ARTIFICIAL INTELLIGENCE:FUELING THE NEXT WAVE OF THE DIGITAL ERA

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 | 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 | December 22, 2022

Contact centres are often viewed as cost drivers rather than business drivers. This is understandable, when you consider that differentiation efforts in this space have often struggled to be sustainable from a cost or staffing perspective. Figuring out the formula of investment to increased income is helped when you have an experienced guide to shorten your journey. Read on to get the benefit of our two companies’ experience, multiplied by hundreds of clients.

whitePaper | October 11, 2021

AI forms the bedrock to help organizations unlock business value from the deluge of unstructured information. Improving operational efficiency by extracting structured data from unstructured documents enables organizations with faster and contextrich decision-making to adapt and thrive in the new normal.

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 | 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.”