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FLASHBACK: Publication – Selection of Strategic Authentication and Tracing Programs – Now for Machine Learning and Artificial Intelligence

From time to time, we share here a flashback to a previous post that remains relevant today. This week, we revisit a journal article on “The Selection of Strategic Authentication and Tracing Programs” in the book “Counterfeit Medicines.” The same questions apply to food authentication and also to

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Reliance on Incomplete or Uncertain Data Sets is an Achilles Heel of Enhanced Traceability, Artificial Intelligence and Machine Learning

Can you trust your data? How much do you need to trust your data? What is the error rate in your data set (e.g., credit card companies expect a 1-3% fraud rate)? The answer to these questions is based on how you respond to the findings. There is

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Generative Artificial Intelligence and Chatbots (Some Insight, and  Two “Articles” That Don’t Exist)

Generative Artificial Intelligence (chatbots) is booming. There are opportunities and pitfalls for food fraud prevention. For example, the predictions are based on currently available information. Also, sometimes, the conclusions or results are incorrect, such as a chatbot providing me with citations for two articles that did not exist.

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Excerpt – Data Analytics: The Value of Predictive Models and Enhanced Traceability

Artificial intelligence and machine learning seem to be the new data analytics or big data hype. There’s an assumption that there is ‘enough’ of the ‘right’ data available to make decisions. There is a difference between a ‘model for insight’ and a ‘model for prediction.’ Food fraud is

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