The Rise of Expert Systems: AI’s First Big Breakthrough

What Are Expert Systems?

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AI’s Early Days

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The First Expert Systems

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How Expert Systems Worked

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Why Were They Revolutionary?

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The Challenges They Faced

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The Shift to Machine Learning

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The Lasting Impact

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What’s Next for AI?

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The Rise of Expert Systems: AI’s First Big Breakthrough

What Are Expert Systems?

01

Expert systems are AI programs that mimic human decision-making in specialized fields like medicine, finance, and engineering.

AI’s Early Days

02

In the 1960s and 1970s, researchers created expert systems to simulate human intelligence, making AI one step closer to reality!

The First Expert Systems

03

DENDRAL (1965) – Analyzed chemical compounds MYCIN (1970s) – Diagnosed bacterial infections XCON (1980s) – Configured computer systems

How Expert Systems Worked

04

These systems used: Knowledge Base – Stored expert information Inference Engine – Applied logic to make decisions

Why Were They Revolutionary?

05

Could outperform human experts in specific tasks Made fast and accurate decisions Reduced human error in critical fields

The Challenges They Faced

06

Required manual updates to stay relevant Struggled with complex, real-world scenarios Lacked learning ability like modern AI

The Shift to Machine Learning

07

By the 1990s, expert systems declined as AI evolved. Machine learning and deep learning took over, allowing AI to learn from data instead of relying on rigid rules.

The Lasting Impact

08

Even today, expert systems influenced AI assistants, medical diagnosis tools, and financial analytics—shaping the AI we use now!

What’s Next for AI?

09

From expert systems to self-learning AI, technology keeps evolving! What do you think the future of AI will look like? Comment below!

Expert Systems in AI

Expert Systems in AI