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Java, Serverless, Clouds, Architecture and Web conversations with Adam Bien

airhacks.fm podcast with adam bien Adam Bien

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Java, Serverless, Clouds, Architecture and Web conversations with Adam Bien

    High-Performance Java, Or How JVector Happened

    High-Performance Java, Or How JVector Happened

    An airhacks.fm conversation with Jonathan Ellis (@spyced) about:
    Jonathan's first computer experiences with IBM PC 8086 and Thinkpad laptop with Red Hat Linux,
    becoming a key contributor to Apache Cassandra and founding datastax,
    starting DataStax to provide commercial support for Cassandra,
    early experiences with Java, C++, and python,
    discussion about the evolution of Java and its ecosystem,
    the importance of vector databases for semantic search and retrieval augmented generation,
    the development of JVector for high-performance vector search in Java,
    the potential of integrating JVector with LangChain for Java / langchain4j and quarkus for serverless deployment,
    the advantages of Java's productivity and performance for building concurrent data structures,
    the shift from locally installed software to cloud-based services,
    the challenges of being a manager and the benefits of taking a sabbatical to focus on creative pursuits,
    the importance of separating storage and compute in cloud databases,
    Cassandra's write-optimized architecture and improvements in read performance,
    DataStax's investment in Apache Pulsar for stream processing,
    the llama2java project for high-performance language models in Java
    Jonathan Ellis on twitter: @spyced

    • 1 時間1分
    LLama2.java: LLM integration with A 100% Pure Java file

    LLama2.java: LLM integration with A 100% Pure Java file

    An airhacks.fm conversation with Alfonso Peterssen (@TheMukel) about:
    discussion about Alfonso's early programming experience and participation in the IOI competition, studying computer science and functional programming with Martin Odersky, internships at Google and Oracle Labs working on compilers and the Espresso project implementing a JVM in Java,
    espresso mentioned in "#208 GraalVM: Meta Circularity on Different Levels", "#194 GraalVM, Apple Silicon (M1) and Clouds", "#167 GraalVM and Java 17, Truffle, Espresso and Native Image" and "#157 The Ingredients of GraalVM",
    porting LLVM to pure Java in one class, integrating Large Language Models (LLMs) in Java by porting the LLAMA model from C to Java,
    GPU acceleration with tornadovm,
    TornadoVM appeared at "#282 TornadoVM, Paravox.ai: Java, AI, LLMs and Hardware Acceleration",
    performance of the Java port being within 10% of the C versions, potential huge opportunities for integrating AI and LLMs with enterprise Java systems for use cases like fraud detection, the Java port being a 1,000 line self-contained implementation with no external dependencies, the need for more resources and support to further develop the Java LLM integration,
    the llama2.java project
    Alfonso Peterssen on twitter: @TheMukel

    • 1 時間1分
    How Kotlin Happened

    How Kotlin Happened

    An airhacks.fm conversation with Anton Arhipov (@antonarhipov) about:
    Anton appeared previously on "#273 The Long Road to Java and Kotlin", discussion about Anton Arhipov's artwork using circles and a compass, attending the JVM Language Summit in 2011 where Kotlin was introduced by JetBrains, initial skepticism about the need for a new JVM language, JSR-305 Annotations for Software Defect Detection by William Pugh, Kotlin's null safety features and interoperability with Java, Kotlin's growth and adoption by Android developers, Kotlin's multiplatform capabilities for targeting native, JavaScript, and WebAssembly, Kotlin's potential beyond Android development, Kotlin's core libraries for date/time, serialization, and coroutines, the Kotlin compiler being self-hosted and written in Kotlin, benefits of Kotlin Native for serverless and IoT compared to GraalVM, Kotlin Multiplatform support in the upcoming JetBrains Fleet IDE, designers using similar UI principles across IDEs and applications
    Anton Arhipov on twitter: @antonarhipov

    • 1 時間17分
    How Azul Happened

    How Azul Happened

    An airhacks.fm conversation with Gil Tene (@giltene) about:
    starting with hacking adventure games on a VAX-11/780 as a teenager,
    building computers and making money in high school,
    providing access to Usenet,
    early programming experiences with Pascal and C/C++,
    moving to Silicon Valley in 1994 and witnessing the rise of Java,
    working on fault-tolerant computer systems at Stratus Computer,
    co-founding Azul Systems and developing the Vega appliances to virtualize Java applications,
    the technical details of how Vega appliances worked by running JVMs on specialized hardware,
    the evolution of Azul to focus on pure software solutions such as Zing and supporting openJDK,
    Gil's continued involvement in coding and maintaining open-source libraries
    Gil Tene on twitter: @giltene

    • 1 時間26分
    Pure Java AI

    Pure Java AI

    An airhacks.fm conversation with Dr. Zoran Sevarac (@zsevarac) about:
    Zoran previously on airhacks.fm: "#169 Deep Learning with Modern Java Code",
    discussion about the latest updates and features in DeepNetts,
    a full-stack Java AI platform,
    University of Minnesota's drug testing application using DeepNetts,
    Jefferson Lab's particle research using DeepNetts Community Edition,
    including GPU support for faster inference using jcuda,
    TensorFlow compatibility, and simplified AI integration with JSR-381,
    real-world applications of DeepNetts in drug testing and particle research,
    challenges and considerations for using GPUs in serverless environments,
    the potential of Apple's M-series chips for machine learning,
    exploring Project Babylon and Code Reflection in Java,
    using Panama and jextract for native library bindings,
    the importance of having developer tools and an IDE for building AI models,
    plans for integrating large language models into DeepNetts,
    the advantages of a pure Java solution for AI in enterprise applications,
    and the bright future of Java in the AI ecosystem,
    Deep Nets 3.1.0 release with GPU support
    Dr. Zoran Sevarac on twitter: @zsevarac

    • 51分
    How OpenRewrite Happened

    How OpenRewrite Happened

    An airhacks.fm conversation with Jonathan Schneider (@jon_k_schneider) about:
    from Pentium 2 machine and a rural high school to becoming a Java refactoring entrepreneur,
    self-taught C++ in high school,
    officer in the U.S. Army and deployed to Iraq and Afghanistan,
    worked on Java projects at an insurance company between deployments,
    joined Netflix to work on engineering tools,
    challenges of migrating Java versions and libraries in a freedom and responsibility culture,
    started the OpenRewrite project at Netflix for automated refactoring and code migration,
    founded the micrometer metrics instrumentation project at Pivotal,
    challenges of introducing automated pull requests in enterprise environments,
    rebooted OpenRewrite while working with Gradle's Hans Dockter,
    founded Moderne to commercialize OpenRewrite for large-scale enterprise refactoring,
    the origin of the Moderne name and its Art Deco roots,
    OpenRewrite's Maven and Gradle plugins for refactoring and styling using a visitor pattern on an enriched AST,
    Moderne's enterprise offering for large-scale refactoring and impact analysis,
    potential integration with large language models and retrieval-augmented generation for code optimization
    Jonathan Schneider on twitter: @jon_k_schneider

    • 1 時間2分

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