNet wins the ImageNet competition, showcasing the power of deep convolutional networks and GPU computing for vision tasks.
2017
🤖 "Attention Is All You Need"
The Transformer architecture is introduced, becoming the foundation for virtually all modern Large Language Models (LLMs).
2020
🤖 GPT-3
The release of GPT-3 with 175 billion parameters demonstrates unprecedented ability to generate human-quality text and code.
Nov 2022
🤖 ChatGPT is Released
The user-friendly interface of ChatGPT drives generative AI into global public consciousness, igniting the mainstream adoption race.
Nov 22, 2025
🤖 Agents & Integration
The market shifts towards AI agents, integrating complex models into workflows for autonomous, multi-step task execution.
AI Landscape: Key Metrics 2025
Visualizing the critical metrics driving the current stage of AI development.
AI Model Parameter Growth (Logarithmic Scale)
The exponential scaling of flagship models drives capability, visualized on a log scale.
Global AI Investment ($ Billions)
Tracking annual private investment, which has soared since the generative AI boom.
Enterprise Adoption Rates (Nov 2025)
Percentage of large enterprises that have implemented or are testing AI solutions.
