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Imagine there was a document that not only attempted to measure the transition to artificial general intelligence (AGI), but also decided who would be allowed to participate once it had been achieved. This is not a sci-fi script, but reality: OpenAI's internal paper on the “Five Levels of General AI Capabilities” is perhaps the most consequential text in recent AI history – precisely because it was not published.

The debate between OpenAI and Microsoft shows that it is no longer just about technology, but about institutional power relations, access rights, and economic hegemony in the age of superintelligence. When AGI becomes contractually relevant rather than hypothetical, the rules of the game shift. And not gradually, but eruptively.

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OpenAI, Microsoft and AGI

The TLDR
A leaked internal OpenAI document titled “Five Levels of General AI Capabilities” has revealed the company's specific framework for classifying when AI becomes more economically competent than humans. The document was reportedly kept private over concerns it could trigger a clause in OpenAI's contract with Microsoft, potentially cutting the software giant off from future AGI technologies and turning a scientific definition into a multi-billion dollar conflict.

“A hidden nail is currently driving into Silicon Valley's most highly praised tech partnership – and this could be a turning point for the entire AI community.”

OpenAI and Microsoft appear to be at a critical crossroads. At the center of it all is a previously unpublished internal OpenAI document titled “Five Levels of General AI Capabilities.” It attempts to systematically describe when AI can be considered “general” – i.e., when it becomes more economically competent than humans in a wide range of tasks. But it is precisely this classification that could trigger a mechanism in the contracts with Microsoft that would deny the software giant access to future AGI technology. The paper was therefore not published despite being completed in May 2024, out of concern that it could inadvertently trigger contractual consequences.

This is explosive for the AI community, as it is the first time that information has leaked out about how the threshold to AGI is conceived institutionally and described technically. This shows that we are no longer just talking hypothetically about AGI – we are negotiating its political and economic consequences in real time.

What happens when a scientific definition becomes a billion-dollar turning point? The answer to this question will determine how transparent, democratic, and accessible our AI future will be.

Why it matters: This document could be the key to making AGI measurable and contractually tangible – or it could become the basis for opacity and power struggles in the AI race.

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Do we need a unified definition of AGI?

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