Biological evolution represents a cumulative process spanning approximately four billion years, during which living systems acquired progressively complex functional capabilities. Despite extensive advances in evolutionary biology, systems biology, and artificial intelli gence, no unified framework currently exists that operationalizes evolution as a sequential accumulation of functional dimensions with explicit computational checkpoints. Here we propose the Evolutionary Dimensional Pipeline (EDP) — a conceptual frame work that models biological evolution as an ordered pipeline of capability layers, begin ning with minimal self-replicating systems and extending toward complex multicellular and cognitive organisms. Each stage is defined functionally rather than taxonomically and is associated with validation criteria that may, in principle, be approximated using AI-driven models. EDP is not presented as a predictive or reconstructive claim, but as a structural scaffold for long-horizon computational biology, artificial life research, and AI-assisted evolutionary decoding.
Dmytro Ihorovych Faliush (Sat,) studied this question.