What Happened
In November 2015, Google announced the open-source release of TensorFlow, positioning it as a flexible, general-purpose system for machine learning.
Why It Matters
TensorFlow quickly became a major framework for training and deploying neural networks, lowering barriers to entry for large-scale experimentation and production ML.
Technical Details
TensorFlow popularized computation-graph-based ML programming and later evolved toward eager execution and higher-level APIs, while maintaining a strong production deployment story.