- November 9, 2018
- Posted by: admin
- Category: Uncategorized
The Internet of Things, expected to grow exponentially over the next half decade, will generate the essential data that AI systems need to automate industry, says Schneider Electric Chief Digital Officer Herve Coureil.
IoT convergence- AI will get essential data to automate industry from IoT,Schneider Electric Chief Digital Officer Herve Coureil tells TechRepublic’s Dan Patterson. The following is an edited transcript of the interview.
Dan Patterson: Artificial intelligence is your core competency. There is possibly no term that has been more hyped over the last, say, 18 to 36 months than AI. Before we get into the details, let’s start by defining our terms. There are a number of phrases we use to describe artificial intelligence, including machine learning, predictive analytics. Help us understand when we talk about B2B AI, what are we really talking about?
Herve Coureil: We’re looking at the convergence of a number of trends. If we look at our sales, it’s really a convergence of IoT on AI actually that’s particularly interesting, because we’re using a lot of machine data and so forth to do predictive analytics on some overuse cases based on AI, essentially machine learning, but we use of course a few other forms of AI.
I would say a common denominator probably. We look at very narrow and specific form of AI. We’re looking at solving very, very specific and well-defined problems that are actually essentially customer programs. We’re not in the business of doing platform type AI capabilities like voice, for instance, or vision. We are partnering, of course, with some of the large cloud vendors for that, but we really develop algorithm that makes sense for our customers, that makes sense from the perspective of our value proposition, which is a value proposition of safety, reliability, efficiency, and sustainability in the world of energy management on automation, so really solving customer problems, then trying to apply in the wide varieties of AI algorithm that exist, the algorithm that would be best fit to address that particular issue or problem.
Dan Patterson: We’re not talking about the speculative artificial general intelligence. You live in the land of business and practical artificial intelligence. Before we have a longer discussion about the Internet of things, let’s start with a cliché. “Data is the new oil.” Okay, IoT sensors will be placed, are already being placed, on nearly every piece of machinery everywhere, every type of business. But let’s get specific. What industries are most impacted by the rise of IoT, and what industries feed the best, most productive data back into predictive analytic systems?
Herve Coureil: From our perspective, we see many industries being really super interested on active in VIUT, on VIUT front, especially every industry that has some mission-critical processes, where you do want zero downtime. You want to be able to do your maintenance predictively and so forth.
Dan Patterson: So critical infrastructure.
Herve Coureil: So critical… a critical process, a critical infrastructure whether it’s in a factory, whether it’s in other sorts of infrastructure is usually for us the starting point. If you have to run something that’s really critical, stepping it, downtime is expensive, then you know you’re looking at sensors. Then you’re looking at capturing those data. Then you’re looking at what do you do with it and what kind of algorithm makes sense in order to extract the right insights, and more important than the insights, right actions. That’s where you have that interesting intersection that that burns on the edge, as we say today, on IoT on AI.
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Article Credit: TechRepublic
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