Episodes

  • ChatGPT for Java Development: Insights and Best Practices

    ChatGPT for Java Development: Insights and Best Practices
    Nov 24 2024
    An airhacks.fm conversation with Bruce Hopkins about: discussion on using ChatGPT for Java development, challenges and benefits of AI-assisted coding, importance of understanding and reviewing AI-generated code, bootstrapping approach in Bruce's book, using ChatGPT as a pair programmer, limitations of AI in making architectural decisions, potential pitfalls of relying too heavily on AI-generated code, multi-modal capabilities of AI models, creating a podcast visualizer project, integrating with Slack and Discord APIs, hallucination issues in AI responses, importance of prompt engineering, potential for Java in AI and LLM integration, advantages of Java in enterprise environments, energy efficiency and performance of Java compared to other languages, upcoming trends in Java development including project valhalla and Vector API, potential for a follow-up book on quarkus and langchain4j, modern Java syntax and features making it competitive with other languages, challenges of translating technical books to other languages, the ChatGPT for Java book
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    50 mins
  • From Java VMs and GPU Acceleration to Motorcycle Electronics

    From Java VMs and GPU Acceleration to Motorcycle Electronics
    Nov 17 2024
    53 mins
  • From XML-Driven Enterprise Java to Serverless AWS Lambdas

    From XML-Driven Enterprise Java to Serverless AWS Lambdas
    Nov 10 2024
    An airhacks.fm conversation with Vadym Kazulkin (@VKazulkin) about: journey as a Java developer from the late 1990s to present, early experiences with Java and J2EE development, transition to cloud and serverless technologies, particularly AWS Lambda, discussion of Java performance on lambda compared to node.js, detailed explanation of AWS SnapStart technology for improving Java cold starts, pros and cons of "fat" Lambda functions versus microservices, challenges of using GraalVM with Lambda, importance of optimizing Lambda package size and dependencies, comparison of quarkus and Spring Boot on Lambda, benefits of serverless architecture for business logic focus, involvement with Java User Group Bonn and AWS Community Builder program, brief mention of asynchronous patterns in serverless architectures, importance of staying technically hands-on as a manager in the rapidly evolving cloud world

    Vadym Kazulkin on twitter: @VKazulkin
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    56 mins
  • JDBC with Oracle Deeper Dive: From OCI to Thin Drivers and Beyond

    JDBC with Oracle Deeper Dive: From OCI to Thin Drivers and Beyond
    Nov 3 2024
    An airhacks.fm conversation with Gerald Venzl (@geraldvenzl) about: discussion about the evolution of Oracle's annual conference from OpenWorld to CloudWorld, the JavaOne conference, explanation of JDBC driver types and their evolution, Oracle's thin JDBC driver becoming the preferred option, availability of Oracle JDBC drivers on Maven Central, proprietary features of Oracle's JDBC driver including Continuous Query Notification (CQN) and Application Continuity, comparison of CQN to Change Data Capture (CDC) and CQRS patterns, Oracle's Flashback Data Archive for auditing and time travel capabilities, Oracle's Advanced Queuing and Transactional Event Queues, ORDS REST APIs, Oracle product page, Oracle JDBC client libraries, the plug-in mechanism implemented in early Java versions for JDBC drivers using Class.forName and static initializers, Gerald Venzl's online presence and recent blog post about running Oracle database on Raspberry Pi

    Gerald Venzl on twitter: @geraldvenzl
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    46 mins
  • Java, LLMs, and Seamless AI Integration with langchain4j, Quarkus and MicroProfile

    Java, LLMs, and Seamless AI Integration with langchain4j, Quarkus and MicroProfile
    Oct 26 2024
    An airhacks.fm conversation with Dmytro Liubarsky (@langchain4j) about: discussion on recent developments in Java and LLM integration, new features in langchain4j including Easy RAG for simplified setup, SQL database retrieval with LLM-generated queries, integration with graph databases like Neo4j, Neo4j and graphrag, metadata filtering for improved search capabilities, observability improvements with listeners and potential integration with opentelemetry, increased configurability for AI services enabling state machine-like behavior, the trend towards CPU inference and smaller, more focused models, langchain4j integration with quarkus and MicroProfile, parallels between AI integration and microservices architecture, the importance of decomposing complex AI tasks into smaller, more manageable pieces, potential cost optimization strategies for AI applications, the excitement around creating smooth APIs that integrate well with the Java ecosystem, the potential future of CPU inference and its parallels with the evolution of server infrastructure, the upcoming Devoxx conference,

    Dmytro Liubarsky on twitter: @langchain4j
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    1 hr
  • Quarkus and LangChain4J - A Match Made in Heaven

    Quarkus and LangChain4J - A Match Made in Heaven
    Oct 20 2024
    An airhacks.fm conversation with Georgios Andrianakis (@geoand86) about: discussion on integrating langchain4j with quarkus for enterprise AI applications, similarities between LLM integration and microservice architecture, benefits of using Java and MicroProfile for AI development, explanation of AI services, chat memory, and tools in LangChain4J, importance of session management and fault tolerance in LLM applications, vector databases and embeddings for efficient information retrieval, RAG (Retrieve Augmented Generation) implementation in enterprise settings, Quarkus dev mode features for LLM experimentation, native image support with GraalVM, local inference possibilities with Java 21's Vector API and quantized models, challenges in prompt engineering and model selection, upcoming features in LangChain4J including Ollama tool support and improved result streaming, future developments in Java for AI and GPU support with Project Babylon, importance of enterprise-grade features like CI/CD, testing, and cloud deployment for LLM applications

    Georgios Andrianakis on twitter: @geoand86
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    1 hr and 3 mins
  • Why JVector 3 Is The Most Advanced Embedded Vector Search Engine

    Why JVector 3 Is The Most Advanced Embedded Vector Search Engine
    Oct 13 2024
    An airhacks.fm conversation with Jonathan Ellis (@spyced) about: discussion of JVector 3 features and improvements, compression techniques for vector indexes, binary quantization vs product quantization, anisotropic product quantization for improved accuracy, indexing Wikipedia example, Cassandra integration, SIMD acceleration with Fused ADC, optimization with Chronicle Map, E5 embedding models, comparison of CPU vs GPU for vector search, implementation details and low-level optimizations in Java, use of Java Panama API and foreign function interface, JVector's performance advantages, memory footprint reduction, integration with Cassandra and Astra DB, challenges of vector search at scale, trade-offs between RAM usage and CPU performance, Eventual Consistency in distributed vector search, comparison of different embedding models and their accuracy, importance of re-ranking in vector search, advantages of JVector over other vector search implementations

    Jonathan Ellis on twitter: @spyced
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    54 mins
  • The AI Revolution in Java Development and Devoxx Genie

    The AI Revolution in Java Development and Devoxx Genie
    Oct 6 2024
    An airhacks.fm conversation with Stephan Janssen (@Stephan007) about: Stephan previously appeared on "#254 How JavaPolis and Devoxx Happened", discussion on the AI revolution in programming, development of an AI-assisted photo sharing application, creation of the Devoxx Genie IntelliJ plugin for AI-augmented programming, advantages of Claude 3.5 from Anthropic, use of local AI models in development environments, integration of AI in Java development, langchain4j and its adoption by Red Hat, development of Java-based AI tools like Lama3.java, jlama and JVector, potential for specialized AI models in software development, challenges and opportunities for junior and senior developers in AI-augmented programming, importance of understanding cloud services and cost structures when using AI, potential future of prompt-based programming and code generation, discussion on maintaining and improving AI-generated code, exciting developments in Java for AI including project valhalla and tornadovm, potential for running AI models directly on Java without external dependencies, considerations for enterprise AI adoption and integration, the need for promoting Java's capabilities in AI development, potential for Visual Studio Code port of Devoxx Genie, the challenge of maintaining AI-generated code versus keeping prompts, the concept of "prompt ops" for software development, the use of AI for code review and improvement, the potential for AI to lower the barrier to entry for new developers, and the exciting future of AI in software development

    Stephan Janssen on twitter: @Stephan007
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    1 hr and 9 mins