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Deep Learning Frameworks in 2025: A Review

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Manage episode 461829787 series 3620285
Content provided by David Such. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by David Such 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://ppacc.player.fm/legal.

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In this episode, we investigate the state of deep learning frameworks in 2025. We review the leading contenders—TensorFlow, PyTorch, JAX, MXNet, and LightningAI—analyzing their strengths, latest features, performance benchmarks, and the size of their user communities.

We also explore key trends shaping the field, including the sustained dominance of established frameworks and the growing popularity of specialized options like LightningAI, known for its focus on performance, scalability, and usability. To wrap up, we discuss future directions in deep learning frameworks, from integrating quantum computing to improving model interpretability. Tune in for a forward-looking discussion on the tools driving the future

If you are interested in learning more then please subscribe to the podcast or head over to https://medium.com/@reefwing, where there is lots more content on AI, IoT, robotics, drones, and development. To support us in bringing you this material, you can buy me a coffee or just provide feedback. We love feedback!

  continue reading

26 episodes

Artwork
iconShare
 
Manage episode 461829787 series 3620285
Content provided by David Such. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by David Such 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://ppacc.player.fm/legal.

Send us a text

In this episode, we investigate the state of deep learning frameworks in 2025. We review the leading contenders—TensorFlow, PyTorch, JAX, MXNet, and LightningAI—analyzing their strengths, latest features, performance benchmarks, and the size of their user communities.

We also explore key trends shaping the field, including the sustained dominance of established frameworks and the growing popularity of specialized options like LightningAI, known for its focus on performance, scalability, and usability. To wrap up, we discuss future directions in deep learning frameworks, from integrating quantum computing to improving model interpretability. Tune in for a forward-looking discussion on the tools driving the future

If you are interested in learning more then please subscribe to the podcast or head over to https://medium.com/@reefwing, where there is lots more content on AI, IoT, robotics, drones, and development. To support us in bringing you this material, you can buy me a coffee or just provide feedback. We love feedback!

  continue reading

26 episodes

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