Digital Transformation

Don’t Let Tooling and Management Approaches Stifle Your AI Innovation

Don’t Let Tooling and Management Approaches Stifle Your AI Innovation

It is no coincidence that companies are investing in AI at unprecedented levels at a time when they are under tremendous pressure to innovate. The artificial intelligence models developed by data scientists give enterprises new insights, enable new and more efficient ways of working, and help identify opportunities to reduce costs and introduce profitable new products and services.

AI Evolution Has Similarities to Analytics, But the Differences Are More Important

No Single Tool is Best for the Entire AI Model Life Cycle

Flexibility Helps Win the Talent War

The Cloud Won’t Bring More Clarity

 

The post first appears in Towards Data Science at https://towardsdatascience.com/dont-let-tooling-and-management-approaches-stifle-your-ai-innovation-5fcee5ec8b2f

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Industry 4.0 is closely associated with more automation (compared to the Third Industrial Revolution), bridging the physical and digital worlds enabled by IIoT, Big Data, IoT, cloud computing, cognitive computing and smart factories.

Investing in innovative Industry 4.0 technologies has many advantages. It boosts collaboration between departments, increases efficiency, fuels growth as well as trims costs. Real-time data and intelligence, predictive analytics and IoT machinery helps companies be proactive when it comes to solving and addressing potential supply chain management and maintenance issues. In addition, it makes it easy to optimise and manage all aspects of manufacturing processes and supply chain.

 

 

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