The rules, standards, and infrastructure forming around AI training and inference — and what they mean for rights holders and AI builders.
Fixed telephony connected places. Mobile communication connected people. IoT connected devices and sensors. Agents are the fourth, and they break the pattern — a device reports, but an AI agent decides, spends and negotiates on someone’s behalf. That moves identity out of the login and into liability. If operators authenticate and wallets identify, the persistent record of agency is still nobody’s job.
Read the analysis →Generative AI was built on data that already existed — the text written, the photographs taken, long before anyone thought to train on any of it. The data physical AI needs mostly does not exist yet, and has to be deliberately produced at real cost. That reframes the whole compensation argument: licensing is not a tax on model training, it is the supply chain of physical AI.
Read the analysis →On August 2, 2026, the EU AI Office gains enforcement powers over general-purpose AI: documentation demands, model evaluation, market withdrawal, and fines up to €15M or 3% of global revenue. The obligations have been law since 2025 — now they get teeth. What that means for AI companies and rights holders, including American ones.
Read the analysis →India's DPDP Act is now operational and consent-first. Its AI Governance Guidelines chose a techno-legal path built on provenance standards. And a government copyright working paper rejected free text-and-data mining as a zero-price license — proposing compensated training instead. The direction of travel: AI training as a licensable event.
Read the analysis →Free during the founding period — fingerprinted in your browser, never uploaded.
Register an assetNewsletter
Notes on the AI knowledge economy, written by the founder.
Your address goes into Alltio’s own list and nowhere else.