Artificial Intelligence Starts with Data
Many are talking about artificial intelligence (AI), myself included. AI holds promise for organizations in every industry and every size. Some of the challenge today is how to prepare for AI in the organization and how to plan AI applications when there is a dearth of relevant case studies.
The foundation for AI is data. You must have enough data to analyze to build models. Your data determines the depth of AI you can achieve — for example, statistical modeling, machine learning, or deep learning — and its accuracy. The increased availability of data is the single biggest contributor to the massive uptake in AI where it is thriving.
Improving Analysis with AI
If you are optimizing a restaurant supply chain, you want to know how much of each food item to stock and how many prep items to prepare in each restaurant daily. You decide this based on anticipated sales in the restaurant. Forecasting can be done with standard time-series analysis on historical sale snapshots, but if you want more accuracy, you could use machine learning or even deep learning methods, both of which need more data.
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