Understanding the AI factory
In Competing in the Age of AI, the authors introduce the concept of the “data pipeline,” a set of components and processes that consolidate data from various internal and external sources, clean the data, integrate it, processes it, and store it for use in different AI systems. What’s important, however, is that the data pipeline works in a “systematic, sustainable, and scalable way.” This means that there should be the least amount of manual effort involved to avoid causing a bottleneck in the AI factory.
Iansiti and Lakhani also expand on the challenges involved in the other aspects of the AI factory, such as establishing the right metrics and features for supervised machine learning algorithms, finding the right split between human expert insight and AI predictions, and tackling the challenges of running experiments and validating the results.
See the full story here: https://bdtechtalks.com/2020/12/02/competing-in-the-age-of-ai/