AI25 articles

Table of Contents Adding filters: From story to codeFirst try: Add a post-filter in MovieServiceSecond try: Use a pre-filterRefining the search with extra filtersApplying toCriteria() in the searchReducing embedding costs with cachingStrategy with @CacheableA minimal frontendStep 1: HTMLStep 2: JavaScriptStep …

Table of Contents Do LLMs have any conversational memory?Implementing chat memory in your AI appChat messages with Java’s Langchain4JLLM chat memory injectionChat memory injection: Proof of conceptPreventing chat memory manipulation is key Do LLMs have any conversational memory? With the …

Table of Contents From AI User to AI Pro1. The Golden Rule: Take Pride and Ownership in Your Craft 🥇2. Feed the Beast: Your Project’s Context is its Fuel ⛽3. Dodge the “Ball of Mud”: Keep Your Code Maintainable 🧠4. …

Fourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of artificial intelligence. Beyond focused tutorials that can enhance your understanding of AI applications, this newsletter concentrates on …

Table of Contents What is hybrid search?How does it work in MongoDB?Why movies collection are the perfect demoInspecting the anchor documentSanity checksStep 1: Prepare the query vectorStep 2: Run semantic searchStep 3: Apply hybrid scoringStep 4: Hybrid ranking with Reciprocal …

Table of Contents A Quick Overview of AgentsPath 1: Standardized Integration with MCP serversPath 2: Custom Integrations for Control and FlexibilityAccuracy, Security, and Performance ConsiderationsAccuracy: Ensure Reliable Query GenerationSecurity: Maintain Protection and GuardrailsPerformance: Manage Unpredictable Agentic WorkloadsThe Agentic Future Depends …

Fourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of artificial intelligence. Beyond opinion pieces and Java focused tutorials that can enhance your understanding of AI applications, …

Last time, we created a vector search index in a local MongoDB Atlas cluster. Now, let’s put it to work with a real case: building an AI-powered movie recommender that suggests films similar to The Matrix–without any shared keywords. 🕒 …

Table of Contents Managing Payara Server Just Got SmarterWhat Is the Payara Server Maven Plugin?Meet the AI Agent (Experimental)Demo #1 – Memory & Threads, in Plain EnglishWhat’s happening:Demo #2 – JDBC, JMX, and JMS Made EasyWhat’s happening:Configuring the AI AgentFinal …

Most major database vendors, like MongoDB , are adding vector search capabilities to their products. It’s becoming a standard feature as demand for AI-powered applications grows. 🕒 Reading time: 3-4 min 🧠 What is vector search needed for? MongoDB Vector …