MachineSex/results/speciation_real_emergent/README.md
Giorgio Gilestro ea051a5f92 E13b/c: harden real-weight speciation — full symmetry group + emergent-divergence null
E13c (the symmetry defense): alignment now runs modulo the FULL
function-preserving unit symmetry group of a ReLU MLP (per-unit positive
rescaling via canonicalise_scale, composed with Re-Basin permutations;
sanity gate recovers a permuted-and-rescaled copy exactly). Verdict: the
full group removes the independent-init barrier (residual 0.001) and
essentially none of the conflict barrier (0.502 -> 0.497) — the residual
is functional, not a missed symmetry (answers arXiv:2606.23607). The
cliff gains a hybrid-fitness readout: merged accuracy 0.97 -> 0.03 with
conflict. Floor proposition drafted (paper/si-notes.md S1): endpoint
invariance + max(eps_A, eps_B) >= mu(S)/2 for any merged model under any
alignment group.

E13b (emergent divergence): pre-registered second reading — with NO
conflicting training signal (disjoint class specialists; rolled-input
conventions), residual is 0.000 at every divergence to t_div=3200, and
the merge RESCUES the forgetting specialists (parents 0.535/0.474 ->
merged 0.955; a sustained Fisher-Muller rescue at zero barrier).
Speciation in real weights requires functional conflict; it does not
emerge from compatible specialisation on shared ancestry. LLM-scale
over-specialisation (cf. 2607.11997) deferred to Phase-3 llm_speciation.

3-panel figure, READMEs, +2 tests (149 green), make mnist wired.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BkRLcc18rwT2Lysu6PbG7v
2026-09-06 12:35:14 +01:00

1.3 KiB
Raw Blame History

E13b — Emergent divergence (no imposed conflict): does model speciation arise spontaneously?

Companion to results/speciation_real/ (full legend and interpretation there; figure panel C of speciation_real.png). Pre-registered design: shared control, disjoint (complementary class specialists 04 vs 59), augment (same labels, inputs rolled ±3 px) — no conflicting training signal anywhere — swept over post-fork divergence t_div ∈ [100, 3200], 4 replicates, with alignment modulo the full ReLU unit symmetry group (E13c).

Outcome (the pre-registered second reading): residual barrier 0.000 at every divergence in both emergent conditions; the merged model rescues the two forgetting disjoint specialists (parents → 0.535/0.474; merge ≈ 0.955 throughout — a sustained FisherMuller rescue at zero barrier). Speciation requires functional conflict; it does not emerge from compatible specialisation on shared ancestry in this regime. An honest bound on the biological analogy, and a positive design result: merging complementary specialists of shared ancestry is safe — the danger is conflicting conventions, not specialisation. LLM-scale over-specialisation is the open tier (llm_speciation, PNAS work order Phase 3).