Detecting the human face is a difficult problem that is faced by experts in the computer vision field. The main reason is because the human face is a dynamic object in which there is a high degree of variability as every face is different.
Computer vision impacts every aspect of our life whether it be a doctor’s visit, driving yourself to work, or using an Instagram filter on your smartphone. The pandemic and the rollout of 5G technology have been catalysts for the implementation of more computer vision technology, namely driverless cars and other IoT applications.
BFSI is one of the industries where AI/ML is causing significant upheavals in 2021 and beyond. Despite the pandemic, interest in AI and ML implementation has been resilient. According to a survey conducted by the Bank of England, around 40% of respondents said that the relevance of machine learning for future operations has increased, with 10% of institutions on a significant rise. The relevance of machine learning has not decreased at any of the banks. The financial sector is heavily utilizing artificial intelligence and machine learning to automate and simplify processes.
Machine Learning algorithms are based on large amounts of data that need to be processed for the algorithm to learn. GDPR requires companies to comply with regulations that will secure consumer data. But questions have been raised about how this regulation will address automation in analytics as the AI and machine learning market grows. GDPR outlines six data protection principles, and according to Norwegian Data Protection Authority, AI is facing four of them.