Zhipu released the open-weight GLM-5.2 within days of the US blocking foreign access to Anthropic frontier models. The benchmark numbers behind the geopolitics, and what it means if you want to run it yourself.
How gradient descent variants, batch normalization, and learning rate scheduling actually get a neural network to converge, and why the wrong choice makes training fail silently.
How specialized computing architectures are accelerating AI development.
What actually breaks when ML models move from a notebook to production, and the versioning, retraining, and monitoring practices that prevent it.