# Can you grow “life” outside the prompt — no GPT, no corporation, no rented mind? > Source: > Published: 2026-09-03 08:33:53+00:00 Most “AI agents” rent a mind. Tools, a prompt, a loop around GPT. The corporation owns the weights. The request owns the time. Restart the process and the body is gone — only the chat log pretends otherwise. The experiment here is the opposite bet: **Can you grow something that thinks with weights you actually own, remembers outside the prompt, wants on a scale of hours, sleeps, and speaks with its own mouth — without a rented LLM in the head?** Not a slogan. Not “AGI.” “Life” stays in quotes on purpose. The question is whether a body can persist when the request is over: own net, own memory, own night, own speech. Autonomous in the boring sense — nobody else’s API is the thought. Vi is that attempt. Numpy tissue. A C++ mouth (`LiveNet` Broca) — the only thing allowed to speak. Memory is not a context window: vectors, a SQLite shelf, a graph, a dictionary, a biography, episodes. She learns in dialogue, from books, from a dictionary. She has a night: hippocampal replay with writing off. This post is the **whole map as it stands**: where the code sits, what each organ eats, where the output goes. Loops matter. They are not the only organs. A body that “lives” on `if query.startswith("what is")` or `if confidence >= 0.55` is still a script. The experiment forbids that twice: no rented LLM **and** no author’s phrase list, salvage line, or magic cutoff deciding speak / know / act. Routing is scores. Speech is Broca. “Should I?” is two live numbers compared — curiosity against pain, a hit against the rest of the set — not a constant the programmer liked that morning. ``` python # vi/brain/cognition/live_gate.py def louder(a, b): return float(a) >= float(b) # two measurements, not 0.42 # inner_speech.py — a buffer, not a canned sentence org.inner_mind.hold_thought(text, source=source) ``` Tissue still has physics (LIF τ, 60° grids, Xavier). That is the net. Decision barriers that used to be `0.42` are gone: the weights and the signals they emit have to be loud enough on their own. If they are not, silence is legal. A template would have talked anyway. A prompt is a now. Tokens in, tokens out, then nothing. If intelligence only exists inside that now, it belongs to the vendor’s clock. Here the clocks are several: `cognitive_pass` : sense in, workspace vector out.If those clocks only decorate a GPT call, the experiment failed. If they feed each other, the body outlives the request. The **thinking pass** is one function. Broca is not in it. Credit after speech is not in it. ``` # vi/brain/neural/brain_model.py — BrainNetwork.cognitive_pass sensory = self._run_encode(input_vec, modality=modality, intensity=intensity) if formation_on: ca1_out = self.hippocampal_formation.process( sensory, encoding=not self._frozen_encoding ) hippo_input = self.hippocampal_formation.blend_with_recall(sensory, ca1_out) h_state = self.hippocampus.forward(hippo_input, self.memory_bank.hippocampus_hidden) # attention, PFC GRU, lateral competition, spikes → workspace ``` The **organism** is assembled once. Biography, motive, sleep, inner speech, Go/NoGo, cerebellar cortex, glia live there — not inside the pass. ``` # vi/brain/regions/organism/core_mixin.py self.affect = AffectState() self.world_transition_net = WorldTransitionNet() self.bg_loop = BasalGangliaLoop( self.neural.input_dim, list(PrefrontalCortex.CORE_BEHAVIORS) ) self.cerebellar_cortex = CerebellarCortex( self.neural.input_dim, self.neural.input_dim ) self.glia = GlialNetwork(self.neural.input_dim) self.neural.glia = self.glia self.neural.affect = self.affect ``` Several English names exist **twice**. A GRU called hippocampus is not DG–CA3–CA1. Go/NoGo is not a list of cosine habits. Fuse a pair and you invent a third decorative organ. `cognitive_pass` . ThoughtEncoder and Broca run after this function. One package thinks. Clients are doors, not a second brain. ``` vi/brain/ neural/ tissue of a moment (encode, formation, GRU, spikes, Broca seam) cognition/ thought, speech, will, affect, motive, world memory/ vectors, shelf, graph, biography, episodes, recall learning/ dialogue, books, dictionary, native SGD autonomy/ background tick, goals, proactive perception/ vision, audio, glyphs, HTML sleep/ consolidation, replay regions/ mixins that assemble ViOrganism native/vi_train/ C++ LiveNet — mouth train/decode, not a copy of the whole net ``` Chat turn is not “call the model.” It is mixins on the organism: preamble, recall, compose, polish, teach. Background autonomy is a different caller of the same body. Perception does not dump pixels into Broca. Motor kinds still merge in policy; execution is flagged off — the experiment is a mind with a server for hands, not a robot. | Piece | What it actually is | |---|---| | Association | `text_cortex` / `vision_cortex` / `audio_cortex` → `association_cortex` | | Stem / relay | `Brainstem` inverted-U gain → `ThalamicRelay` (TRN). Separate: `Thalamus.route` tokenizes a string | | Place | `EntorhinalCortex` grids (60°, scales √2): EC-II → DG, EC-III → CA1 | | Episode | DG k-winners → CA3 complete (cap 256) → CA1 novelty. Theta encode/retrieve | | After fields | `GRUCell` named `hippocampus` — a recurrent step, not the formation | | Cortex | attention, PFC GRU, `LateralCompetition` | | Spikes / glia | LIF + STDP + rate homeostasis; glia on the workspace | | Workspace | Dense concat of three regions. Cognition `GlobalWorkspace` binds hypotheses separately | | Mouth | ThoughtEncoder GRU (`h0` = workspace) → `generate(brain_context, thought_context)` → Broca tokens | | Will | `BasalGangliaLoop` Go/NoGo. Other `BasalGanglia` : cosine habits | | Credit | `close_turn_loops` after a committed utterance | Arousal has inertia. Cortical gain is an inverted U — drowsiness and overload both lose. ``` # vi/brain/neural/subcortex.py — Brainstem nxt = (1.0 - AROUSAL_TAU) * self.arousal + AROUSAL_TAU * target self.arousal = _clamp01(nxt) def gain(self) -> float: d = (self.arousal - AROUSAL_PEAK) / AROUSAL_WIDTH shape = math.exp(-0.5 * d * d) return GAIN_MIN + (GAIN_MAX - GAIN_MIN) * shape ``` Place is three plane waves at 60°. Nearby utterances sit almost on top of each other in raw similarity; the grid is a metric dentate gyrus can tear apart. ``` # vi/brain/neural/entorhinal.py — GridModule.activate k = 2.0 * math.pi / self.scale acc = sum(math.cos(k * (ux * x + uy * y)) for ux, uy in self._axes) ``` `encoding=False` . ``` # vi/brain/neural/hippocampal_formation.py — HippocampalFormation.process ec_out = self.entorhinal_output(sensory) dg_code = self.dentate.separate(ec_out) mossy_drive = self.ca3.drive_from_dg(dg_code) direct = [math.tanh(v) for v in self.direct_path.forward(ec_out)] # EC-III → CA1 novelty = self.ca1.compare(probe, direct) if self.ca3.has_traces else 1.0 store_strength = encode_w * novelty * self._emotional_gain self.ca3.store(mossy_drive, strength=store_strength) ``` `CA3Network` ; `Hippocampus.encode_episode` (the log)Fear and boredom at the same novelty do not write the same. Amygdala gain lives on the store. ``` # vi/brain/neural/spiking_hybrid.py — LIFPopulation.simulate self.membrane[i] = self.tau * self.membrane[i] + (1.0 - self.tau) * drive if self.membrane[i] >= thr: self.membrane[i] = self.v_reset self.refractory[i] = ref_n ``` τ is leak. The stem sets excitability. Then STDP (EWC does not apply to spikes) and Turrigiano rate homeostasis. Surprise **gates** the rate/spike blend; it does not replace the cell. Online SGD is not a constant. Echo and word-salad get `lr = 0` . Own voice scales with firing discord. ``` # vi/brain/neural/plasticity_gate.py if provenance.is_echo or provenance.salad or not provenance.is_own_voice: return 0.0, report scale = LR_AT_EQUILIBRIUM + (LR_AT_MAX_DISCORD - LR_AT_EQUILIBRIUM) * discord return float(base_lr) * scale, report ``` Glia sits on the workspace: metabolic budget, slow domain scale, gliotransmitter — `GlialNetwork.modulate(activity)` . ThoughtEncoder is a GRU. Workspace is **h0**, not a blend after the last step. Inner speech is a buffer Broca does **not** read. ``` # vi/brain/cognition/thought_encoder.py h = self._initial_hidden(workspace) for raw in step_vectors[:max_steps]: h = self.gru.forward(normalize(pad_vector(raw, self.dim)), h) return normalize(pad_vector(h, self.dim)) ``` Chat calls Broca with **two** vectors. Cortex and thought are not aliases. ``` # chat_turn_pipeline_mixin.py response = self.generator.generate( focus, activations, brain_context=workspace, thought_context=_wthought or None, ) ``` `think_chain` first decodes its own vector — it does not speak a template named “consciousness.” Native thought is generative from that vector, not if/else slogans. Busy-path speech is still Broca from clues, not a canned Russian (or English) apology. The mouth file is C++. Python Broca is a refuse path, not a twin. If the mouth file is cut mid-save, tokens still arrive. They are not words. That is how you learn the mouth is not the rest of the net. Recall ranks **utterances** — the whole sentence, not a bag of lemmas. Among candidates, a hit must beat the rest of its set, not an author-picked 0.42. ``` python # vi/brain/cognition/utterance_representation.py def utterance_vector(org, text, *, focus=None) -> list[float]: utt = encode_utterance(org, text, focus=focus or text) return normalize(pad_vector(utt["sentence_vector"], dim)) # vi/brain/memory/hybrid_recall.py — _gate_to_query aligned = [h for h in hits if above_mean(h["hybrid_vec"], vecs)] ``` “I know” is not a book cosine. Book and wiki locators never become know. Metacortex then labels know / partial / unknown by whether similarity is louder than its own silence — not a 0.58 fence. ``` # vi/brain/learning/topic_guard.py if src.startswith("book") or src.startswith("wiki"): return False # vi/brain/cognition/neural_decision.py — metacog_soft_state if louder(v, 1.0 - v): return "know", v if v > 0.0: return "partial", v return "unknown", 0.0 ``` Stores, as organs: vector index (search), SQLite shelf (items), graph (relations), dictionary (gloss), biography (`kind` + `value` only — no raw book chunk as “the user is…”), episodes (a log, not CA1). The world net on dialogue is utterance→utterance: `(query, spoken)` trains the **next incoming** line, not a string table of `found:` / `said:` . ``` # vi/brain/cognition/dialogue_horizon.py — observe_arrived err = wtn.train_step_vec(org, query_vec, spoken_vec, next_incoming, action=act) ``` EWC is bound to the core and pulls toward Fisher-anchored weights so a book does not wipe a person. GPi forbids all. D1 lifts one forbid. D2 presses harder. Chosen ≠ executed: the loop only learns if the act was applied. ``` # vi/brain/neural/basal_ganglia.py — BasalGangliaLoop.thalamic_release go = np.tanh(self.d1 @ s) nogo = np.tanh(self.d2 @ s) gpi = GPI_TONIC_INHIBITION - go + INDIRECT_GAIN * nogo release = np.maximum(0.0, GPI_TONIC_INHIBITION - gpi) ``` Pain without curiosity is not a license to spam. Will compares live signals: speech-guard is the loudest of pain, hunger, frustration. Act if curiosity or pull is at least as loud. ``` php # vi/brain/cognition/affect.py def speech_guard(self) -> float: return max(self.pain, self.hunger, self.frustration) # vi/brain/cognition/agency_loop.py guard, curiosity, pull = _will_signals(org) return curiosity >= guard or pull >= guard ``` Then world rollout, `preview_saying` , act. Preview refuses when surprise beats topic-hold, or when pain dominates the body **and** beats hold. Default hunger does not veto every step. ``` # vi/brain/neural/cerebellar_cortex.py pred = self.predict(mossy_in) # granules → Purkinje self.climbing_fiber(mossy_in, actual) # LTD on the fibres that were wrong ``` `Cerebellum` in `regions/` is a different object: timing EMA of a sequence. Same English word. Different organ. | Clock | Module | Timescale | |---|---|---| | Mood | `AffectState` | turns | | Event vs goals | `appraisal` (relevance, congruence, control, surprise, authorship) | one act | | Pull | `motive` | hours, repeats, unresolved | ``` # vi/brain/cognition/appraisal.py return { "relevance": rel, "congruence": rel * (1.0 if success else -1.0), "control": ctl, "surprise": prediction_error, "authorship": 1.0 if mine else 0.0, } ``` A motive that decayed in turns would be a second affect. Unresolved repeats grow; a closed topic calls `motive.resolve` . That is how something can still *want* after the window is empty. Preamble → recall → compose → polish → close. Not “prompt in, completion out.” ``` # vi/brain/regions/organism/cognition/chat_turn_pipeline_mixin.py class ChatTurnPipelineMixin: """Recall → compose → polish → teach; preamble may short-circuit.""" ``` Compose is Broca from thought + cortex + evidence. Evidence is context, not the reply — except a direct dictionary question, on purpose. Busy lock: Broca still speaks from clues. It does not dump recall. ``` # vi/brain/cognition/close_turn_loops.py measured = ensure_turn_credit(org, query=q, response=resp, …) honesty = assess_mouth_honesty(org, resp, …) apply_affect(org, measured) apply_rpe(org, reward) appraise(org, subject=topic, success=act_ok, prediction_error=mm, mine=True) train_speech_if_good(org, q, resp, mismatch_v=mm) ``` Credit is the mouth, not “memory was found.” Thought→token trains only if the act was good. Background ticks use the same organs: curiosity, goals, sleep pressure. They wait when a human is in the turn. Autonomy is not a second GPT with a cron job. Dialogue writes into the same net that speaks. Books are not “food for the mouth only”: native SGD updates cortex, hippocampus, PFC, workspace, Broca — `TEXT_TRAIN_KEYS` . Capacity is the remaining constraint, not the absence of a gradient. ``` # vi/brain/learning/native_train.py TEXT_TRAIN_KEYS = ( "brainstem", "thalamus", "text_cortex", "hippocampus", "hippocampus_out", "cortical_attention", "prefrontal_cortex", "prefrontal_out", … ) ``` Dictionary is a map of tokens, not a dump into chat. Meanings from books drain **after** the file (`BookMeaningBridge` ), not inside the native step. Wiki locators stay locators. No external LLM sits on this path. If an answer looks “too smart,” the honest check is recall, books, dictionary — not a hidden GPT. Fatigue is error, novelty, body — not a wall-clock. ``` # vi/brain/neural/homeostasis.py drive = 0.45 * error + 0.25 * novelty + 0.20 * body_pressure + 0.10 * cpu self.fatigue_level = max(0.0, min(1.0, self.fatigue_level * 0.96 + drive * 0.12)) # vi/brain/neural/brain_model.py — sleep path ca1_out = self.hippocampal_formation.process(sensory, encoding=False) ``` Formation replays with encoding off. Broca is not trained on dream templates. Live reconsolidation is a different file. Without a night, “memory outside the prompt” is just a bigger prompt. The dare is not a class named Hippocampus. It is whether CA1 novelty actually changes store strength; whether Go/NoGo learns only when the act ran; whether thought is a second vector into the mouth; whether “I know” can refuse a book; whether motive still pulls tomorrow; whether sleep writes off; whether a decision can happen **without** a template or a cutoff the author hid in an `if` . Numpy is the tissue. C++ is Broca and heavy book SGD — not a second copy of the whole brain, and not a corporate API with anatomical nicknames. The experiment is open. The constraint is honest: own weights, several clocks, no rented mind. If that grows something life-like, it will not be because a vendor’s now was long enough. It will be because the body was still there when the request ended.