From the course: Twelve Myths about Data Science
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Implementing AI is a one-time project, not an ongoing process
From the course: Twelve Myths about Data Science
Implementing AI is a one-time project, not an ongoing process
- Today, let's address a common misconception. The notion that integrating AI into your business is a one-time task. Many believe that once AI is implemented, your business is all set. This idea suggests that with AI, you can simply set it and forget it, expecting AI to just run flawlessly without any further intervention. However, the reality is that deploying AI is akin to embarking on a marathon, rather than a sprint. It requires continuous engagement with frequent adjustments and updates necessary to ensure optimal performance. Consider AI systems as similar to high performance vehicles. They require regular maintenance to remain competitive, and they require very specific things to make them operate at their peak performance. It's like navigating a ship but not having any idea where you're going. You're going to end up off the map eventually. Take this fictional company, Acme Inc., a company that adopted AI hoping for a quick solution to their operational challenges. Initially…
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AI will solve all our problems effortlessly3m 5s
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Data science projects will always yield immediate ROI3m 51s
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AI and automation will replace human decision-making entirely3m 11s
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Data quality is not as important as quantity2m 11s
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Machine learning models are always objective and unbiased2m 51s
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Data science is solely a technical discipline3m 8s
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Deep learning is the answer to every problem3m 29s
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AI and machine learning will replace jobs, leading to mass unemployment5m 19s
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Anyone can become a data scientist with a short online course4m 46s
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Data science is only relevant for large corporations3m 20s
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Implementing AI is a one-time project, not an ongoing process2m 37s
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More data always leads to better results2m 18s
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