Catalogic ECX and IBM FlashSystem V9000: Software-defined agility

whitePaper | August 30, 2022

Traditional database management systems have become more essential than ever, as data volume, velocity, and variety all increase at breakneck speed. But the harsh truth is that legacy database management systems were never designed for a digital-first business climate shaped by such factors as cloud computing, pervasive mobility, microservices, new data sources, and cloud-native application development.

whitePaper | February 16, 2023

This technical white paper discusses the market trends, use cases, and benefits of Conversational AI. It describes a solution and validated reference architecture for Conversational AI with the Kore.ai Experience Optimization Platform on Dell infrastructure.

whitePaper | December 6, 2019

Machine learning (ML)-driven personalization is fast expanding from social media to the wider information space, encompassing legacy media, multinational conglomerates and digital-native publishers: however, this is happening within a regulatory and oversight vacuum that needs to be addressed as a matter of urgency. Mass-scale adoption of personalization in communication has serious implications for human rights, societal resilience and political security. Data protection, privacy and wrongful discrimination, as well as freedom of opinion and of expression, are some of the areas impacted by this technological transformation.

whitePaper | July 10, 2020

There’s no arguing that preventing failures and accidents is critical for industry. Unexpected incidents can grind operations to a halt for extended periods of time and necessitate expensive repairs. Just 12 hours of downtime for an oil production platform could cost six to eight million dollars in lost production opportunity alone. A single day of grounding for a plane costs roughly four to five million dollars. Because of these disruptions, industrial sectors are always on the lookout for newer, better maintenance methods, and the approach on everyone’s lips right now is predictive maintenance. While everyone agrees on the name, there is less consensus on what it means or how to implement it. But to truly unlock the potential of predictive maintenance, it needs to be paired with artificial intelligence (AI) and machine learning (ML).

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 | September 15, 2022

The concept of Artificial Intelligence (AI) and Machine Learning (ML) dates back to the 1950s with researchers trying to use machines to simulate human intelligence in machines. However, their use in the financial sector has been limited. With enhanced customer service and mounting cost pressures, financial institutions (FIs) have now started to look at AI as a possible solution for improving cost and operational efficiencies.