The big AI dreams of making machines that could someday evolve to do intelligent things like humans could - I was turned off by that. I didn't really think that was feasible when I first joined Stanford.

Andrew Ng’s quote reflects his skepticism toward the idea that artificial intelligence (AI) could one day evolve to the point where machines perform intelligent tasks in the same way humans do. He mentions the "big AI dreams" of creating machines with human-like intelligence, which was a prominent vision in the early days of AI research. However, Ng expresses his initial disbelief in the feasibility of this vision when he first joined Stanford, implying that he was not convinced by the idea that machines could fully replicate or match human intelligence.

Ng’s skepticism suggests that he viewed the goal of creating machines that could evolve to perform intelligent tasks in a human-like manner as an ambitious and perhaps unrealistic goal. This reflects a common divide in AI research: some scientists focus on creating systems that mimic human cognitive functions, while others, like Ng, believe more in practical applications of AI, such as improving specific tasks rather than pursuing broad, human-like intelligence. Ng’s approach to AI was more grounded in solving real-world problems using AI rather than chasing the elusive dream of creating fully autonomous systems with general human intelligence.

By saying that he was "turned off" by this idea, Ng is indicating his preference for a more pragmatic and focused approach to AI research. Rather than striving to replicate human-like cognition in machines, Ng was more interested in developing AI that could excel in specific areas, such as machine learning, data analysis, and automation, where practical outcomes could be achieved. This shift in focus reflects the broader trend in AI development toward narrow AI, where systems are designed to perform specific tasks rather than striving for general AI that emulates human behavior.

Ultimately, Ng’s quote highlights the tension within AI research between those who dream of creating machines with human-like intelligence and those who take a more realistic and problem-solving approach to the technology. His stance on AI suggests that, while it’s exciting to imagine machines that can think like humans, it’s more important to focus on achievable goals and practical uses of AI to benefit society.