Artificial Intelligence In Imaging Applications And Use Cases

How will AI and analytics change life in the next 25 years? In this episode, we look forward to the next 25 years and will share predictions about the technological innovations prevalent then based on a projection of AI and analytics forward.

Are you using Google's TensorFlow framework to develop your deep learning models? And are you doing inference processing on those models using Intel compute devices: CPUs, GPUs, VPUs and/or HDDL (High Density Deep Learning) processing solutions? If the answer to both questions is "yes", then this hands-on tutorial on how to integrate TensorFlow with Intel's Distribution of the OpenVINO toolkit for rapid development while also achieving accurate and high performance inference results is for you!

To navigate today's everchanging business environments requires agility, efficiency, and innovation. So, it's no surprise that companies both big and small are hungry for greater automation and intelligence. The ability to easily find, capture, and share knowledge throughout an organization has become paramount.

The world is moving from operation to automation and not only in factories. AI is here to revolutionize the way the world around us acts and responds to our actions. AI at the edge is about bringing the intelligence where the action is. This session will talk about why AI at the edge is so important. But also we will talk about how to scale AI at the edge and move it from the lab into real full-scale deployment. At the end of the day, it is all about software (intelligence) and data. To combine Software and Data in ways that can support multiple use cases, we need to think of modularity, and this is where microservices are important. We will discuss how microservices are the building blocks that will let the developer create any use case they want to.