AI Podcast Interviews Articles and Reports

As a business practice, model development aims to create a dataset, tailored through machine learning, that can accurately predict outcomes or classify data based on input variables. By following a structured approach, developers can ensure that the model development process is efficient, effective, and reproducible.

Traditionally, responsible AI management practices are not just a matter of theoretical ethics debates but a practical matter of compliance. Financial sectors are highly regulated and monitored to ensure the safety and security of consumers and the overall economy. Many of those regulations are written so that responsible management practices are meant to avoid penalties. 

From work-from-home policies and digital-first communication with prospects – the COVID-19 pandemic dramatically accelerated many trends already in progress for businesses and consumers. Among sales teams, digitally enabling buyer journeys became a must-have almost overnight.

Knowledge graphs have grown into a major trend in life sciences since the term was introduced by Google in 2012. However, despite this recent uptick in use, they significantly impact the space. Knowledge graphs enable several critical functions within life sciences, including drug development, literature review, and regulatory reporting.

While the steel industry may not be synonymous with AI adoption, steel manufacturers are not different from any other business in ensuring efficiency in their output and throughput. There are almost certainly opportunities for AI implementation across an industry worth hundreds of billions of dollars that currently lags behind in adopting AI technology.

COVID-19 did not just bring waves of diseases and contagious variants across the world starting in early 2020 – a tsunami of fraud soon followed the broad sweep of a pandemic that would engulf the global insurance industry. 

Episode summary: In this episode, we speak with Alan O'Herlihy, Founder and CEO of Ireland-based Everseen. Alan speaks to us about how machine vision systems can be used to detect theft or mistakes at a checkout counter (including forgetting to scan items, customers intentionally hiding items, and more). Alan not only explains where these technologies are in use today, but he also breaks down some of his own predictions about what these computer vision systems might make possible in the workplace of tomorrow.

As AI automation (aka, “intelligent automation,” or IA) in financial services quickly becomes mainstream, it attracts increased stakeholder interest as firms explore the possibility of unlocking value via increased efficiency, cost reduction, and enhanced predictive capabilities.