High performance computing (HPC) systems have empowered researchers at higher ed institutions to investigate and tackle some of the world's most complex problems for decades. Researchers have turned to artificial intelligence (AI) hardware and software solutions to advance their initiatives for similar duration. In the past, HPC and AI may have coexisted in the same lab, but did not easily integrate with one another. In the past few years, that's changed as these technologies have intersected creating an opportunity for converged HPC/AI platforms where the whole most definitely exceeds the sum of the parts. The result gives researchers access to unparalleled high-performance and acceleration from edge to cloud at every scale, changing the type and amount of science they can accomplish. Today we'll look at converged HPC/AI platforms, why they're critical to the ongoing success of higher ed institutions' research and future grant acquisition, and what to look for in a platform.

Like their commercial counterparts, public sector entities want to extend their infrastructures and operations to the edge. The term "edge" has become overused and overloaded, and few consumers and technologists genuinely understand it in depth. Many fear the edge due to security concerns or the required changes affecting people, processes, and culture. Those that have adopted edge technology have done so in a fashion that limits its benefits. Simply "storing and ignoring" information without insight or passing all data from the edge back to the core or the cloud – where it degrades network performance and may arrive too late to be relevant – undervalues the edge. To fully get their return on their edge investments, public sector entities must implement "the intelligent edge." During this Public Sector Tech Talk, Hewlett Packard Enterprise joins WWT to explore what that means and how to achieve the objective.

The idea of edge computing is that sensor data needs rapid reactions and millisecond-range response times. Edge data sent to the core is used for business insight and immediate action. Core systems need instant operational reaction at the edge. And the cloud is a great place to put transitory workflows and to analyze things that will grow over time. With the number of edge computing devices continuing to grow exponentially year over year, designing IT architectures to capture, process, analyze, and derive deeper insights from that data will be one of the defining challenges of the next decade. And as with most challenges, it also opens exceptional opportunities to drive growth and success. Learn how WWT and HPE bring together hybrid technologies to solve complex problems quickly and efficiently.

As our ability to collect big data increases the need to be able to analyze the data also increases, having a unified high-performance architecture (HPA) under one canopy helps future-proof the enterprise's digital transformation journey. One of the biggest challenges in computing is handling the onslaught of information while still being able to efficiently process it. Only the combination of high performance computing (HPC) systems with their scalability and performance and AI/ML/DL systems with their ability characterize, classify, and learn can we create dynamically-optimized systems. Learn how HPA brings together different technologies to solve complex problems quickly and efficiently.