Deep Learning Frameworks in 2025: A Review
About this episode
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
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