Minimal Sufficiency: A Principle 'Similar' to End-to-End (cacm.acm.org)

Researchers Tatipamula and Vinton Cerf urge the AI/ML community to build a shared, interoperable stack of standard services—analogous to the Internet protocol suite—to accelerate ecosystem growth. Micah Beck responds by proposing a formal design principle he calls minimal sufficiency and a unified infrastructure model, the Exposed Buffer Architecture (EBA), that extends beyond networking to include storage and processing. Minimal sufficiency frames service specifications as logical theories ordered by “no weaker than” (logical strength): given two services that can both implement the same applications, prefer the weaker specification because it makes fewer commitments and is more likely to be widely adopted. Beck ties this to the Hourglass Theorem, which explains why a narrow, weak common layer promotes voluntary adoption and interoperability. Technically, minimal sufficiency treats service specs as a partial order—many specifications are incomparable—so the approach helps compare closely related variants but doesn’t fully resolve trade-offs like performance, security, or practical simplicity. EBA is presented as an application of the principle: factorize AI/ML cloud services into weaker, reusable primitives for networking, storage, and computation to produce a “least common divisor” basis for interoperability. Beck argues this formalism captures important aspects of the end-to-end intuition while offering a precise framework for designing next-generation AI/ML infrastructure, though he cautions it’s an incomplete tool and must be balanced with real-world constraints.