There’s a term circulating in mortgage technology conversations that deserves a closer look: AI-native. The implication is that companies built entirely in the AI era have a structural advantage over established platforms. If you didn’t architect your foundation around artificial intelligence from day one, the argument goes, you’re playing catch-up. That assumption warrants a closer

Fanatics Betting and Gaming (FBG) built a multi-agent customer support system on AWS to solve a challenge unique to sports betting. Customers expect instant, accurate answers, especially during live events when every minute counts. Customers ask about account issues, deposit limits, state-specific regulations, and responsible gaming resources. The rules vary across every jurisdiction where an

Montreal has long been a global AI hub, anchored by pioneers like Yoshua Bengio and institutions such as Mila – Quebec AI Institute, one of the world’s leading centres for deep learning research. Out of that ecosystem, BrainBox AI emerged in 2017, co-founded by Jean-Simon Venne and Sean Neely with the goal of applying autonomous

By Max Darrow is an Emmy award winning reporter/MMJ for KPIX 5. He joined the KPIX 5 news team in July 2021. Read Full Bio August 19, 2026 / 6:07 PM PDT / CBS San Francisco Add CBS News on Google AI is everywhere these days, especially in the Bay Area. Advertisements are on billboards

Written by Coursera Staff • Updated on Aug 20, 2026 Learn about AI boot camps, including what they are, how they compare to other learning options, and the skills you can learn to support your career goals. Key takeaways An AI boot camp is an immersive, hands-on program that lets you learn the latest AI

For decades, breast cancer screening has largely been guided by age. But advances in artificial intelligence (AI), growing recognition of individual risk factors and ongoing debate over screening recommendations are accelerating a shift toward a more personalized approach to early detection. While professional societies continue to differ primarily on screening intervals and, in some cases

Announcing a new article publication for BIO Integration Accurate localization of anatomical landmarks is crucial for clinical diagnosis and treatment assessment. However, existing Convolutional Neural Network (CNN)-based methods may result in global spatial information loss and consequent localization failures in the presence of complex anatomical structures or parenchymal abnormalities. Therefore, a method capable of modeling

New UTulsa faculty member Mohammed Meysami uses mathematics to make artificial intelligence more trustworthy and reliable. While AI can analyze data and answer questions quickly, it often does not explain how it reaches its conclusions or how confident it is in its answers. Meysami is creating mathematical frameworks that allow AI to estimate and report