AI hype cycle is distracting companies
Machine learning is having an \”AI\” issue. It’s time to differentiate today’s practical ML from research projects. With new generative AI capabilities released every few months, and AI hype escalating even more, it’s important that we distinguish most of the current ML projects. It’s important to correctly name these projects. Call them \”ML\” and not \”AI\”. Including all ML initiatives within the \”AI umbrella\” oversells and confuses, leading to a high rate of failure for ML business implementations. The term \”AI\”, when used in conjunction with ML, is overly broad and implies human-level capabilities. When you decode the term \”AI,\” it becomes clear that it’s a wildly overused buzzword. If it’s not about artificial general intelligence or a grandiose technology goal, it’s just a bunch of hype.
Page-utils class= article-utils–vertical hide-for-print data-js-target= page-utils data-id= tag: blogs.harvardbusiness.org, 2007/03/31:999.357346 data-title= The AI Hype Cycle Is Distracting Companies data-url=/2023/06/the-ai-hype-cycle-is-distracting-companies data-topic= AI and machine learning data-authors= Eric Siegel data-content-type= Digital Article data-content-image=/resources/images/article_assets/2023/06/Jun23_02_Skizzomat-383×215.jpg data-summary=
They miss out on real-time projects by focusing only on sci-fi.
Source:
https://hbr.org/2023/06/the-ai-hype-cycle-is-distracting-companies?ab=hero-main-text
