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Author: Jane A




Episode 112

By definition an ecosystem brings together multiple products in order to deliver an outcome. However, today’s IoT standards don’t go far enough enable different products to work together. Another layer is needed to ensure ecosystem products speak the same language.
Listen to this podcast (or read the transcript), where I speak with David McCall about the Open Connectivity Foundation and the codebase they provide to enable smart home products from different vendors to talk to each other – exactly what you need for any ecosystem...




Episode 111

No one company is big enough to provide an end-to-end industrial Internet of Things solution. Realizing this the Industrial Internet Consortium (IIC) was founded to bring together different solutions from different vendors to address different use cases. The end game however is not technology, but business – to understand what is needed to put together solutions that not only work well, but sell well.
Listen to this podcast (or read the transcript), where I discuss the IIC with Stephen Mellor to see if this consortium is right for you...




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 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 ...