Episode 109

Convoluted Neural Networks or CNNs are a type of AI typically used in computer vision to process images, but they are also applicable to process the time series data we typically get from sensors in IoT.

Listen to this podcast (or read the transcript), where I speak with Simon Crosby about how these CNNs can be used to make predictions about the future and reduce the massive amounts of data we collect to just the important stuff.

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Episode 108

AI and in particular, deep learning, is a powerful tool for uncovering useful relationships within data; but once found, can’t explain what they mean. Contrast this with humans, armed with tribal knowledge and more traditional analytics, who understand the data relationships but just can’t find as many of them.

Listen to this podcast (or read the transcript), where I speak with Drew Conway about how to find the balance between man and machine when looking for data value.

The post Balancing the Tension Between Informed Analytics and Blackbox AI appeared first on .

Episode 104

Although AI has been around for over 60 years, it’s only been relatively recently that it’s been practical to apply it to real world problems such as those found in IoT. One, because the computational power is now available and two, because vast amounts of data are now available to train it.

Listen to this podcast (or read the transcript), where I speak with Richard Boire about the differences between artificial intelligence and analytics in the context of IoT

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Episode 103

Is it just semantics or is there a real difference between artificial intelligence (AI) and analytics; between machine learning (ML) and AI; between deep learning (DL) and ML, and between analytics and DL? Well, it depends on how detailed you want to go.

Listen to this podcast (or read the transcript), where I speak with Bret Greenstein about using AI in IoT and how it’s different from using analytics

The post Illuminating the Enterprise’s Dark Data with AI in IoT appeared first on .

Episode 89

The digital twin can be hierarchical – representing environments, systems, products and even parts. When digitizing supply networks with digital twins, the network can be a digital twin of its systems, which can be digital twins of their assets, which can be digital twins of their parts which themselves can be digital twins. Sound complicated? It doesn’t need to be. Start at the level of the hierarchy that returns the most value and proceed from there.

Listen to this podcast (or read the transcript), where I speak with Dr. Lane Warshaw and Aaron Parrott about the digital twin and its profound use in digital supply networks

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Episode 88

We’ve discussed the digital twin at length but what is the cognitive digital twin? Is it possible to develop cognitive computing models with our data to endow our digital twin with artificial intelligence? The answer is yes.

Listen to this podcast (or read the transcript), where I speak with Dr. Ahmed El Adl about how this is done and the situations where an AI approach to reaching insights may be better than an analytics approach

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Episode 79

There are two types of manufacturing: discrete manufacturing where the output is physical, countable things, and process manufacturing, where the output is chemistry – think oil & gas. Process manufacturing has been consistently instrumented for over two decades so it is not surprising that they’re a little ahead of their discrete counterparts on their path to IoT.

Listen to this podcast (or read the transcript) with Peter Zornio about IoT analytics in process manufacturing, and his advice is applicable to all industries

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Episode 28

Big Data is big! It’s another entire industry that’s subsumed by the Internet of Things. There’s a lot to consider but it all starts with your business information requirements – what you get by transforming the raw sensor data you collect into business value you can use.

Listen to this podcast (or read the transcript) with Big Data expert Mark van Rijmenam to conclude our seven-part miniseries on analytics by covering the entire array of what’s available

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Episode 25

First it was Big Data and now it’s the Internet of Things; the science of data is becoming increasingly sexy, maybe not Victoria’s Secret sexy but it certainly get the juices flowing for business leaders in the know. Hot or not? Definitely hot.

Listen to this podcast (or read the transcript) with Ajit Jaokar about his passion, data science, and the application of machine learning, deep learning and predictive analytics in IoT

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