Google's AlphaGo is an extraordinary breakthrough for Artificial Intelligence. The game of 19x19 Go has 1.74×10^172 unique positions and is about a 'googol' times harder to calculate than chess. Experts thought it would take at least another decade before AI would be able to beat the best human players. So how did Google tackle this problem? What algorithms did they use and how do they work?...

But as we embrace these new technologies, we must also ask ourselves: Are we becoming less capable of thinking for ourselves? Do these tools make us smarter, or do they risk dulling our critical thinking skills? This talk will encourage us to think critically about the role of AI in our education. Together, we will discover how to use AI to support our learning journey while still developing our ability to think critically....

Nowadays, most software projects are distributed systems: components are located on different networked computers which communicate and coordinate their actions by passing messages. Debugging distributed systems is not easy. When two components don't play nice together, the cause could be virtually anything: software, DNS, routing, firewalls, proxies, load balancers, TLS.. and more! In this talk, I'll share my experience with debugging distributed systems. We'll look at typical issues and share ways to debug those issues and find their root causes. We'll dive into networking, infrastructure, logging/tracing/metrics, testing, remote debugging and more. I'll share lots of examples and war stories along the way. After this talk, you'll have practical knowledge on how and where to get started with debugging distributed systems yourself!...

Last January a challenge was posted online by Gunnar Morling: How fast can you parse a file with one billion rows of weather data using Java? Little did I know this deceivingly simple question would lead me down a path that taught me all about: parallelism, memory mapped files, SWAR techniques (SIMD as a register), bit twiddling, branchless code, mechanical sympathy, Graal native compilation and finally... I even turned to the dark side: using sun.misc.Unsafe. Join me in this deep dive where I'll explain all the code changes and tricks that took me from the reference implementation which processes the billion records in less than 4 minutes, to processing everything in under two seconds. Who knew Java could be _this_ fast?...

Arthur C. Clarke once said: "Any sufficiently advanced technology is indistinguishable from magic" The first time I used Shazam (the music matching app) it felt just like that: pure magic. The app shortly listens with the microphone and tells you which song is playing. As a programmer I generally have a pretty good understanding of what happens behind the scenes, in this case, however, we were absolutely gobsmacked. After a weekend of studying, reading scientific papers and experimenting and coding: we had a working Shazam clone written in Java. During this talk, we'll reveal what we've learned and what algorithms and tricks are being used....

How to verify your Kotlin project in a Kotlin way? I am talking about test coverage and about style linter. Wouldn’t it be great if we can really use Kotlin in the full spectrum and use tools that support those features? Of course, we would also like to check our code with a linter. In Java we have multiple ways to do that, but with the specific Kotlin format, we are in need of a new linter and formatter. Ktlint (spoken as kitty-lint, for the cat-lovers among us) is the perfect plugin to fit your needs. Most of us will know or even use test coverage engines like Jacoco or IntelliJ. An advantage of this is that it’s well known and considerably solid. The disadvantage is that it doesn’t support all Kotlin features, like a Kotlin directory structure. Because of that you have to choose to OR don’t use the Kotlin directory structure, OR pick a new test coverage engine. This is where Kover comes in. In this talk I will go over both plugins to see what the advantages are, how to configure them, and to determine which child-diseases are still there....

In this talk we’ll look at learning a new language from a Linguistic and Neurological perspective, while at the same time looking at how we can apply this in the IT setting we work in. At the end of this talk you will know how your brain stores new information and how that information can be retrieved and used. Next to that you will be given some practical tips and tricks on how to improve your own learning curve and how to help others support others who are in the process of learning. As a previous speech-and-language therapist I would like to give you a better understanding of how we learn languages and how this knowledge can help us in the never-ending changing world of software development!...

We’ll also cover how to structure your coding sessions using the primary–recency effect. Along the way, you’ll get actionable tips for boosting focus and leveraging downtime. Whether you’re learning a new Java framework or mastering advanced concepts, you’ll walk away with science-backed tips to learn smarter, code better, and stay ahead....

How do quantum computers work? What is a qubit? What the hell happened to Schrödinger's cats? During this talk we'll together unravel the mysteries of entangled qubits. We'll explain the basics of quantum computing in simple and fun ways, including visual demonstrations with polarizing filters and a skippyball (known as Mr Qubit). We'll even build an actual working quantum computer.... tribute, a simulator, in Java! And I'll explain how larger quantum algorithms work by explaining the quantum benefits in Shor's Prime Factoring algorithm. But beware, this talk isn't for the faint hearted. We'll keep away from all the unnecessary complicated math, but if Math.random() is unlucky we might kill some more cats....

In software design and software architecture, we often face the question: should we build this generic or specific? Usually, this is not an easy question to answer. The answer depends on a lot of different factors, including future factors you may not be aware of - yet. In this talk, I'll share my experiences and thought process as a developer and software architect with choosing between generic and specific solutions. I'll talk about generic vs specific design & architecture, both on a project level and organization level. We'll look at sharing code/components between teams, inner source culture, monorepo's, microservices, lifecycle management of generic components and strategic design as a tool to help decide. After this talk, you'll have practical insights that can help you to choose between generic and specific solutions yourself....