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