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Analytics & AI




Episode 108

Through its different techniques, machine learning allows us to look deep into our IoT data, giving us the hindsight, insight and foresight we need to transform that data into useful information, and ultimately value. But what’s the mechanism to do that?
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....




Episode 107

Through its different techniques, machine learning allows us to look deep into our IoT data, giving us the hindsight, insight and foresight we need to transform that data into useful information, and ultimately value. But what’s the mechanism to do that?
Listen to this podcast (or read the transcript), where I speak with Curtis Seare about the tools and frameworks used to incorporate AI into IoT projects....




Episode 106

Through its different techniques, machine learning allows us to look deep into our IoT data, giving us the hindsight, insight and foresight we need to transform that data into useful information, and ultimately value. But what’s the mechanism to do that?
Listen to this podcast (or read the transcript), where I speak with Vish Pai about the relationship between ML and the IoT platform....




Episode 105

When talking AI in IoT what we’re really talking about is machine learning in IoT, and the one thing machine learning needs above all else, is data. Lot’s and lots of data. Structured IoT data, when piped in properly can be transformed and loaded efficiently for machine learning to create beautiful, and more important, accurate models.
Listen to this podcast (or read the transcript), where I speak with Anand Rao about the symbiotic relationship between AI and IoT...




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 ...




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 ...




Episode 97

The technology of the software-defined product, containing the digital twin, is the most important technology in IoT – the most important because it’s directly related to creating value. Sometimes it can get a bit confusing.
Listen to this podcast (or read the transcript), where I share with you three lessons from the ICIP Technology course. The first, a simple example to demonstrate the software-defined product and digital twin. Then, an overview lesson on standards and protocols, and finally an overview lesson on IoT analytics and big data ...


Analyzing athlete data has been performed in high-level sports for years but it’s only recently that wearables and IoT could be realistically used to deliver useful information to athletes and coaches alike.
Watch this video (or read this transcript) to see Mounir Zok discuss how today’s wearables combined with state of the art Internet of Things technologies are advancing sport ...




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 ...