For the past decade or so, the conversation around artificial intelligence (AI) has focused on how this new technology can solve a myriad of business problems. While that's true, the conversation missed a critical component for AI success: high-quality data.
Without high-quality data, an investment in AI technology and algorithms is essentially moot. If you invest in AI technology without also investing in high-quality data, it's the same as hiring unqualified, unmotivated employees to operate your business.
The quality of the training data you use to train your AI algorithm determines the quality of your output. If the training data is of low quality, you'll get low-quality solutions, which will lead you to make decisions that won't benefit your company.
It's time to shift the conversation from which business problems AI can solve to how to make your AI technology the best it can be—and that conversation starts with understanding the AI lifecycle.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/04/20/managing-the-data-for-the-ai-lifecycle/?sh=18804d5555ed
Without high-quality data, an investment in AI technology and algorithms is essentially moot. If you invest in AI technology without also investing in high-quality data, it's the same as hiring unqualified, unmotivated employees to operate your business.
The quality of the training data you use to train your AI algorithm determines the quality of your output. If the training data is of low quality, you'll get low-quality solutions, which will lead you to make decisions that won't benefit your company.
It's time to shift the conversation from which business problems AI can solve to how to make your AI technology the best it can be—and that conversation starts with understanding the AI lifecycle.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/04/20/managing-the-data-for-the-ai-lifecycle/?sh=18804d5555ed
