As the marketing of almost every advanced cybersecurity product will tell you, artificial intelligence is already being used in many products and services that secure computing infrastructure. But you probably haven't heard much about the need to secure the machine learning applications that are becoming increasingly widespread in the services you use day-to-day. Whether we recognize it or not, AI applications are already shaping our consciousness. Machine learning-based recommendation mechanisms on platforms like YouTube, Facebook, TikTok, Netflix, Twitter, and Spotify are designed to keep users hooked to their platforms and engaged with content and ads. These systems are also vulnerable to abuse via attacks known as data poisoning.

For years, fraud has been a major issue in sectors like banking, medical, insurance, and many others. Due to the increase in online transactions through different payment options, such as credit/debit cards, PhonePe, Gpay, Paytm, etc., fraudulent activities have also increased. Moreover, fraudsters or criminals have become very skilled in finding escapes so that they can loot more. Since no system is perfect and there is always a loophole them, it has become a challenging task to make a secure system for authentication and preventing customers from fraud. So, Fraud detection algorithms are very useful for preventing frauds. Here comes Machine Learning which can be used for creating a fraud detection algorithm that helps in solving these real-world problems.

This article originally appeared in TechCrunch. While Elon Musk and Mark Zuckerberg debate the dangers of artificial general intelligence, startups applying AI to more narrowly defined problems such as accelerating the performance of sales teams and improving the operating efficiency of manufacturing lines are building billion-dollar businesses. Narrowly defining a problem, however, is only the first step to finding valuable business applications of AI. To find the right opportunity around which to build an AI business, startups must apply the "Goldilocks principle" in several different dimensions to find the sweet spot that is "just right" to begin -- not too far in one dimension, not too far in another. Here are some ways for aspiring startup founders to thread the needle with their AI strategy, based on what we've learned from working with thousands of AI startups.

The idea of AI-powered tools and technology transforming practices and revenue models within industries has gathered tremendous weight in the last couple of years. The reason -- artificial intelligence has backed the talk with the walk. It is becoming the real deal. Kind of like those who said the Internet was only a fad back in 1997 and it became one of the key difference makers in human history. Is the Internet still a fad?