✅ Early Foundations (1950s–1970s)

Alan Turing (1950): Proposed the Turing Test to measure a machine’s ability to exhibit intelligent behavior indistinguishable from a human.

1956 Dartmouth Conference: Considered the birth of AI as a field of study. Researchers gathered to explore whether machines could “think.”

Early Programs: Simple problem solvers and “expert systems” began to appear, such as programs for chess or logical reasoning.

✅ The Rise and Challenges (1980s–1990s)

Expert Systems (1980s): AI was applied in business and medicine through rule-based systems that could make decisions in narrow domains.

AI Winters: Periods of reduced funding and interest (mid-70s and late-80s) due to slow progress and high expectations not being met.

✅ Modern Era of AI (2000s–Today)

Big Data & Machine Learning (2000s): The explosion of digital data enabled AI systems to train more effectively.

Deep Learning (2010s): Neural networks achieved breakthroughs in image recognition, natural language processing, and speech recognition.

Generative AI (2020s): Tools like ChatGPT, MidJourney, and DALL·E demonstrated AI’s ability to generate human-like text, images, and other creative content.

✅ Milestones at a Glance

1950s: Turing Test, symbolic AI.

1980s: Expert systems used in medicine and industry.

2010s: Self-driving cars, image recognition, smart assistants.

2020s: Generative AI and widespread AI adoption.