How to define, describe & think about IoT

There is no doubt that IoT is here to stay, mainly in areas such as manufacturing and transportation where there are clear benefits to connecting devices such as energy efficiency. Industrial IoT (IIoT), in particular, is being increasingly adopted as early adopters have successfully used the technology to remove inefficiencies, prevent errors, and optimize yields with real-time adjustments. …

Here is one model to think about how IoT projects can grow in complexity, and correspondingly, value: the IoT Extensibility Framework, taken from The Amazon Way on IoT. This describes four increasingly complex levels of IoT projects.

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#iot, #strategy

Creating the Intelligent Asset: Fusing IoT, Robotics, and Artificial Intelligence

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#iot, #robotics, #videos

The Artificial Intelligence–Powered Pivot to the Future

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#strategy, #videos

AI Knowledge Map: how to classify AI technologies

Multiple classifications, distinctions, landscapes, and infographics exist to represent and track the different ways to think about AI. However, I am not a big fan of those categorization exercises, mainly because I tend to think that the effort of classifying dynamic data points into predetermined fix boxes is often not worth the benefits of having such a “clear” framework (it is a generalization of course, cause sometimes they are extremely useful). …

This article in principle targets both people who are starting in AI to give them a broad sense of what is out there, as well as experts and practitioners who are experimenting with these technologies for a while (with an explicit request to send me feedback on how you would structure it or other technologies that should be captured by AI spectrum).

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#artificial-intelligence