Successfully Evaluating AI Models in Industry

An interesting article from University of Delaware:

“A new approach to artificial intelligence that builds in uncertainty.”

AI workers are combining the best of both worlds. Deterministic models based on scientific understanding of processes and statistical models, to create more accurate and precise probabilistic models.

The model itself identifies what data are needed to reduce model error and helps to identify the most productive areas for further work.

Researchers, manufacturers and suppliers producing AI models for improved control of industrial processes will increasingly compete based on the accuracy and precision of their models.

Using rigorous methods, PCA can assist industrial sites to evaluate complex models coming from equipment and chemical suppliers.

As McKinsey & Co. says, “The Fourth Industrial Revolution is Happening Now in Manufacturing.” The winners will be those who act now and are successful at making the incremental improvements in performance.

When modelling our world, we use observations, thoughts and concepts. But, be aware that these are only our approximations to reality, not actual reality!

 

A new approach to artificial intelligence that builds in uncertainty, October 19, 2020, University of Delaware

Modelling and Observing Reality in an Uncertain, Interconnected World, September 19, 2020, PCA

The Fourth Industrial Revolution is Happening Now in Manufacturing

Over-Reliance on Expert Intuition

The Risks Associated with Predictive Models – What We All Need to Remember: We Can’t Predict Everything!

 

Broken robot

Using rigorous methods, PCA can assist companies to successfully implement AI process control models

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PCA is the independent technology service assisting industry to improve process, chemistry, productivity, sustainability. For Chemicals, Mining, Paper, Metals, Alumina, Food, Utilities, Retail and other Industries.

With PCA's Core Trust Design, processes, chemistry, equipment and control strategies are assessed in an impartial, objective manner using industrial process and chemistry knowledge, the industrial site's own data and "statistical thinking".

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