vkatsuba

Deep walkthrough of Erlang-RED from TADSummit, led by Gerrit Riessen (creator of Erlang-RED), with contributions from Vance Shipley (SigScale Global Inc.), Jonathan Eisenzopf (Talkmap), and Viacheslav Katsuba (Scalicon Inc.), hosted by Alan Quayle. The session demonstrates building a Diameter AAA authorization flow with visual state machines, unit testing, and documentation - making telecom protocols more accessible while leveraging Erlang/OTP’s concurrency and fault-tolerance.

An interview with Vance Shipley (SigScale Global Inc.) and Viacheslav Katsuba (Scalicon Inc.), discussing how Erlang/OTP powers fault-tolerant and massively scalable systems in telecom.

We touched on open source protocol stacks (SIGTRAN, TCAP, CAP, MAP, NGAP, RADIUS, EAP) and briefly on how Erlang could support modern AI-driven use cases.

Erlang/OTP continues to power some of the world’s most reliable, scalable real-time systems - from telecom and fintech platforms to Voice AI and IoT. With built-in fault tolerance, hot code upgrades, and seamless distribution, it remains the go-to choice where uptime and resilience are critical. Companies like WhatsApp, Facebook Chat, Zoom, IBM, Goldman Sachs, Nintendo, and more rely on it to handle millions of concurrent users without breaking a sweat.

Fascinating project! The approach to enhancing the dataset and exploring feature engineering for something as dynamic as Dota 2 must have been a serious challenge, but the results sound promising. It’s inspiring to see machine learning applied to gaming analytics like this—gives a whole new perspective on how we can quantify and predict complex, real-time events. Looking forward to seeing how this evolves!

You're welcome! It was a great read, and I'm happy to share it. Looking forward to more of your insights in the future! Keep up the fantastic work!

I recently came across a fantastic article detailing the journey of building a Dota 2 Match Outcome Predictor using machine learning. The author dives deep into data analysis, feature engineering, and predictive modeling, sharing both successes and challenges along the way. If you're into gaming, data science, or machine learning, it's a great read full of real-world insights.

You can take a look to the interview with Francesco Cesarini https://www.youtube.com/watch?v=-m31ag9z4VY for more details - here is provided a part where compared JVM with a BEAM.

If you want to expand the examples or improve the topic - just leave a comment about it.

This is a good point, thanks! I will extend the topic or maybe will be better to provide new topic as continuation of the current topic - since putting everything in one article can be difficult to understand and will increase the article itself, making it more difficult to read.

yes, they are incredibly useful for development and finding bottlenecks

Pretty interesting!

New topic from Ukrainian Erlanger for Erlang Battleground! In this time we discuss pretty interesting stuff about Erlang/OTP and ASN.1

New rebar3 plugin for spell checking of the source code with Sheldon.

In short - yes, only for fun, but this behavior will be changed in the future - since you are not the first user to ask the same question :-).

Yes! You are totally right :-).

Not sure about the service in the current implementation, but it could be :-).

> I wonder why was Erlang picked and whether it will be offered as a service.

You see in open source exist a lot of spell checkers based on different languages - but in Erlang this is one of the first. In Erlang world already implemented a lot of interesting projects like messengers, chats, writted a lot of documentation where spell checking is need and important. Plus we already create some useful plugin for checking strings, binaries and comments in Erlang projects based on AST - but we will outline this in more detail in the next article, which I hope will be released early next week.

> Also how does it know how to replace "correct" by "misspelled"?

This is future implementation what we will try add into this library - so far this library offers only candidates for replacement. But we are gradually moving in this direction and will be collected more algorithms for it.

Thanks!

The bazinga was added only for fun to keep the spirit of the famous TV series. We have already received some feedback that this is superfluous and not all users would like to see bazinga. For this reason, we have created a ticket and will work on it in the near future so that this behavior can be disabled or enabled through the configuration parameter.