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Pure Java AI

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Content provided by Adam Bien. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Adam Bien or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
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

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293 episodes

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Pure Java AI

airhacks.fm podcast with adam bien

217 subscribers

published

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Fetch error

Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on April 28, 2024 13:47 (5d ago)

What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.

Manage episode 413531271 series 2469611
Content provided by Adam Bien. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Adam Bien or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
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

  continue reading

293 episodes

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