Bigger Is Not Better: Why A Complex Deep Learning Network Is Often Worse than a Simple One for Business Problems

Artificial intelligence (AI) is rapidly advancing in the business world, with an increasing number of companies employing deep learning networks to improve their operations. However, it may come as a surprise that more complex and sophisticated deep learning models may not necessarily be better suited for solving business problems. In fact, in many cases, deploying a simpler network can yield more effective results. In this blog post, we'll explore why complex deep learning networks can be inefficient and even detrimental when applied to business scenarios. In my experience, one of the biggest challenges with deep learning networks is obtaining enough training data to achieve accurate results.