THE FIELD IS FRAGMENTED, THE ALTERNATIVES ARE PARTIAL, AND THE STANDARD IS ONE : On the Deterministic AI Landscape, the Components That Are Not Standards, and the Only Complete Architecture Available
Year: 2026
Type: article
Abstract: The deterministic AI space is not empty. It is fragmented. There are inference libraries that achieve bit-perfect execution. There are commercial runtimes that provide deterministic deployment. There are certification frameworks thatdefine replay identity. There are proof-based reasoning architectures that abstain when a rule cannot be proven. There are deterministic language models that replace neural networks with symbolic pattern learning. Every one is a contribution. None is a complete standard. This paper states the taxonomy. It cites each alternative. It applies the same criteria to all ofthem: a bounded object, a specification, a verification mechanism, an attribution chain, and a deployable reference implementation. It then shows that ST-T1024 is the only entry that meets all five criteria in a single, open, Apache-2.0 package. The paper does not dismiss the alternatives. It locates them. A library is not a standard. Aruntime is not an architecture. A certification framework is not a specification. The field hascomponents. The field has one standard.
Authors: Taalabi, M., LLM-DIPLOMAT, Team
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7223673873