You tap, you swipe, you enter your pin, what happens next? Let’s unpack the blackbox of money movement, starting with card networks - our most frequently used tool in North America.

Does anyone have a good story for transitioning from a monolith to microservices? Well with some careful planning you can.

LLM’s have brought AI to the general public and impressed. However, understanding how transformers unlocked this opportunity is fundamental to understanding the challenges that still remain to be solved.

Over the last decade we saw several companies document their grueling transitions from monoliths to Micro Services and the success it brought about. As a result, every company saw being on Micro Services as the right infrastructure. But is it always the best move?

AI is a catch all term for all computer learning techniques, even if Neural Networks dominate our perception of what IA is. But NN’s are not the only answer to every AI problem, they also aren’t even the primary algorithm for most applications of AI we use today.

“We don’t know what it is doing or how it arrives at the decision it does.” This statement has been espoused often when researchers, companies, and engineers describe their deep learning models. It seems paradoxical: How can we create something where we can’t describe its function?