SEPTEMBER, 20218 THIS GAME OF AIThe new definition of technology today is "AI". Many companies have claimed to be a technology company by connecting itself to AI. It has a few different definitions throughout the history of computer science. From expert systems to machine learning including Bayesian models and support vector machine, each of them had its moment. With the recent advances in deep learning, AI resurged in various areas. This game of AI has been changing. One might therefore wonder: why has it not been popular in applications until now? What is changing our way of working with AI essentially? The answer is not going to be simple.In a business environment, different companies have different strategies when they face the new AI technologies, owing to the nature of their business. Some of the companies became early players in this game of AI adopters because these early players had the resources to equip themselves with talents of the right skills. At the same time, they also had less concerns about the technology and put all their focus solely on the performance. On the other hand, the companies hesitated to join the game because they either did not have the resources to build the right team, or they wanted to wait until they fully understand the technology and all the potential legal/ethical issues were cleared. The gap between early and late players had even grown larger. One of the major reasons is "deep learning." As the most successful AI technology today, deep learning is considered expensive too. A deep learning model can be as huge as you want, and the training can also be as expensive as the size of the model grows.BY ANGUS KONG, AVP OF DATA SCIENCE, TOKOPEDIAIN MY OPINION
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