Why do so many governance proposals focus on chips? Read one key paper and write a jargon-free explainer for someone outside tech.
Compute governance underpins export controls, thresholds and verification proposals. Explaining it well is how ideas spread to decision-makers.
Output: An 800-word explainer.
Read the introduction and summary of “Computing Power and the Governance of Artificial Intelligence”. Note the three or four properties that make compute governable.
Think of something similar people already understand (regulating dangerous materials, for example) and where the comparison breaks.
Explain what compute is, why it is trackable, what governments do with that, and one big open question.
Ask a friend to explain it back to you. Fix whatever came back wrong.
All steps done
Share what you made, then try another project. The PDF version has room for notes.
Next: Estimate how much compute a famous model needed Next steps
Use the rule of thumb “training compute ≈ 6 × parameters × training tokens” to estimate the compute behind a model, then compare your answer with Epoch AI’s database.
Write a short, jargon-free explainer of one AI safety idea (reward hacking, sycophancy, compute governance, DNA screening) for someone outside tech.
Download Epoch AI’s free dataset of notable AI models, chart training compute over time in Python, estimate how fast it grows, and count how many models cross the EU AI Act’s compute threshold.
Export controls target data-centre chips. But consumer hardware keeps getting better, and frontier-level performance reaches it within about a year. Update the analysis with the latest hardware.
