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Java 22 and 23 Features

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Contenuto fornito da Adam Bien. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Adam Bien o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
An airhacks.fm conversation with Nicolai Parlog (@nipafx) about:
Java 22 and 23 new features overview, including unnamed variables with underscore, multi-source file launching, G1 region pinning, Foreign Function & Memory API finalization, Markdown Javadoc support, ZGC generational collector by default, discussion on Java installation and beginner-friendliness, debate on proper use of LTS terminology for Java releases, potential for Java in AI/ML space with new vector APIs and native performance, comparison of Java to python for AI workloads, challenges and opportunities for Java adoption in data science and machine learning domains, importance of specialized AI models vs general models for enterprise use cases, trade-offs between developer experience and operational efficiency for different languages and runtimes, potential future directions for Java in high-performance computing and AI acceleration, previously, Nicolai appeared on "#300 Object-Oriented Programming (OOP) vs. Data-Oriented Programming (DOP) in Java"

Nicolai Parlog on twitter: @nipafx

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312 episodi

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Manage episode 437877038 series 2469611
Contenuto fornito da Adam Bien. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Adam Bien o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
An airhacks.fm conversation with Nicolai Parlog (@nipafx) about:
Java 22 and 23 new features overview, including unnamed variables with underscore, multi-source file launching, G1 region pinning, Foreign Function & Memory API finalization, Markdown Javadoc support, ZGC generational collector by default, discussion on Java installation and beginner-friendliness, debate on proper use of LTS terminology for Java releases, potential for Java in AI/ML space with new vector APIs and native performance, comparison of Java to python for AI workloads, challenges and opportunities for Java adoption in data science and machine learning domains, importance of specialized AI models vs general models for enterprise use cases, trade-offs between developer experience and operational efficiency for different languages and runtimes, potential future directions for Java in high-performance computing and AI acceleration, previously, Nicolai appeared on "#300 Object-Oriented Programming (OOP) vs. Data-Oriented Programming (DOP) in Java"

Nicolai Parlog on twitter: @nipafx

  continue reading

312 episodi

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