Certifying Fairness of AI-Applications An Impossible Task?

whitePaper | October 18, 2022

If you have worked in lending for even just the past year, you have already experienced its cyclical nature. Take mortgage lending, for example. Less than a year ago, the main problem facing mortgage originators was how to process high volumes of applications while still observing regulatory compliance and conformance to underwriting policies.

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 | December 29, 2022

In our modern world, taking advantage of Artificial Intelligence (AI) to gain insights from data is becoming more prevalent day by day. Graphical Processing Unit (GPU) systems use multiple cores to perform parallel processing, running select workloads to decrease processing times. Compared to GPUs, Central Processing Units (CPUs) have fewer cores; previously, this resulted in less capacity for parallelized processing. To move beyond this limitation, Intel has released new hardware that runs typical AI mathematical computations more efficiently on the CPU, and has also released libraries with hardware optimizations that enable an additional increase in performance.

whitePaper | November 29, 2022

Artificial intelligence has long since graduated from science fiction and speculative use cases to widespread and diverse development across fintech sectors. CB Insights reported that financings for AI startups showed continued robust activity through Q2 2022, despite changes in market sentiment from the exuberance of 2021.

whitePaper | June 7, 2022

Telecoms need to be able to incorporate new technologies and next-generation connectivity such as 5G to customers and end users. To achieve these ambitious goals, they need to optimize their networks – make them more intelligent if you will. Some of the tools needed include artificial intelligence (AI), machine learning (ML) and artificial intelligence operations (AIOps). This document will explore what intelligent networking means to telecoms, vendors and customers, and how AI and ML technologies and tools can be used, the cultural shifts the industry needs to make it a success, and what to bear in mind when deploying machine learning across a telecom network.

whitePaper | February 17, 2022

Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data.