 Hi, I'm Maggie Miller here at IoT World and I'm with Francesco Dodo. He is with ST Microelectronics. Welcome. So you spoke here about embedded intelligence, so tell us what is that? So I see Microelectronics actually focusing a lot on the intelligent nodes, embedded nodes, and today where we came actually with a new tool, it's called STM32QMX.ai. It is basically a way to bring intelligence from the cloud down to the node. And we have some example here that we can show. So typically in the experience of customers or products where you need to bring intelligence into an end product, you always have to capture data, then level those data to meet your use case, then train a sort of algorithms that can do that. And then finally, here is the hard part for an engineer. How do I pour the model that I train in a standard framework, things like TensorFlow and so on, on an embedded node like this guy? So that's where we come with our tool that allows basically to bring the engineering time and efforts down to a single click, bringing algorithms from traditional frameworks and neural network frameworks down to a microcontroller, which is our problem. And I have a demo from here that I can give to you guys. For example, with this simple demo, we can pretend actually to have a letter and you will see here that the system can do character recognition. For example, we had a P letter that was recognized and an I letter and all of this is done straight into the node. And tell us some of the use cases. Perfect. That's a very good question because it brings me to the next demo where now we look at the overall artificial intelligence into the node that brings not just the neural network models or the machine learning running into the node, but it goes up to the cloud. And you see over here in our ecosystem, we're looking into the embedded nodes. So here we get local sensors, right now we're monitoring vibration of two models, collecting those data, bringing through a getaway up to the cloud, and you see here the kind of the diagram. So you see the two nodes over here, the getaway and the cloud. We're able actually to monitor those data in real time. You're seeing actually right now, back in a dashboard running on AWS, the entire data, vibrational data coming from those two models directly into the cloud. How we do that now and why is this unique into this? Because we're bringing together our partnership with AWS that goes straight into our nodes and it's powered either through microprocessor when we go to getaways or microcontrollers when we go directly to the node. Then the power of the sensors allow us to get this information, process them directly at the node and then send only the meaningful information directly to the cloud, so we upload the cloud. And all of this is available to our customers through SDKs, evaluation boards and of course all the ST products that really brings the value to the application. That's great and there's a lot of buzz happening at your booth here at IoT World. It's exciting. So what is your main message? Actually, the message this year that we're bringing over here is how ST allow actually the industries, several industries to meet really innovation. And even if you walk through the booth, you see this kind of layout over here where we have an intersection through different industries, like for example, the industrial world, personal electronics with things like watches or wearable devices, but also the more traditional computer market, all connected with innovation through our products. Sensors, connectivity, microcontrollers and power of course to make sure that everything can be powered up properly. Wow, exciting time. So thank you for sharing all this with us. Thank you very much. Thank you.