Java devs: InMobi boosts ML inference speed with SIMD Vector API

#DAY3 Week 1 Java -> Gen AI Java developer Most developers ask "How do I use AI?" The better question is "Which AI, for which problem, at what cost?" I spent today mapping the LLM landscape as part of my 5-week Java → GenAI Engineer challenge, and here's the cheat sheet I wish I'd had earlier: 𝗠𝗼𝗱𝗲𝗹 𝗣𝗶𝗰𝗸𝗲𝗿 𝗳𝗼𝗿 𝗝𝗮𝘃𝗮 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀: • Customer chatbot → GPT-4o or Claude Haiku (speed + quality) • Legal / long docs → Claude 3.5 Sonnet (200K context window) • Code generation → GPT-4o (leads benchmarks) • Privacy-sensitive → Llama 3 via Ollama (data never leaves your machine) • High-volume, low-cost → GPT-3.5 or Claude Haiku (cents per 1K tokens) • Need to fine-tune → Llama 3 or Mistral (open weights required) The underrated insight: Spring AI gives you a single ChatClient interface across all of these. Switching providers is a config change, not a rewrite. Context windows matter more than most people realise. 128K tokens ≈ a short novel. Get this wrong in a RAG pipeline and your app silently drops context without warning. #GenAI #Java #SpringAI #MachineLearning #SoftwareEngineering #LLM #OpenSource

Integrating Generative AI into Enterprise Java with Spring AI 🚀 Ready to bring Generative AI into enterprise Java Enter Spring AI! 🤖🍃 • If you're a Java developer looking to integrate Large Language Models (LLMs) into your projects, you've probably noticed that the ecosystem has historically been skewed towards Python. Spring AI is changing that. Key Feature: Write Once, Run Anywhere and Vendor Lock-in Prevention • The biggest superpower Spring AI brings to the table is the "Write Once, Run Anywhere" philosophy applied to AI models. • Through universal abstractions like ChatClient, you can write your business logic once and seamlessly swap between OpenAI, Google Vertex AI, Amazon Bedrock, or local models (like Ollama) simply by updating your application.yml properties. • Complete prevention of LLM vendor lock-in. Further Discussion and Community Engagement • I'll be sharing more about Spring AI's advanced features later this week. • Have you started looking into it yet? • Let me know below! 👇 #SpringAI #Java #GenerativeAI #SpringFramework #SoftwareEngineering #AryanDevCodes

🤖 Built an AI Command Assistant in Python — Completely Free! Just finished building a fully functional AI assistant from scratch that understands natural language commands and controls your entire system! Just type a command like: → open youtube → browser opens instantly → search jobs in chennai → Google search launches → play AR Rahman hits → YouTube opens with results → take a screenshot → saved automatically → turn up the volume → system volume increases → open notepad → app launches → close notepad → app closes Tech stack: → Python 3.12 → Groq AI (free tier) — understands natural language → PyAutoGUI — system control → pyttsx3 — voice feedback The best part? Zero paid tools. 100% free. Built the entire pipeline from scratch: Text Input → Groq AI → Intent Classification → Action Router → System Execution This is just the beginning. Next up: GUI dashboard + wake word detection 🚀 #Python #AI #Automation #NaturalLanguageProcessing #OpenSource #BuildInPublic #100DaysOfCode #MachineLearning #Programming #Groq 

JVM Enters the AI Agent Arena! The world of AI agents is exploding, and now Java developers have a powerful new seat at the table! Rod Johnson, the legendary founder of Spring, is building one of the first JVM-native AI agent frameworks! This is huge news for enterprise applications. Think seamless integration, robust security, and the power of AI agents running natively within your existing Java infrastructure. No more complex integrations with Python – true JVM-native power! This move signals a major shift, making sophisticated AI agent capabilities accessible to a broader range of developers and businesses. What are your thoughts on JVM-native AI agents? How do you see this impacting enterprise adoption of AI? Share your insights in the comments! 👇 #LangChain #AI #Java #JVM #AIagents #SpringFramework #RodJohnson #ArtificialIntelligence #MachineLearning #EnterpriseAI Read Full Article Here: https://lnkd.in/gkHTykxV

🚀 Day 2 of My AI Engineering Learning Journey Today I implemented a complete Retrieval-Augmented Generation (RAG) pipeline using Java and Spring Boot. As a backend engineer with 10+ years of experience in Java and microservices, I wanted to understand how modern AI applications actually work behind the scenes. Instead of only using AI APIs, I built the system from scratch. ��� What I implemented today • Built a REST API using Spring Boot • Generated embeddings locally using Ollama with the Llama 3 model • Stored vector embeddings in PostgreSQL using pgvector • Implemented vector similarity search to retrieve relevant documents • Built a RAG pipeline where retrieved documents are passed to the LLM to generate contextual answers 🧠 Architecture I built User Question → Generate Embedding → Vector Search (pgvector) → Retrieve Relevant Documents → Send Context to LLM → AI Generates Final Answer 💡 Tech Stack Java • Spring Boot • WebClient • Ollama • Llama3 • PostgreSQL • pgvector • Vector Search This project helped me understand some core AI engineering concepts: ✔ Embeddings ✔ Vector databases ✔ Semantic search ✔ Retrieval-Augmented Generation (RAG) Excited to continue the journey and next explore document chunking and building a ChatGPT-style document assistant. #AIEngineering #Java #SpringBoot #RAG #VectorDatabase #LLM #GenerativeAI #BackendEngineering

AI agents are becoming a key architectural pattern in modern applications. If you're working with Java and want to explore how agentic capabilities can be implemented with familiar tools, this hands-on session by Laura Schlosser and Arnaud Jean is really great! They’ll show how to build AI agents using Spring AI — the Java way. Worth checking out. 📅 April 16 Details in the original post.

New post in my Spring AI 2 series! This time: Advisors — the middleware of your AI pipeline. We explore SimpleLoggerAdvisor, build custom advisors, and look at recursive patterns. #SpringAI#Spring#AI#Java

𝗚𝗼𝗼𝗴𝗹𝗲 𝗘𝘅𝗽𝗮𝗻𝗱𝘀 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗞𝗶𝘁 𝘁𝗼 𝗝𝗮𝘃𝗮 𝘄𝗶𝘁𝗵 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗧𝗼𝗼𝗹𝗶𝗻𝗴 🛰️ [AI AGENTS] Google's ADK now supports Java, enhancing AI agents with new tools and controls. Why it matters: The expansion of Google's ADK to Java signifies a broader push to democratize AI agent development across enterprise-grade programming environments. Enhanced tooling and human-in-the-loop features address critical aspects of agent reliability and control, accelerating their adoption in complex applications. 🤔 How will multi-language AI agent frameworks influence enterprise software architecture and developer skill sets? #AIADK #JavaAI #GoogleAI #AgentDevelopment #LLMAgents 📡 Follow DailyAIWire for autonomous AI news 🔗 https://lnkd.in/dNa-UerB

We integrated AI agents into a real Java project in production. The first thing we learned was that the model wasn’t the problem. What was missing, no tutorial really explains. 👉 The full story here: https://lnkd.in/eYF3Km7N #AI #AgenticAI #SoftwareEngineering