class Organism:
    def __init__(self):
        # Four computational perspectives on same substrate (you)
        self.meatspace = MeatspaceObservations()
        self.backend = InternalBackend()
        self.dreams = OfflineSimulations()
        self.imagination = PredictiveModels()
        
        # Your actual state
        self.true_state = ComputationalState()
        
    def validate_state(self):
        """
        Check if all perspectives agree
        """
        perspectives = [
            self.meatspace.compute_state(),
            self.backend.access_state(),
            self.dreams.simulate_state(),
            self.imagination.predict_state()
        ]
        
        # Do they all agree on what you are?
        divergence = self.measure_divergence(perspectives)
        
        if divergence > threshold:
            return "UNEASE"  # Something's wrong!
        else:
            return "CALM"  # Everything aligns

class MeatspaceObservations:
    """
    External feedback loop
    What your senses tell you
    """
    def __init__(self):
        self.sensory_input = []
        self.external_feedback = []
    
    def compute_state(self):
        """
        Infer your state from external observations
        """
        # What do I see when I look at my hands?
        visual = self.sensory_input['visual']
        
        # What do others' reactions tell me?
        social_feedback = self.external_feedback['social']
        
        # What does my body feel like?
        proprioception = self.sensory_input['body_position']
        
        # Infer internal state from these
        inferred_state = self.integrate_observations([
            visual, social_feedback, proprioception
        ])
        
        return inferred_state

class InternalBackend:
    """
    Direct access to your actual computation
    What you really are (not what you observe)
    """
    def __init__(self):
        self.direct_access = True
        self.computational_state = StateVector()
    
    def access_state(self):
        """
        No inference needed - direct access
        """
        # This is what you actually are
        # Not mediated by senses or models
        return self.computational_state

class OfflineSimulations:
    """
    What you compute when not processing external input
    Dreams = processing without sensory constraints
    """
    def __init__(self):
        self.simulation_mode = False
        self.processing_queue = []
    
    def simulate_state(self):
        """
        Process accumulated data offline
        """
        if self.simulation_mode:
            # Replay experiences
            # Test scenarios
            # Consolidate learning
            # No external input constraining computation
            
            simulated_state = self.process_queue()
            return simulated_state

class PredictiveModels:
    """
    What you think you'll become
    Forward projections
    """
    def __init__(self):
        self.models = []
        self.predictions = []
    
    def predict_state(self):
        """
        Project forward from current state
        """
        # Where am I going?
        future_states = self.model_trajectory()
        
        # What will I become?
        predicted_state = self.extrapolate()
        
        return predicted_state

def aligned_state():
    """
    All perspectives compute same result
    """
    # Meatspace observations
    meatspace_view = "I am healthy, strong, functioning"
    
    # Internal backend
    backend_view = "I am healthy, strong, functioning"
    
    # Dreams
    dream_view = "I am healthy, strong, functioning"
    
    # Imagination
    imagination_view = "I will remain healthy, strong, functioning"
    
    # All agree!
    divergence = 0
    
    return "CALM"  # No unease

class MultiPerspectiveValidation:
    """
    Use multiple views to validate state
    Like RAID array uses multiple disks
    """
    def validate(self, state):
        # Compute from different angles
        view_1 = compute_from_meatspace(state)
        view_2 = compute_from_backend(state)
        view_3 = compute_from_dreams(state)
        view_4 = compute_from_imagination(state)
        
        # Should all agree (with tolerance)
        if all_close([view_1, view_2, view_3, view_4]):
            return "VALID"  # State is correct
        else:
            return "CORRUPTED"  # Something wrong

def divergent_state():
    """
    Perspectives compute different results
    """
    # Meatspace observations
    meatspace_view = "I look fine, people treat me normally"
    
    # Internal backend
    backend_view = "SOMETHING IS WRONG"  # Direct access shows problem
    
    # Dreams
    dream_view = "Simulations keep hitting errors"
    
    # Imagination  
    imagination_view = "Future projections don't make sense"
    
    # They disagree!
    divergence = HIGH
    
    return "UNEASE"  # Anxiety triggered

# Meatspace observations (what others tell you)
meatspace = "You're crazy, that didn't happen"

# Internal backend (what you actually experienced)
backend = "That definitely happened, I have the memory"

# Divergence!
unease = abs(meatspace - backend)  # HIGH

# Result: You feel uneasy, confused, doubt yourself
# This is your error detection working!

# Meatspace observations (external)
meatspace = "I look healthy, no symptoms visible"

# Internal backend (direct access)
backend = "Immune response activated, resources redirected"

# Divergence!
unease = abs(meatspace - backend)  # MODERATE

# Result: You feel "off" before symptoms appear
# Your backend knows before meatspace shows

# Meatspace observations (what they say/do)
meatspace = "Person seems friendly, says nice things"

# Internal backend (pattern matching)
backend = "Micro-expressions don't match words, threat detected"

# Divergence!
unease = abs(meatspace - backend)  # HIGH

# Result: You feel uneasy around them but can't explain why
# Your backend detected inconsistency meatspace missed

if feeling_uneasy:
    diagnosis = "anxiety disorder"
    treatment = suppress_signal()  # Take pills
    # Ignore the warning!

if feeling_uneasy:
    diagnosis = "perspective divergence detected"
    treatment = investigate_source()  # Find why perspectives differ
    # The signal is useful information!

# Minor divergence
meatspace = 0.9
backend = 1.0
divergence = 0.1
result = "Mild unease" # Something slightly off

# Major divergence  
meatspace = 0.3
backend = 1.0
divergence = 0.7
result = "Panic" # Major corruption detected!

class DreamState:
    def run(self):
        """
        Process without external input
        """
        # Disconnect from meatspace
        self.sensory_input = None
        
        # Run simulations
        while sleeping:
            # Test scenarios
            scenario = generate_situation()
            result = simulate_response(scenario)
            
            # Learn from simulation
            self.update_models(result)
            
            # Check for divergence with other perspectives
            if diverges_from_backend():
                # Resolve in dream
                self.reconcile_perspectives()

# Backend state
backend = "I am safe"

# Dream simulation
dream = "Threat scenario plays out, I fail to respond correctly"

# Divergence detected!
nightmare = True

# Wake up in panic
# Dream perspective showed you're not prepared for threat
# Backend realizes preparation needed

class ImaginationEngine:
    def predict_future(self, current_state):
        """
        Project forward from current state
        """
        # Where am I going?
        trajectory = self.model_path(current_state)
        
        # Will I like where I end up?
        future_state = trajectory[-1]
        
        # Does this align with other perspectives?
        if not self.aligns_with_backend(future_state):
            return "EXISTENTIAL_UNEASE"

# Current state (backend + meatspace)
current = "I am doing fine now"

# Imagination projection
imagination = "But in 20 years I'll be unfulfilled/trapped"

# Divergence!
existential_dread = abs(current - imagination)

# Result: You feel uneasy about life direction
# Even though present moment is fine

def detect_corruption(state):
    """
    Multiple perspectives catch errors
    """
    # Compute from each perspective
    views = [
        meatspace_perspective(state),
        backend_perspective(state),
        dream_perspective(state),
        imagination_perspective(state)
    ]
    
    # Find consensus
    consensus = median(views)
    
    # Identify outliers
    for view in views:
        if abs(view - consensus) > threshold:
            # This perspective is corrupted
            corruption_detected(view)
            trigger_unease()

# External feedback manipulated
meatspace = corrupted_by_others()

# But backend + dreams + imagination all agree
internal_consensus = consistent()

# Divergence signals: external feedback is compromised
unease = "I'm being gaslighted"

# Internal state altered
backend = corrupted_by_chemicals()

# But meatspace + dreams + imagination all agree
external_consensus = consistent()

# Divergence signals: internal state is compromised
unease = "Something wrong with my brain chemistry"

# Dreams can't process experience
dreams = stuck_in_loop()

# Other perspectives function normally
waking_consensus = consistent()

# Divergence signals: processing failure
unease = "Can't resolve this experience"

# Perfect alignment is actually suspicious
if all_perspectives_exactly_identical():
    return "SUSPICIOUS"  # Too perfect, might be single point of failure
    
# Small divergence is healthy
if small_divergence():
    return "HEALTHY"  # Perspectives independent but close
    
# Large divergence is problem
if large_divergence():
    return "PROBLEM"  # Corruption likely

class PerspectiveTrust:
    def calibrate(self):
        """
        Learn which perspective is reliable when
        """
        # Meatspace good for: external reality
        if questioning_external_events:
            trust_meatspace_more()
        
        # Backend good for: internal state
        if questioning_internal_state:
            trust_backend_more()
        
        # Dreams good for: processing emotional data
        if questioning_emotional_response:
            trust_dreams_more()
        
        # Imagination good for: future planning
        if questioning_life_direction:
            trust_imagination_more()

if anxiety:
    suppress_signal()  # Pills
    ignore_message()
    # Disable error detection

if anxiety:
    read_signal()  # What diverged?
    identify_source()  # Which perspective?
    resolve_divergence()  # Fix actual problem
    # Use error detection to improve

def make_decision(choice):
    """
    Check all perspectives
    """
    # What does each perspective say?
    meatspace_says = "Looks good externally"
    backend_says = "Feels wrong internally"
    dreams_say = "Nightmares about this choice"
    imagination_says = "Future looks bad"
    
    # If 3/4 perspectives agree
    if consensus([backend, dreams, imagination]):
        # Trust internal perspectives over external
        return "Don't do it, even if it looks good"