Computer modeling and artificial intelligence (AI) are two technologies that were expected to help the pharmaceuticals and biotech industry provide solutions to new and emerging diseases. Storage performance and data management are key to the effectiveness of both of these capabilities.

Find out how storage architectures and technologies supported the quest for a COVID-19 vaccine and what we can learn from these experiences. 

Data acquisition, storage, and analysis is a critical aspect of the design of self-driving systems for autonomous vehicles (AVs) - the amount of data acquired is a critical advantage for companies building these vehicles.

Hear about the latest in how today's storage technologies are enabling the latest in data capture and analysis for AVs. 

Social media companies must store extremely large amounts of data for very long durations, while being responsive to users, and economical.

Learn how these companies utilize "off-the-shelf" technology to address these challenges. 

NVMe-oF will be seven years old as of September 2021. Most storage companies, analysts, and NVMexpress.org (the parent organizations for NVMe and NVMe-oF) say that NVMe-oF is "the future", yet the number of production implementations is faily small. Where is NVMe-oF today, and what does its future look like? 

The conventional wisdom for hosting applications in datacenters has been to run them across thousands of virtual machines (VMs) and virtual storage devices (VLUNs) to simplify datacenter resource management and improve application resiliency. Computational storage, where the storage devices perform all or part of the computational workload, has been proposed as a more optimized alternative, especially for highly parallel applications. Does computational storage deliver these benefit, and how does it compare to conventional approaches. 

A variety of approaches have been proposed for storing data for artificial intelligence (AI) and machine learning (ML) applications, including both centralized storage (storage arrays) and distributed storage.

Hear about the strengths and weaknesses of each of these approaches from experts on the implementation of AI systems, and which types of AI workloads benefit from each approach 

Modern business intelligence systems utilize high-performance server configurations to produce rapid analysis of critical business data. Two of the most promising approaches for business intelligence are hyper-converged infrastructure (HCI) and composable infrastructure (CI) clusters.

Join experts on both of these architectures to understand the advantages of each approach for business intelligence applications. 

Many cloud service providers start their business utilizing "public cloud" compute and storage resources to run their applications, but look to build their own datacenter as their business grows and the cloud becomes expensive.

This webinar will look at what the key factors are in driving a decision between public cloud, a private datacenter, or a hybrid approach for cloud service providers. 

At the intersection of artificial intelligence, petabyte-scale storage, and cutting-edge computing is radiometry, the study of millions of medical images to speed up the time to diagnosis of cancers.

This webinar will explore the various storage architectures and data management tools necessary to keep up with the growth in high-resolution imagery for radiometry. 

Join G2M Research and a panel of industry experts to discuss the major enterprise storage tends, innovations, events and happenings of 2021, and what to expect in 2022.