AI on the edge: solving enterprise challenges with embedded machine learning - Seguridad Mania.com - España y América Latina

As AI dominates the tech stage, the intersection of Internet of Things (IoT) and artificial intelligence is taking up more of the spotlight. From AI-powered healthcare instruments to autonomous vehicles, there are many cases where artificial intelligence can be used and benefited from on edge devices. However, building an end-to-end architecture to enable such a solution comes with different challenges to other AI stacks, both in training models and in deploying them to the edge. ## Open source at the edge Open source solutions enable edge devices in different ways. From operating systems to ML platforms, enterprises can choose from a wide variety of solutions. This abundance of choice can be overwhelming, leading to organisations delaying decisions and not scaling their AI at the edge initiatives. Join this webinar about AI at the edge Join Andreea Munteanu, Product Manager for AI, Steve Barriault, VP of IoT Field Engineering and Alex Lewontin, IoT Field Engineering Manager, to discuss AI at the edge. During the webinar, you will learn: - The main challenges rolling out AI at the edge and how to address them - How to secure your ML infrastructure, from the data centre to the edge - Key considerations to start and scale your ML embedded projects - Benefits of running AI at the edge - Common use cases and how to get them started quickly - Role of open source in the Edge AI space