Woyce
Compute governance is the emerging set of rules that treat AI chips, data centers, and cloud capacity as regulated infrastructure rather than ordinary commercial hardware.
A comparison of how the United States, European Union, and China are regulating artificial intelligence, and what the growing divergence means for companies building and deploying AI systems.
AI safety institutes are government-backed bodies that test frontier AI models for dangerous capabilities before and after release. Here's how the network works and why it matters.
A practical breakdown of how AI export controls actually function — from Entity Lists and license categories to the global map of who can buy advanced chips.
A look at how India is extending its Digital Public Infrastructure model—Aadhaar, UPI, ONDC—into artificial intelligence, and what that means for sovereignty, compute, and data.
A practical breakdown of the new wave of frontier AI transparency laws, what they require model developers to publish, and how companies building on top of these models should prepare.
AI incident reporting is the practice of systematically logging and disclosing when AI systems cause harm, and it's rapidly becoming a policy requirement worldwide.
A plain-language look at why AI regulators use raw training compute — measured in FLOPs — as the trigger for oversight, and what that means for model builders.
A look at how GPU exports, sovereign datacenter deals, and chip export controls have turned AI infrastructure into a tool of geopolitics.
A look at why AI's next competitive battleground is language coverage, not just model size, and what local-language models mean for builders and businesses.
A practical look at how companies now license text, images, audio, and video to train AI models, and why courts and settlements are setting the price.
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