RUG::B

One of first steps in learning a programming language is discovering how to debug that pesky issue in the middle of our program. Why the code execution isn't entering my if statement? What is the value of my_variable? Why Ruby, whyyyy???

Some developers are happy to debug by just puts'ing their way to the solution, others like to poke variables in a REPL or debug frames step by step. All in all, debugging is a means to an end: getting your code to work as you've expected.

In this talk we aim to first clear up some misconceptions about debuggers and understand what is available for us in the Ruby ecosystem. In the Ruby 3.1 release, there are improvements to the "debug" gem with a lot of nice features that might make you reconsider doing step debugging again, in case you aren't already.

As a fellow "throw a pry here and there" debugger, I was impressed to see all this progress happening and hope you'll too!

In this talk, we explore how AI works under the hood. We start with the basics of artificial neural networks, and then speedrun through all the major types of architectures used for different tasks, such as computer vision, speech recognition, and natural language processing.

No previous machine learning knowledge is assumed. We will try to cut through the hype and the jargon to show how things actually work.

Given the limited time, the aim is a high-level understanding of the models. Hopefully, this will give you enough information to decide for yourself whether to delve deeper, or to sit this one out.

Extension and partial summary of my Stories in Open Source talk. Extended with new parts, old parts will be summarized.

New stuff mostly looks at part of the burden of Open Source and the Open Source // Life Balance.

Last minute editions have last minute talks 😅