Tim Berglund

Up until early 2023, I regularly said AI would always have a bright future—and I didn't mean that as a compliment. Sure, deep learning had made us good at building very impressive classifiers in the decade or so prior, but for so long, human-like intelligence was just five years in the future—and that made me a skeptic. Things are different now, but how much skepticism is still warranted? What is it that we've got on our hands? What changes is modern AI bringing with it? Like with so many other questions, the answers are easier if we understand where we've come from. Beginning with the Turing Test itself, the famous Dartmouth Conference of 1956, and the Perceptron of 1957, we'll trace decades of disappointment and broken promises as we tried to realize the true potential of computing, at the same time grasping for an understanding of what it means to be human. Taking a close look at various technologies along the way, we'll arrive in the 21st century, the revival of neural networks, the advent of the Transformer, and a revolutionary new technology category that has prompted oracles of weal and woe from our most optimistic and apocalyptic technology prophets. Standing on the edge…

Data professionals and software developers of every stripe are increasingly moving into the world of real time, streaming data. There's no question that this is our future, and that its promises are already being realized, but how did we get here?

When things get a little bit cheaper, we buy a little bit more of them. When things get cheaper by several orders of magnitude, you don't just see changes in the margins, but fundamental transformations in entire ecosystems.

You were using Apache Kafka on premises a few years ago and have been happily building applications with it since then. But now it’s well past time to move to the cloud, and you'd like to refactor your first application to something that feels more native to the cloud.

It has become at truism in the past decade that building systems at scale, using non-relational databases, requires giving up on the transactional guarantees afforded by the relational databases of yore, ACID transactional semantics are fine, but we all know you can’t have them all in a distributed system.