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Java Articles by Foojay.io

May, 2025

  • 27 May

    Intro to RAG: Foundations of Retrieval Augmented Generation, part 1

    Author: Jennifer Reif Original post on Foojay: Read More Table of Contents Why RAG?Large Language Models (LLMs)Vector embeddings Vectors applied to words Vectors applied to data Similarity search Wrapping up!Resources Retrieval Augmented Generation (RAG) may sound complex, but it accurately represents the process of the system. RAG is a method that enhances the capabilities of Large Language Models (LLMs) by …

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  • 26 May

    Azul and JetBrains Collaborate to Enhance Runtime Performance for Kotlin Workloads

    Author: Geertjan Wielenga Original post on Foojay: Read More SUNNYVALE, Calif., — May 20, 2025 — Azul, the only company 100% focused on Java, and JetBrains, the leading provider of professional software development tools and creator of the Kotlin programming language, today announced a strategic technical collaboration to enhance the runtime performance and scalability of web and server-side Kotlin applications. This strategic collaboration …

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  • 26 May

    AI Test Generation: A Dev’s Guide Without Shooting Yourself in the Foot

    Author: Jonathan Vila Original post on Foojay: Read More Table of Contents So, AI Can Write Tests Now? Cool, But…How AI Learns to Code (And Why That’s a Problem for Tests)Problem #1: AI Tests Might Just Be WrongProblem #2: Testing the Code You Have, Not the Code You Need (Verification vs. Validation Trap)So? What to Do? Don’t Use AI for …

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  • 22 May

    Understanding BSON: A Beginner’s Guide to MongoDB’s Data Format

    Author: Tim Kelly Original post on Foojay: Read More Table of Contents What is BSON? Why not just JSON? BSON vs. JSONCommon BSON data types (and their Java equivalents)BSON and MongoDB internalsSetup and project structureBSON data types and document creation Nested fields and arrays Why use nested structures? Raw BSON manipulationQuerying with BSONAggregation with BSONPOJO mapping: Bridging Java and BSON …

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  • 21 May

    How to send prompts in bulk with Spring AI and Java Virtual Threads

    Author: Raphael De Lio Original post on Foojay: Read More Table of Contents Here’s the flow:Virtual Threads for Massive ParallelismSpring AI Prompt CallProcessing in BatchesHandling Errors GracefullyProcess Results in BulkFull ImplementationStay curious! TL;DR: You’re building an AI-powered app that needs to send lots of prompts to OpenAI. Instead of sending them one by one, you want to do it in …

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  • 19 May

    How Deep Netts and Java AI Transformed Particle Physics at US DoE, Jefferson Lab

    Author: Zoran Sevarac Original post on Foojay: Read More At the intersection of nuclear physics and artificial intelligence, Jefferson Lab is leveraging Java-based AI to overcome one of the most computationally intense challenges in modern science: reconstructing particle trajectories from high-frequency electron scattering experiments. Each second, over 16,000 interactions are recorded as particles pass through a complex array of drift …

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  • 19 May

    Join the NLJUG JSpring Conference on Thursday, June 5

    Author: Martin Smelt Original post on Foojay: Read More Join the Dutch Java community at J-Spring 2025, the premier Java conference in the Netherlands, taking place Thursday, June 5th at Jaarbeurs Utrecht. This international event, organized by the NLJUG (Dutch Java User Group), will be bigger than ever before, offering attendees a comprehensive program featuring world-class speakers from across the globe. Dive deep into …

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  • 19 May

    How to Deploy a Vaadin Application as a WAR on Tomcat 11

    Author: Simon Martinelli Original post on Foojay: Read More Table of Contents Step 1: Download Tomcat 11Step 2: Create a New Vaadin ProjectStep 3: Adjust the pom.xmlStep 4: Update the Spring Boot Application ClassStep 5: Build the Application for ProductionStep 6: Deploy the WAR to TomcatConclusion If you want to run a Vaadin application on an external servlet container like Apache Tomcat …

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  • 16 May

    What is RAG, and How to Secure It

    Author: Brian Vermeer Original post on Foojay: Read More Table of Contents Why use RAGHow RAG Works 1. Retrieval 2. Generation Security implications of using RAG Prompt injection through retrieved content Data poisoning Access control gaps in retrieval Leaking PII to third-party models Caching risks and session bleed Contradictory or low-quality information Proactive and remediation strategies for securing RAG Sanitize …

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  • 14 May

    Building a Real-Time AI Fraud Detection System with Spring Kafka and MongoDB

    Author: Tim Kelly Original post on Foojay: Read More Table of Contents What we are buildingPrerequisitesCreate our MongoDB databaseCreate a Vector Search indexCreate a Spring applicationSetting up configuration MongoDB configuration Spring AI configuration Kafka configuration Generate our synthetic customer profiles The customer model Customer seeding How the sample customers are structured The transaction model Generating random transactions How do we …

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