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EU AI Act Obligations for General-Purpose AI Models
Technique
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The EU AI Act treats a general-purpose AI model as systemic-risk when it has high-impact capabilities or the Commission designates it for equivalent capabilities or impact.
More than 10^25 training FLOP creates a presumption of high-impact capability, not an unchallengeable classification; systemic-risk providers have extra evaluation, risk-management, incident-reporting, and cybersecurity duties.
The AI Act’s systemic-risk category is a subset of general-purpose AI models. Article 51 provides two routes: a model has high-impact capabilities assessed with appropriate tools, indicators, and benchmarks; or the Commission designates it because capabilities or impact are equivalent, using Annex XIII criteria. Training compute above 10^25 floating-point operations creates a presumption of high-impact capability. The number is a threshold in the law and is subject to delegated adjustment; it is not the only way to qualify. Article 52 requires a provider whose model meets the compute condition to notify the Commission without delay, and no later than two weeks after the condition is met or it becomes known that it will be met. The provider may submit substantiated arguments that the model does not, due to its specific characteristics, present systemic risks. The Commission can reject that case or designate a model on its own initiative or following a qualified scientific-panel alert. Commission guidelines describe its interpretation and enforcement approach but are not binding law. Article 55 adds four duties beyond the general GPAI requirements: standardized model evaluation, including documented adversarial testing; assessment and mitigation of possible systemic risks at Union level; documentation and reporting of serious incidents and corrective measures; and adequate cybersecurity for both model and physical infrastructure. These duties are not waived just because a model is distributed under a free and open-source license. Providers can rely on an approved code or harmonised standards while available, or demonstrate alternative adequate means for Commission assessment. GPAI obligations began applying on August 2, 2025. The Commission’s guidance states that its enforcement powers apply from August 2, 2026, and qualifying models already on the market before August 2, 2025 have a compliance transition until August 2, 2027. Providers should track training-compute evidence, expected threshold timing, notification, and any designation decision. This is an overview, not a legal opinion on an individual model.
Les décisions en matière d'architecture déterminent les performances et les coûts d'exploitation pendant des années.
La formation technique aide les équipes à choisir la bonne pile, pas seulement la plus récente.
De meilleurs choix d’ingénierie réduisent les incidents de fiabilité en production.
The Act empowers the Commission to revise compute thresholds and benchmarks as capabilities and hardware efficiency evolve. A provider should not assume today’s FLOP threshold will remain fixed or that falling below it resolves designation risk. Monitor official Commission guidelines and any delegated acts, and review status when a model’s training run, capabilities, distribution, or deployment context changes. Track delegated updates to Annex XIII and any official changes to the compute presumption. Document threshold calculations consistently across training runs. Review changes before each release.
A provider forecasts training compute above 10^25 FLOP and prepares the Article 52 notification before the threshold is reached.
A provider crossing the threshold submits evidence with its notification explaining why the model’s specific capabilities do not create systemic risk.
A safety team documents adversarial testing, EU-level risk assessments, incident response, and infrastructure security for a designated model.
A company with an open-source systemic-risk model checks Article 55 duties rather than assuming Article 53’s limited exception covers it.
L’optimisation d’un benchmark peut masquer des faiblesses plus larges du système.
Les coûts d’infrastructure et de maintenance sont souvent sous-estimés.
Les lacunes en matière de sécurité et d’observabilité peuvent se creuser à mesure que les systèmes deviennent plus complexes.
Définissez les objectifs de latence, de qualité et de coût avant la mise en œuvre.
Benchmark dans des conditions de charge et de données réalistes.
Surveillance des instruments pour détecter les erreurs, la dérive et l'impact sur l'utilisateur.
Préparez les chemins de restauration et de réponse aux incidents avant la mise à l’échelle.
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The EU AI Act treats a general-purpose AI model as systemic-risk when it has high-impact capabilities or the Commission designates it for equivalent capabilities or impact. More than 10^25 training FLOP creates a presumption of high-impact capability, not an unchallengeable classification; systemic-risk providers have extra evaluation, risk-management, incident-reporting, and cybersecurity duties.
Article 51(2) presumes high-impact capabilities above the compute threshold, while Article 51 and 52 allow other evidence and procedures.
Article 51(1)(b) and Article 52(4) allow Commission designation based on equivalent capabilities or impact using Annex XIII criteria.
Article 52(1) requires notice without delay and no later than two weeks after the condition is met or known to be expected.
Article 55(1)(a) requires model evaluation under state-of-the-art protocols, including documented adversarial testing.
Article 55(1)(c) requires tracking, documenting, and reporting serious-incident information and possible corrective measures.
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EU AI Act Obligations for General-Purpose AI Models
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