Bringing real-time AI to the Edge
The advent of cutting-edge technologies like artificial intelligence (AI) and edge computing has tremendous potential to enable faster decision-making via direct machine to machine (M2M) communication in an effective way without the necessity of a centralized hub.
Besides, the mix of these two technologies that is AI at the Edge helps to deliver real-time analytics, make fast decisions based on insights, create new business models and deliver better results.
AI at the Edge means running AI algorithms locally on a hardware device using edge computing. These algorithms are based on the data generated on the device itself which helps organizations to process data with the device and provides the required information in real-time.
“Edge AI Software market is forecasted to grow from $355 million in 2018 to 1.12 trillion dollars by 2023.” – Forbes
In this webinar, our experts will talk about how AI at the Edge can help companies to process huge amounts of data at the device itself instead of AI processing done in a cloud-based data center with deep learning models. You will get to know how it offers speed, agility, security and intelligence in operational functions. They will also talk about advantages of having AI at the Edge and how implementing it can transform any industry.
- What is AI at the Edge
- Why AI at the Edge is a game-changer
- Applications of AI at the Edge
- Industrial use cases for accelerating AI at the Edge
- What is the roadmap to achieve AI at the Edge?
- Q & A