This article provides guidance on how organizations can successfully implement AI by identifying the right problems, finding solutions in complex contexts, and prioritizing projects for maximum benefit.
While AI has the potential to solve major problems, organizations embarking on such journeys often encounter obstacles. They include a dearth of high-quality data; too many possible solutions; the lack of a clear, measurable objective; and difficulty in identifying whether a proposed solution is “good.” In tackling these issues, Google DeepMind, Alphabet’s AI lab that is striving to solve extremely challenging real-world problems, has come up with solutions that can benefit others.
It also offers guidance in choosing which opportunities to pursue after potential projects have overcome those hurdles.Artificial intelligence has witnessed a remarkable surge, captivating researchers, product teams, and end users alike with its transformative potential. But despite its recent popularity, AI is only successful in solving problems with very specific features. In this article, we offer guidance to help organizations identify the right problems to address with AI, to find solutions when the context does not perfectly align with what AI is best at solving, and, after potential projects have overcome those hurdles, to choose those that can offer the largest benefits for business or for broader society
Artificial Intelligence AI Implementation Problem Solving Data Science Google Deepmind
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