// SPDX-License-Identifier: Apache-2.0 // © 2026 Lutar, Stephen P. — SZL Holdings · ORCID 0009-0001-0110-4173 · Doctrine v11 // // surfaces/testtime.js — TEST-TIME-COMPUTE / REASONING-SCALING-LAWS organ for the // holographic frontier ring. The THIRD scaling axis (alongside pretrain scaling and // post-train scaling): how much extra INFERENCE-time compute buys how much accuracy. // // Renders two 3D growing curves driven by a live closed-form snapshot from // /api/killinchu/v1/testtime/scaling: // 1. pass@N (best-of-N / repeated-sampling coverage) — a curve that climbs across // N = 1,2,4,...,256 parallel samples. // 2. sequential revision accuracy vs number of reasoning/revision steps — a curve // with diminishing returns as k grows. // A HUD shows accuracy climbing as compute (N / steps) increases, plus the derived // scaling_exponent and effective_oom_multiplier. Honesty label "MODELED" is read // VERBATIM from the JSON and displayed as-is; it is never upgraded. // // Surface export shape (mirrors neuromorphic.js / interpretability.js exactly): // export default { id, title, endpoints, mount(ctx), unmount() } // ctx = { stage, container, live, label, THREE, szl3d } // // DATA SHOWN (all from live endpoint): // base_accuracy, N_samples, pass_at_N, pass_at_N_curve[] // sequential_steps, revised_accuracy, revised_accuracy_curve[] // scaling_exponent, effective_oom_multiplier // // LEADERS ADOPTED & CITED (clean-room; NOT claimed as SZL's own): // DeepSeek-R1 (RL reasoning / long CoT): DeepSeek-AI et al. 2025, arXiv:2501.12948 // https://arxiv.org/abs/2501.12948 // Scaling LLM Test-Time Compute Optimally: Snell et al. 2024, arXiv:2408.03314 // https://arxiv.org/abs/2408.03314 // Large Language Monkeys (repeated sampling / pass@N): Brown et al. 2024, arXiv:2407.21787 // https://arxiv.org/abs/2407.21787 // // HONESTY LABELS: MODELED (closed-form scaling-law simulation; no LLM calls, no live // model eval). Read verbatim from JSON; never upgraded here. // COLOURS: lattice-blue 0x5b8dee (pass@N curve), violet-blue 0x8a6bff (revision curve), // proof-teal 0x3af4c8 (HUD accent / rising-compute marker). Purple BANNED as UI/background. // 0 RUNTIME CDN. Vendored three.js r170 via page importmap. // DOCTRINE v11: degrades gracefully (grey) on 404/error; honesty label still shown. // Nothing here is in the locked-8. Λ stays Conjecture 1. Trust never 100%. const ID = "testtime"; const TITLE = "Test-Time Compute · Reasoning-Scaling Laws (live)"; // Endpoint is hosted on the dedicated killinchu Space (isolated compute), reached // cross-origin (killinchu returns access-control-allow-origin: https://a-11-oy.com). // This keeps the test-time-compute organ's rebuilds/faults isolated from the flagship. const EP = "https://szlholdings-killinchu.hf.space/api/killinchu/v1/testtime/scaling?seed=42&p=0.2&N=64&steps=8"; // data-viz hues — purple BANNED const C_PASSN = 0x5b8dee; // lattice-blue (pass@N curve) const C_REVISE = 0x8a6bff; // violet-blue (sequential revision curve — data-viz only) const C_DIM = 0x42505d; // grey (degraded / no-live-data) const C_ACCENT = 0x3af4c8; // proof-teal accent (HUD / rising-compute marker) const C_GRID = 0x1b3a44; // floor / link colour // curve layout geometry const CURVE_LEN = 10.0; // world-units along X (compute axis, log-spaced) const CURVE_DEPTH = 3.0; // world-units separating the two curve lanes (Z) const CURVE_HEIGHT= 5.0; // world-units of max curve rise (Y, accuracy axis) let _stage = null, _THREE = null, _ctx = null, _group = null, _overlay = null; let _frameReg = false, _polls = [], _el = {}, _badge = null; let _plain = false; // geometry handles let _passLine = null; // THREE.Line — pass@N growing curve let _passDots = []; // Array — markers along pass@N curve let _revLine = null; // THREE.Line — sequential-revision growing curve let _revDots = []; // Array — markers along revision curve let _marker = null; // THREE.Mesh — HUD "current compute" marker (pulses) let _floor = null; // live state const S = { label: null, baseAcc: null, // base_accuracy N: null, // N_samples passAtN: null, // pass_at_N passCurve: null, // pass_at_N_curve[] steps: null, // sequential_steps revAcc: null, // revised_accuracy revCurve: null, // revised_accuracy_curve[] scalingExp: null, // scaling_exponent effOom: null, // effective_oom_multiplier state: "init", }; // ============================================================================= // mount(ctx) // ============================================================================= export function mount(ctx) { _ctx = ctx; _stage = ctx.stage; _THREE = ctx.THREE; _group = new _THREE.Group(); _stage.scene.add(_group); _stage.camera.position.set(2, 8, 20); try { if (_stage.controls && _stage.controls.target) { _stage.controls.target.set(2, 2.5, 0); _stage.controls.update(); } } catch (_) {} try { _stage.setBloom(true); } catch (_) {} _buildFloor(); _buildCurves(); _buildMarker(); if (!_frameReg) { _stage.onFrame(_onFrame); _frameReg = true; } _badge = ctx.live.createBadge(); _polls.push(ctx.live.poll(EP, 5000, _onScaling, { badge: _badge, onState: (m) => { S.state = m.state; _paintOverlay(); } })); _buildOverlay(); return { id: ID, started: true }; } // ============================================================================= // builders // ============================================================================= function _buildFloor() { const THREE = _THREE; const grid = new THREE.GridHelper(40, 40, C_GRID, 0x0f2027); grid.material.opacity = 0.18; grid.material.transparent = true; grid.position.y = -0.01; _group.add(grid); _floor = grid; } // Pre-allocate curve line geometries with a fixed max point-count; we update // point positions in-place as live data arrives (no per-poll geometry churn). const _MAX_PTS = 16; function _buildCurves() { const THREE = _THREE; // pass@N curve lane (Z = 0) { const pts = new Array(_MAX_PTS).fill(0).map(() => new THREE.Vector3(0, 0, 0)); const geo = new THREE.BufferGeometry().setFromPoints(pts); const mat = new THREE.LineBasicMaterial({ color: C_PASSN, transparent: true, opacity: 0.85, linewidth: 2 }); _passLine = new THREE.Line(geo, mat); _group.add(_passLine); const dotGeo = new THREE.SphereGeometry(0.09, 10, 8); for (let i = 0; i < _MAX_PTS; i++) { const m = new THREE.Mesh(dotGeo, new THREE.MeshStandardMaterial({ color: C_PASSN, emissive: C_PASSN, emissiveIntensity: 0.3 })); m.visible = false; _group.add(m); _passDots.push(m); } } // sequential-revision curve lane (Z = CURVE_DEPTH) { const pts = new Array(_MAX_PTS).fill(0).map(() => new THREE.Vector3(0, 0, CURVE_DEPTH)); const geo = new THREE.BufferGeometry().setFromPoints(pts); const mat = new THREE.LineBasicMaterial({ color: C_REVISE, transparent: true, opacity: 0.85, linewidth: 2 }); _revLine = new THREE.Line(geo, mat); _group.add(_revLine); const dotGeo = new THREE.SphereGeometry(0.09, 10, 8); for (let i = 0; i < _MAX_PTS; i++) { const m = new THREE.Mesh(dotGeo, new THREE.MeshStandardMaterial({ color: C_REVISE, emissive: C_REVISE, emissiveIntensity: 0.3 })); m.visible = false; _group.add(m); _revDots.push(m); } } // baseline axes (compute axis + accuracy axis ticks), grey, data-viz only const axisPts = [ new THREE.Vector3(0, 0, -0.6), new THREE.Vector3(0, CURVE_HEIGHT, -0.6), // accuracy axis new THREE.Vector3(0, 0, -0.6), new THREE.Vector3(CURVE_LEN, 0, -0.6), // compute axis ]; const axisGeo = new THREE.BufferGeometry().setFromPoints(axisPts); const axisLine = new THREE.LineSegments(axisGeo, new THREE.LineBasicMaterial({ color: C_GRID, transparent: true, opacity: 0.4 })); _group.add(axisLine); } function _buildMarker() { const THREE = _THREE; _marker = new THREE.Mesh( new THREE.IcosahedronGeometry(0.22, 1), new THREE.MeshStandardMaterial({ color: C_ACCENT, emissive: C_ACCENT, emissiveIntensity: 0.5, wireframe: true, transparent: true, opacity: 0.85 }), ); _marker.position.set(0, 0, 0); _group.add(_marker); } // ============================================================================= // live data handler // ============================================================================= function _onScaling(j) { // read honesty label VERBATIM — never upgrade S.label = (j.label || "MODELED").toUpperCase(); S.baseAcc = typeof j.base_accuracy === "number" ? j.base_accuracy : null; S.N = typeof j.N_samples === "number" ? j.N_samples : null; S.passAtN = typeof j.pass_at_N === "number" ? j.pass_at_N : null; S.passCurve = Array.isArray(j.pass_at_N_curve) ? j.pass_at_N_curve : null; S.steps = typeof j.sequential_steps === "number" ? j.sequential_steps : null; S.revAcc = typeof j.revised_accuracy === "number" ? j.revised_accuracy : null; S.revCurve = Array.isArray(j.revised_accuracy_curve) ? j.revised_accuracy_curve : null; S.scalingExp = typeof j.scaling_exponent === "number" ? j.scaling_exponent : null; S.effOom = typeof j.effective_oom_multiplier === "number" ? j.effective_oom_multiplier : null; _updateCurves(); _paintOverlay(); } // ============================================================================= // geometry updater — drives the two growing curves from live data // ============================================================================= function _logX(n, nMax) { // log-spaced compute axis: n=1 -> x=0, n=nMax -> x=CURVE_LEN const lo = Math.log10(Math.max(1, 1)); const hi = Math.log10(Math.max(2, nMax)); const v = Math.log10(Math.max(1, n)); return CURVE_LEN * (v - lo) / Math.max(1e-6, (hi - lo)); } function _linX(k, kMax) { return CURVE_LEN * (k / Math.max(1, kMax)); } function _updateCurves() { const THREE = _THREE; const live = S.state === "live"; // --- pass@N curve --- if (live && S.passCurve && S.passCurve.length) { const nMax = S.passCurve.reduce((m, r) => Math.max(m, r.n), 1); const pos = _passLine.geometry.attributes.position; const n = Math.min(_MAX_PTS, S.passCurve.length); for (let i = 0; i < _MAX_PTS; i++) { if (i < n) { const row = S.passCurve[i]; const x = _logX(row.n, nMax); const y = row.pass_at_n * CURVE_HEIGHT; pos.setXYZ(i, x, y, 0); _passDots[i].position.set(x, y, 0); _passDots[i].visible = true; } else { // repeat last point so the line doesn't dangle at origin const row = S.passCurve[n - 1]; const x = _logX(row.n, nMax); const y = row.pass_at_n * CURVE_HEIGHT; pos.setXYZ(i, x, y, 0); _passDots[i].visible = false; } } pos.needsUpdate = true; _passLine.geometry.computeBoundingSphere(); _passLine.material.color.setHex(C_PASSN); _passLine.material.opacity = 0.85; } else { _passDots.forEach((d) => { d.visible = false; }); _passLine.material.color.setHex(C_DIM); _passLine.material.opacity = 0.25; } // --- sequential-revision curve --- if (live && S.revCurve && S.revCurve.length) { const kMax = S.revCurve.reduce((m, r) => Math.max(m, r.k), 1); const pos = _revLine.geometry.attributes.position; const n = Math.min(_MAX_PTS, S.revCurve.length); for (let i = 0; i < _MAX_PTS; i++) { if (i < n) { const row = S.revCurve[i]; const x = _linX(row.k, kMax); const y = row.revised_accuracy * CURVE_HEIGHT; pos.setXYZ(i, x, y, CURVE_DEPTH); _revDots[i].position.set(x, y, CURVE_DEPTH); _revDots[i].visible = true; } else { const row = S.revCurve[n - 1]; const x = _linX(row.k, kMax); const y = row.revised_accuracy * CURVE_HEIGHT; pos.setXYZ(i, x, y, CURVE_DEPTH); _revDots[i].visible = false; } } pos.needsUpdate = true; _revLine.geometry.computeBoundingSphere(); _revLine.material.color.setHex(C_REVISE); _revLine.material.opacity = 0.85; } else { _revDots.forEach((d) => { d.visible = false; }); _revLine.material.color.setHex(C_DIM); _revLine.material.opacity = 0.25; } // --- HUD marker: sits at the current (N, pass@N) point, pulses proof-teal --- if (_marker) { if (live && S.passAtN != null && S.N != null && S.passCurve && S.passCurve.length) { const nMax = S.passCurve.reduce((m, r) => Math.max(m, r.n), 1); const x = _logX(S.N, nMax); const y = S.passAtN * CURVE_HEIGHT; _marker.position.set(x, y, 0); _marker.material.color.setHex(C_ACCENT); _marker.material.emissive.setHex(C_ACCENT); _marker.material.opacity = 0.85; } else { _marker.material.color.setHex(C_DIM); _marker.material.emissive.setHex(C_DIM); _marker.material.opacity = 0.3; } } } // ============================================================================= // per-frame animation // ============================================================================= function _onFrame() { const t = performance.now(); if (_group) _group.rotation.y = Math.sin(t * 0.00010) * 0.15; if (_marker) { _marker.rotation.y += 0.02; _marker.rotation.x += 0.01; const pulse = 1.0 + 0.15 * Math.sin(t * 0.004); _marker.scale.setScalar(pulse); } } // ============================================================================= // overlay // ============================================================================= function _buildOverlay() { const ctx = _ctx; _overlay = document.createElement("div"); Object.assign(_overlay.style, { position: "absolute", left: "14px", top: "14px", zIndex: "6", display: "flex", flexDirection: "column", gap: "8px", maxWidth: "min(94%,440px)", font: "12px ui-sans-serif,system-ui,Segoe UI,Roboto,Arial", color: "#eef3f6", }); const h = document.createElement("div"); h.style.cssText = "font:600 13px ui-sans-serif,system-ui;letter-spacing:.4px"; h.textContent = TITLE; _overlay.appendChild(h); const sub = document.createElement("div"); sub.style.cssText = "color:#9fb1bf;font-size:11px;line-height:1.55"; sub.innerHTML = 'The third scaling axis (alongside pretrain and post-train): spend more ' + 'inference-time compute \u2014 parallel repeated sampling (pass@N) or ' + 'sequential reasoning steps \u2014 and trade it for accuracy. Honesty label ' + 'MODELED (closed-form scaling law; no LLM calls, no live model eval). 0 runtime CDN.'; _overlay.appendChild(sub); const brow = document.createElement("div"); brow.style.cssText = "display:flex;gap:8px;align-items:center;flex-wrap:wrap"; if (_badge && _badge.el) brow.appendChild(_badge.el); _overlay.appendChild(brow); const card = document.createElement("div"); card.style.cssText = "background:#0a1117;border:1px solid #1d2a36;border-radius:9px;padding:9px 10px;display:flex;flex-direction:column;gap:6px"; const chead = document.createElement("div"); chead.style.cssText = "display:flex;align-items:center;gap:8px;flex-wrap:wrap"; const dot = document.createElement("span"); dot.style.cssText = "width:9px;height:9px;border-radius:50%;background:#5b8dee;box-shadow:0 0 7px #5b8dee"; const nm = document.createElement("b"); nm.style.cssText = "font-size:12px;color:#5b8dee;letter-spacing:.3px"; nm.textContent = "test-time-compute"; chead.appendChild(dot); chead.appendChild(nm); card.appendChild(chead); const grid = document.createElement("div"); grid.style.cssText = "display:grid;grid-template-columns:1fr;gap:4px"; function kpiRow(id, label) { const r = document.createElement("div"); r.style.cssText = "display:flex;justify-content:space-between;gap:10px;font-size:11px"; const l = document.createElement("span"); l.style.cssText = "color:#9fb1bf"; l.textContent = label; const v = document.createElement("b"); v.id = id; v.style.cssText = "font-variant-numeric:tabular-nums;color:#eef3f6;text-align:right;max-width:58%"; v.textContent = "\u2014"; _el[id] = v; r.appendChild(l); r.appendChild(v); return r; } grid.appendChild(kpiRow("tt-base", "base accuracy p")); grid.appendChild(kpiRow("tt-n", "N samples (parallel compute)")); grid.appendChild(kpiRow("tt-passn", "pass@N \u2014 MODELED")); grid.appendChild(kpiRow("tt-steps", "sequential steps k")); grid.appendChild(kpiRow("tt-rev", "revised accuracy \u2014 MODELED")); grid.appendChild(kpiRow("tt-exp", "scaling exponent")); grid.appendChild(kpiRow("tt-oom", "effective compute (orders of magnitude)")); grid.appendChild(kpiRow("tt-label", "honesty label")); card.appendChild(grid); const fn = document.createElement("div"); fn.style.cssText = "font-size:9.5px;color:#6b7a86;line-height:1.5"; fn.textContent = "DeepSeek-R1, DeepSeek-AI et al. arXiv:2501.12948 \u00b7 Snell et al. arXiv:2408.03314 (optimal test-time compute) \u00b7 Brown et al. arXiv:2407.21787 (Large Language Monkeys / pass@N). MODELED \u00b7 not claimed-as."; card.appendChild(fn); _overlay.appendChild(card); const pl = document.createElement("button"); pl.textContent = "\u25d1 what this means"; pl.title = "Toggle plain-language explanation for investors & consumers."; pl.style.cssText = "font:11px ui-monospace,monospace;padding:5px 11px;border-radius:7px;border:1px solid #3af4c8;background:#08140f;color:#3af4c8;cursor:pointer;width:fit-content"; pl.addEventListener("click", () => { _plain = !_plain; pl.style.background = _plain ? "#0f2a20" : "#08140f"; _applyPlain(); }); _overlay.appendChild(pl); const pd = document.createElement("div"); pd.id = "tt-plain"; pd.style.cssText = "font-size:10.5px;color:#c9d6df;line-height:1.55;border:1px dashed #26333f;border-radius:7px;padding:7px 9px;display:none"; _el["plain"] = pd; _overlay.appendChild(pd); (ctx.container || document.body).appendChild(_overlay); _paintOverlay(); } function _applyPlain() { const pd = _el["plain"]; if (!pd) return; pd.style.display = _plain ? "block" : "none"; if (!_plain) return; const n = S.N != null ? String(S.N) : "loading\u2026"; const pAtN = S.passAtN != null ? (S.passAtN * 100).toFixed(2) + "%" : "loading\u2026"; const steps= S.steps != null ? String(S.steps) : "loading\u2026"; const rAcc = S.revAcc != null ? (S.revAcc * 100).toFixed(2) + "%" : "loading\u2026"; pd.innerHTML = "What this means: Instead of training a bigger model, you can spend more " + "compute at answer time. Drawing " + n + " independent samples and " + "keeping the best one (\u201cbest-of-N\u201d) pushes the chance of getting a correct " + "answer to " + pAtN + ". Letting the model take " + steps + " sequential " + "reasoning/revision steps instead pushes accuracy to " + rAcc + ", but with " + "diminishing returns \u2014 each extra step helps less than the last. " + "Plain: this is the third lever for making AI smarter \u2014 next to \u201ctrain a bigger " + "model\u201d and \u201cfine-tune it more\u201d, you can also just let it \u201cthink longer\u201d " + "at inference time. This view is a MODELED closed-form scaling law, not a live " + "model evaluation."; } function _tok(s) { if (s === "live") return null; if (s === "missing") return "NO-LIVE-DATA"; if (s === "degraded") return "DEGRADED"; if (s === "error") return "OFFLINE"; return "\u2026"; } function fx(v, d) { return typeof v === "number" ? v.toFixed(d) : "\u2014"; } function pct(v, d) { return typeof v === "number" ? (v * 100).toFixed(d) + "%" : "\u2014"; } function _set(id, v) { if (_el[id]) _el[id].textContent = v; } function _paintOverlay() { const t = _tok(S.state); _set("tt-base", t || pct(S.baseAcc, 2)); _set("tt-n", t || (S.N != null ? String(S.N) : "\u2014")); _set("tt-passn", t || pct(S.passAtN, 4)); _set("tt-steps", t || (S.steps != null ? String(S.steps) : "\u2014")); _set("tt-rev", t || pct(S.revAcc, 4)); _set("tt-exp", t || fx(S.scalingExp, 6)); _set("tt-oom", t || fx(S.effOom, 3)); // honesty label verbatim — never upgraded _set("tt-label", t || (S.label || "MODELED")); if (_plain) _applyPlain(); } // ============================================================================= // unmount — clean up everything; must not affect other organs // ============================================================================= export function unmount() { _polls.forEach((p) => { try { p.stop(); } catch (_) {} }); _polls = []; try { if (_overlay && _overlay.parentNode) _overlay.parentNode.removeChild(_overlay); } catch (_) {} try { if (_group && _stage) { _group.traverse((o) => { if (o.geometry && o.geometry.dispose) o.geometry.dispose(); if (o.material) { const ms = Array.isArray(o.material) ? o.material : [o.material]; ms.forEach((m) => { if (m.dispose) m.dispose(); }); } }); _stage.scene.remove(_group); } } catch (_) {} _group = _overlay = null; _passLine = null; _passDots = []; _revLine = null; _revDots = []; _marker = null; _floor = null; _el = {}; _badge = null; _plain = false; _frameReg = false; _stage = _THREE = _ctx = null; S.label = S.baseAcc = S.N = S.passAtN = S.passCurve = null; S.steps = S.revAcc = S.revCurve = S.scalingExp = S.effOom = null; S.state = "init"; } export default { id: ID, title: TITLE, endpoints: [EP], mount, unmount };