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WSO2
Tracing the root cause of a performance issue requires a lot of patience, experience, and focus. It’s so hard that we sometimes attempt to guess by trying out tentative fixes, but that usually results in frustration, messy code, and a considerable waste of time and money. This talk explains how to correctly zoom in on a performance bottleneck using three levels of profiling: distributed tracing, metrics, and method profiling. After we learn to read the JVM profiler output as a flame graph, we explore a series of bottlenecks typical for backend systems, like connection/thread pool starvation, invisible aspects, blocking code, hot CPU methods, lock contention, and Virtual Thread pinning, and we learn to trace them even if they occur in library code you are not familiar with. Attend this talk and prepare for the performance issues that will eventually hit any successful system. About authorWith two decades of experience, Victor is a Java Champion working as a trainer for top companies in Europe. Five thousands developers in 120 companies attended his workshops, so he gets to debate every week the challenges that various projects struggle with. In return, Victor summarizes key points from these workshops in conference talks and online meetups for the European Software Crafters, the world’s largest developer community around architecture, refactoring, and testing. Discover how Victor can help you on victorrentea.ro : company training catalog, consultancy and YouTube playlists.
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Victor Rentea
Six common myths about ontology engineering, knowledge graphs, and knowledge representation.
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
johnbeverley2021
💥 You’re lucky! We’ve found two different (lead) developers that are willing to share their valuable lessons learned about using UiPath Document Understanding! Based on recent implementations in appealing use cases at Partou and SPIE. Don’t expect fancy videos or slide decks, but real and practical experiences that will help you with your own implementations. 📕 Topics that will be addressed: • Training the ML-model by humans: do or don't? • Rule-based versus AI extractors • Tips for finding use cases • How to start 👨🏫👨💻 Speakers: o Dion Morskieft, RPA Product Owner @Partou o Jack Klein-Schiphorst, Automation Developer @Tacstone Technology
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
UiPathCommunity
Retrieval augmented generation (RAG) is the most popular style of large language model application to emerge from 2023. The most basic style of RAG works by vectorizing your data and injecting it into a vector database like Milvus for retrieval to augment the text output generated by an LLM. This is just the beginning. One of the ways that we can extend RAG, and extend AI, is through multilingual use cases. Typical RAG is done in English using embedding models that are trained in English. In this talk, we’ll explore how RAG could work in languages other than English. We’ll explore French, Chinese, and Polish.
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
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WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
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