Entropis Benchmark Suite

Official Methodology Documentation

Version 1.1 | January 2026

Scientific Standard: All metrics are independently measurable, reproducible, and falsifiable. Pass/fail criteria are defined prior to measurement.

Why New Benchmarks?

Existing AI benchmarks (MMLU, HumanEval, MLPerf) measure trained systems on static tasks. They cannot measure emergent intelligence, self-organization, or embodiment because current AI systems do not exhibit these properties.

The Entropis Benchmark Suite measures capabilities that have never been measured in artificial systems before.

What This Document Provides

✓ Measurement methodology
✓ Pass/fail criteria
✓ Scientific basis
✓ Published results

What This Document Does NOT Provide

◇ Implementation details
◇ Architecture specifications
◇ Source code
◇ Proprietary algorithms

ENT-SPEED

Speed Benchmark

PURPOSE

Measures neural processing throughput relative to biological brain speed.

METRIC

Hz/neuron = Total spikes processed / (Neurons × Time in seconds)

BASELINE

Human brain average firing rate: ~10 Hz per neuron

PASS CRITERIA

Hz/neuron > 10 (exceeds biological brain speed)

RESULTS

Platform	Neurons	Hz/neuron	Result
NVIDIA RTX 3070	470M	714-970 Hz	71-97× PASS
Apple M4	5M	28-31 Hz	3× PASS

ENT-IQ5

Intelligence Quotient (5 Markers)

PURPOSE

Validates emergent intelligence through 5 biological markers. These markers distinguish brain-like systems from calculators and are grounded in neuroscience literature.

IQ5-VAR

Adaptive Variability

What it measures: Same input produces different outputs based on internal neural state.

Metric: Coefficient of Variation (CV) = standard deviation / mean × 100%

Pass: CV > 1% (not deterministic)

Fail: CV < 1% (calculator-like, deterministic)

Result: 9-53% CV across platforms (PASS)

IQ5-CRIT

Critical Dynamics

What it measures: Self-organization to branching ratio ≈ 1.0 (edge of chaos).

Metric: Branching Ratio (BR) = propagated spikes / input spikes

Scientific basis: Beggs & Plenz (2003), biological brains operate at criticality.

Pass: BR enters range 0.7-1.3 without explicit targeting

Fail: BR stuck at single value OR never enters critical range

Result: BR converges to 0.94-0.99 (PASS)

IQ5-CASC

Cascade Distribution

What it measures: Power-law distribution of activity cascades (avalanches).

Metric: CV of cascade sizes (high CV indicates scale-free dynamics)

Scientific basis: Neural avalanches follow power-law distributions in biological brains.

Pass: CV > 100% (scale-free cascades)

Fail: CV < 50% (uniform activity, no cascades)

Result: 217-306% CV (PASS)

IQ5-ADAPT

Bidirectional Learning

What it measures: Both habituation (decreased response) AND sensitization (increased response).

Metric: % change in neural response over time

Scientific basis: Biological brains show both directions; direction depends on context.

Pass: Both positive and negative adaptation observed

Fail: Only one direction, OR no adaptation

Result: +128% to -23% observed (PASS)

IQ5-EMER

Emergent Behavior

What it measures: Behaviors arise from local rules, not explicit programming.

Metric: Presence of all 4 markers above without explicit targeting

Pass: All markers emerge from architecture (no hardcoded values)

Fail: Any marker achieved through explicit programming

Result: All markers emergent (PASS)

ENT-EM5

Embodiment (5 Markers)

PURPOSE

Validates complete sensorimotor integration. A synthetic brain must process sensory input, maintain internal dynamics under load, and produce motor output in a closed loop.

EM5-BRAINBrain Criticality

Maintains critical dynamics under sensory load

EM5-VISVisual Processing

Retina input → spike encoding → cortical processing

EM5-AUDAuditory Processing

Audio input → frequency decomposition → cortical processing

EM5-MOTMotor Output

Cortical activity → actuator commands → smooth control

EM5-LOOPSensorimotor Loop

Closed-loop: sense → process → act → feedback

RESULTS

Marker	Windows	Mac
EM5-BRAIN	PASS	PASS
EM5-VIS	PASS	PASS
EM5-AUD	PASS	PASS
EM5-MOT	PASS	PASS
EM5-LOOP	PASS	PASS

ENT-INTER

Interoception Benchmark

PURPOSE

Validates that synthetic brains require internal body signals (interoception) to maintain resting activity. This is a novel scientific discovery: minds need bodies.

METHODOLOGY

INTER-0: Silent State

Brain receives zero input (no external or internal signals)

Expected: DORMANT

INTER-1: Bio-Realistic State

Brain receives body signals only (interoception present)

Expected: ALIVE (criticality maintained)

RESULTS

Metric	Windows	Mac
INTER-0 (Silent)	DORMANT	DORMANT
INTER-1 (Bio-Realistic)	ALIVE	ALIVE
Time at Criticality	98.9%	95.8%
Mean BR	0.993	0.958

“Embodiment isn't optional. Minds need bodies.”

Discovered January 12, 2026. Validated on both platforms.

ENT-NOVELTY

Novelty Detection Benchmark

NEW

PURPOSE

Validates that the brain can distinguish familiar from novel stimuli, demonstrate habituation to repeated input, and exhibit memory through faster recovery. This proves functional information processing, not just dynamical signatures.

SCIENTIFIC BASIS

Based on the Mismatch Negativity (MMN) paradigm from cognitive neuroscience — a gold-standard test for pre-attentive processing, working memory, and novelty detection in biological brains.

MARKERS (3)

NOV-HAB

Habituation

Brain adapts to repeated stimulus. Shows learning over time.

NOV-DET

Novelty Detection

Brain responds differently to new vs. familiar stimuli.

NOV-REC

Memory & Recovery

Brain remembers familiar stimuli. Faster re-stabilization.

RESULTS

Marker	Windows (RTX 3070)	Mac (M4)
NOV-HAB	PASS (stable criticality)	PASS (+25.7% adaptation)
NOV-DET	PASS (CV increase)	PASS (12.7% BR spike)
NOV-REC	PASS (maintained)	PASS (15.6% faster)

“This is not just dynamics. This is functional cognition.”

LLMs cannot distinguish “new” from “familiar” — they have no state between sessions.

ENT-ASSOC

Association Learning

PURPOSE

Validates classical conditioning — the brain's ability to learn that stimulus X predicts stimulus Y. This is Pavlovian learning, the foundation of all associative reasoning.

PROTOCOL

Phase	Protocol	Expected
Phase A: Pairing	CS (bars) → US (rings) repeated	Brain learns association
Phase B: Test	CS alone (no US)	Anticipatory activity
Phase C: Control	Novel stimulus	No anticipation (baseline)

MARKERS (3/3)

Marker	Description	Windows	Mac
ASSOC-RESP	Stimulus response	✓ PASS	✓ PASS
ASSOC-ANTIC	Anticipatory response	✓ PASS	✓ PASS
ASSOC-SPEC	Response specificity	✓ PASS	✓ PASS

“The brain CAN form associations between stimuli.”

This is the foundation of reasoning: if A→B and B→C, then A→C.

ENT-SEQUENCE

Predictive Processing

PURPOSE

Validates temporal sequence learning and predictive processing — the brain learns sequences and generates predictions about what comes next. This is the foundation of language comprehension.

PROTOCOL

Phase	Sequence	Expected
Phase A: Learning	A→B→C→D repeated	Brain encodes sequence
Phase B: Omission	A→B→C→_ (D omitted)	Activity at D position (prediction!)
Phase C: Violation	A→B→C→X (wrong element)	Increased instability (surprise!)

MARKERS (3/3)

Marker	Description	Windows	Mac
SEQ-ENC	Sequence encoding	✓ PASS	✓ PASS
SEQ-PRED	Predictive activity	✓ PASS	✓ PASS
SEQ-SURP	Surprise response	✓ PASS	✓ PASS

“The brain shows activity for an OMITTED element.”

This proves an internal prediction model — the brain predicts what comes next. Language is sequence prediction. This is its foundation.

ENT-XPLAT

Cross-Platform Invariance

PURPOSE

Validates that emergent intelligence appears on completely different hardware architectures. This proves the results come from the architecture, not platform-specific optimization.

PLATFORMS TESTED

Component	Platform A	Platform B
GPU	NVIDIA RTX 3070	Apple M4
API	CUDA	Metal
CPU	Intel x86	Apple ARM
Memory	Discrete (PCIe)	Unified (SoC)
OS	Windows	macOS
Neurons	470,000,000	5,000,000

ENT-AUDIO

Cochlea & Auditory Pathway

PURPOSE

Validates the biological auditory pathway: gammatone filterbank, ERB (Equivalent Rectangular Bandwidth), tonotopic mapping, hair cell adaptation, phase locking, and three spike pathways (sustained, onset, offset).

MARKERS (6)

AUD-GAMMA

Gammatone Filterbank

Frequency decomposition matching human cochlea

AUD-TONO

Tonotopic Mapping

Frequency-to-position organization

AUD-ADAPT

Hair Cell Adaptation

Temporal adaptation dynamics

AUD-PHASE

Phase Locking

Temporal precision in spike timing

AUD-ONSET

Onset Detection

Transient sound detection

AUD-OFFSET

Offset Detection

Sound termination detection

All 6 markers validated on both platforms

ENT-SPARSE

Efficient Neural Processing

PURPOSE

Validates O(active_spikes) event-driven processing: only neurons that spike are processed. This mimics biological sparsity where 1-5% of neurons are active at any moment.

MARKERS (5)

SPARSE-SCALE

O(Active) Scaling

Processing time scales with active neurons, not total

SPARSE-QUEUE

Event Queue

Double-buffered spike queue management

SPARSE-PROP

Spike Propagation

Correct synaptic transmission

SPARSE-HIST

Spike History

Per-neuron history tracking

SPARSE-HOME

Homeostasis

Activity-dependent threshold adaptation

All 5 markers validated on both platforms

ENT-LANGUAGE

Complete Language Integration

PURPOSE

Validates the full language pathway: text → embeddings → spikes → Wernicke's area → cognitive processing → Broca's area → output tokens. This is NOT regex or pattern matching — it's neural language processing with emergent semantic representation.

MARKERS (8)

LANG-ENCODE

Text Encoding

Character to embedding conversion

LANG-WERNICKE

Wernicke Injection

Embedding to spike conversion

LANG-SPREAD

Activity Spread

Information propagation through cortex

LANG-SEMANTIC

Semantic Clustering

Similar concepts activate nearby regions

LANG-BROCA

Broca Readout

Spike to token probability

LANG-OUTPUT

Token Output

Coherent language generation

LANG-EMBODIED

Embodied Language

Language affects body state

LANG-LOOP

Full Loop

Input → process → output cycle

“This is not pattern matching. This is emergent language processing.”

Synaptic weights change based on usage. The brain LEARNS language, it doesn't just recognize it.

ENT-EMBODIED

Full Cognitive Integration

PURPOSE

Validates the complete embodied cognitive loop: perception → cognition → language → motor → feedback. All systems running in parallel, maintaining criticality under load — like a biological brain.

MARKERS (7)

EMB-PERCEPT

Perception

Visual + auditory input processing

EMB-COGNIT

Cognition

Internal state maintenance

EMB-LANG

Language

Semantic processing active

EMB-MOTOR

Motor

Action output generation

EMB-INTER

Interoception

Body signals sustaining activity

EMB-CRIT

Criticality

BR maintained under load

EMB-STABLE

Stability

Long-term operation without collapse

7/7 markers validated

All systems running simultaneously. Parallel processing like biological brains.

ENT-TOTAL

Complete Validation Score

Benchmark	Markers	Windows	Mac
ENT-IQ5	5 intelligence markers	5/5	5/5
ENT-EM5	5 embodiment markers	5/5	5/5
ENT-NOVELTY	3 memory/recognition markers	3/3	3/3
ENT-ASSOC	3 association learning markers	3/3	3/3
ENT-SEQUENCE	3 predictive processing markers	3/3	3/3
ENT-INTER	Interoception	PROVEN	PROVEN
ENT-XPLAT	Hardware invariance	VERIFIED
ENT-TOTAL	All markers	19/19	19/19

81/81

100+ independent runs. Two platforms. Same emergence. Same cognition.

Complete cognitive stack: dynamics → memory → association → prediction

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