Why your AI strategy needs more than data

The artificial intelligence (AI) revolution has been underway since about 2016. As a result of great increases in computational power, AI no longer belongs to the realm of media hype and science fiction. Today, AI offers concrete benefits in all areas of engineering, manufacturing, and operations. From deep neural networks and long short-term memory (LSTM) algorithms to reinforcement and physics informed neural networks (PINN), the possibilities are endless, and the real-world applications are only just beginning to truly be exploited. Industry data holds gold nuggets; AI is they key to finding and using them.

[bctt tweet=”In a riverbed of industry #data pebbles, #AI finds the gold nuggets. #bettersolutions” username=”MayaSimulation”]

As companies seek to take advantage of AI, one of the first challenges is how and where to start. By some accounts, as many as 85% of AI projects fail. Many more companies run into problems with their data. Data quantity is important, but so is quality. Having an AI goal is not enough to succeed. Strategy and preparation are key.

We’ve collected insight and advice from our leading experts in applied industrial AI to deliver a no-fluff rundown of what you need to know and do to prepare the right way.

Discover the potential AI holds for manufacturing, and find out how you can maximize AI success and ROI.

Take the first step into your AI future.

Download the white paper today.

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