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Episode 110

AI today is getting better at learning. In fact, learning is what differentiates what we call AI from advanced analytics. Machine learning algorithms minimize an error function by autonomously and iteratively adjusting their model variables. But what’s next for AI and machine learning?
Listen to this podcast (or read the transcript), where I speak with James Canton to hear predictions on where the predictive technology of machine learning will go in the Internet of Things....




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....




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....




Episode 107

If you’re like me, before I started digging into AI, it all seemed so mysterious. Not only how it worked but also how it was put to work. But when thought of as a subset of analytics things come into focus – fast.
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 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 99

In my view, delivering outcomes is IoT’s killer app. It requires the IoT platform, its technical underpinning, and the IoT ecosystem, its business underpinning, to come together in just the right way.
Listen to this podcast (or read the transcript), where I share with you three lessons from the ICIP Strategy & Digital Transformation course. The first is an overview of outcomes, also one of the major drivers of every IoT strategy. Then a digital transformation lesson on marketing and finally, an important methodology that should always be employed when starting an IoT offering – Design-Sell-Build ...




Episode 98

Business is all about creating value and then monetizing it; and it’s no different in IoT. For companies to succeed in IoT, both value creation and value monetization must be mastered.
Listen to this podcast (or read the transcript), where I share with you three lessons from the ICIP Business course. The first, an overview of the value creation framework, that walks through the four types of value creation in IoT. The next lesson is on one of the five classes of business models used in IoT – the Service business model. And the third lesson is an overview of risk management – the business counterpart to cybersecurity. This episode is a lot shorter than last week’s but packs a big punch ...




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 ...