The First AI Winter (1974–1980): Expectations vs. Reality
What Was the AI Winter?
Imagine being excited about a new toy that promises a lot but doesn’t quite deliver. That’s what happened with AI in the 1970s. Researchers had high hopes, but the technology wasn’t advanced enough to meet expectations. This led to reduced funding and interest, known as the AI Winter.
Why Did It Happen?
- Limited Computing Power: Computers weren’t powerful enough to handle complex AI models.
- High Expectations: People expected AI to solve problems like a human, but it was far from it.
- Lack of Data: AI models needed a lot of data to learn, which wasn’t available at that time.
The Second AI Winter (1987–1993): A Repeat of Challenges
The second AI Winter occurred in the late 1980s due to similar reasons. Despite advancements, AI technologies like expert systems (programs that mimic human expertise) didn’t live up to the hype, leading to another round of reduced interest and funding.