Research Proves IT Transformation’s Persistent Linkto Agility, Innovation, and Business Value

whitePaper | January 12, 2020

“The services market for artificial intelligence technologies is rapidly maturing on the back of several years of learning and a realization—delivering AI is unlike delivering any other technology thus far. Delivering on the promise of AI calls for far more collaboration between service providers, tech vendors, and enterprise clients.” The biggest differentiator in enterprise AI services, as described by most of the customer leaders, is the quality of people—not just the quantity available for a specific skill. Domain understanding and data engineering capabilities are top priorities. A culture of innovation, experimentation, collaboration, and co creation with customers is the key winning formula here.”

whitePaper | August 10, 2020

Data is the most important asset businesses have. As the world has become increasingly digital, data has grown in volume and value. In fact, this most valuable resource of modern society doubles in volume every year and that growth rate is likely to accelerate even further. Of course, this creates a challenge: how to store data securely and how to be sure that every operation with data is secured? Today loss of data means loss of everything: business, identity, future, and even life in some cases.

whitePaper | September 29, 2021

Penguin Computing’s Analytics Practice acts as a single point of reference for hardware, software, architectural design, and much more, enabling organizations to focus their energy on their AI projects. Access this white paper to learn more about this secure, end-to-end solution designed to alleviate AI infrastructure woes.

whitePaper | November 23, 2022

The modern distributed workplace—including enterprises with thousands of branches and remote workers—requires updated approaches to cloud, networking, and security infrastructure. Cloud migration has opened the door to a huge increase in sophisticated applications, requiring networks that can carry traffic to an increasingly remote workforce. In turn, this creates a unique set of new requirements for security, including special capabilities to handle unpredictable locations of users, applications, and traffic flows.

whitePaper | January 20, 2022

Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there is an increasing interest in developing neural network (NN) solutions to deploy them on low-power edge devices such as the Arm Cortex-M microcontroller systems. To enable that, we present CMSIS-NN, an open-source library of optimized software kernels that maximize the NN performance on Cortex-M cores with minimal memory footprint overhead. We further present methods for NN architecture exploration, using image classification on CIFAR-10 dataset as an example, to develop models that fit on such constrained devices.

whitePaper | August 10, 2020

2020 has posed significant, unexpected challenges to the world – and to IT departments in most organizations. Work practices have shifted rapidly and, given the volatile economic climate, many organizations are looking to protect against uncertainty and ensure business continuity by implementing cost savings initiatives. As an IT leader, you and your team are uniquely positioned to deliver added value to the organization by leveraging Technology Intelligence data to find these additional cost savings opportunities.