Navigation in a 3D environment with RL & Event deduplication in Kafka

Agenda:

18:00-18:30 Navigation in a 3D environment with Reinforcement Learning (Predrag Njegovanovic)
18:30-19:00 Event deduplication in Kafka (Vladimir Vajda)
19:00-19:30 Networking

Navigation in a 3D environment with Reinforcement Learning

Summary:
Reinforcement learning in today's order of things when artificial intelligence is on the rise is a favorable field for new research. One of the problems that were tried to be solved in the last year or two is the problem of environmental control or navigation. This talk is going to present one form of solution to the problem of navigation and generalization in a three-dimensional environment while there are restrictions of rewards, by forming an autonomous agent with deep learning techniques.

Bio:
Predrag is a Data Scientist who found a combination of programming, mathematics, and research in AI. He is a talented and awarded young professional who always seeks new knowledge, ways to improve himself, and also challenging problems that will push him out of his comfort zone.

Event deduplication in Kafka

Summary:
Implementing even the simplest algorithms in a distributed system as highly available can be really challenging. There are a lot of scenarios where something can go wrong and produce incorrect results. This talk is about what it takes to have a resilient solution for event deduplication. I'll try to guide you through my thought process and try to present all the scenarios in which something can go wrong.

Bio:
Vladimir Vajda works as Data Engineer at SmartCat. He started as a Java developer but got interested in distributed and data-intensive systems. Loves great argument, a good book, good beer, and tasty food. He usually spends his spare time with his family or tinkering and playing with some new technology or project.