Traditional AI
Focus on models and prediction.
Camera
AI Model
Prediction
Five Infrastructure Layers for Physical AI
Five Infrastructure Layers Shape How Physical AI Systems Operate
Sensing, synchronization, communication, computing, and control determine how autonomous systems perceive, decide, and act.
Explore the Five Layers →5ACTION
4COMPUTE
3COMMUNICATION
2TIME
1PERCEPTION
Why Five Layers?
Five InfrastructureProblems EveryAutonomous SystemMust Solve
A model produces a prediction. The infrastructure determines how that prediction is synchronized, delivered, processed, and executed.
A prediction is only the beginning
The complete infrastructure
The Five Infrastructure Layers
Together they define overall system behavior.
From sensing to action, every layer contributes to system behavior.
Explore the Five Layers
Five Layers.
One Coordinated System.
Each layer introduces different engineering requirements, system constraints, and design priorities.
Layer 1
Perception
Capture the physical world accurately.
Multi-Sensor Data Capture
Collect information from cameras, LiDAR, IMUs, radar, and other sensors.
Calibration & Spatial Alignment
Ensure every sensor measures the same environment from the correct position and orientation.
Build Reliable Inputs
Reliable systems begin with consistent sensor data before any AI processing takes place.
Layer 2
Time
Align every device to a shared timeline.
One Common Time Reference
Synchronize cameras, LiDAR, IMUs, and controllers to the same clock.
Accurate Sensor Fusion
Precise timestamps ensure data from different sensors represents the same moment.
Easier Debugging & Analysis
A shared timeline makes replay, diagnostics, and root cause analysis far more reliable.
Layer 3
Communication
Deliver data predictably across the system.
Deterministic Networking
Deliver sensor and control data with predictable latency.
Low Latency, Low Jitter
Minimize timing variation that affects synchronization and control.
Reliable Data Delivery
Reduce packet loss and maintain stable communication between distributed devices.
Layer 4
Compute
Turn synchronized data into decisions.
AI Inference
Process sensor data using AI models and perception algorithms.
High-Performance Processing
Handle multiple sensor streams while maintaining consistent performance.
Real-Time Responsiveness
Generate decisions fast enough to support continuous autonomous operation.
Layer 5
Action
Translate decisions into physical actions.
Motion Execution
Convert AI decisions into precise physical movement.
Closed-Loop Control
Continuously adjust system behavior using real-time feedback.
Safe & Predictable Operation
Deliver repeatable motion under changing real-world conditions.
Our Platform
Infrastructure Across Every Layer
NeuronEDGE provides dedicated infrastructure across sensing, positioning, networking, AI computing, and system integration for autonomous systems.
View all productsPerception
TALO-B1000
Sensor Bridge
Aggregate and synchronize multi-sensor data to support accurate perception and sensor fusion.
Learn moreTime
TALO-F1200GU
Inertial Navigation System
Maintain continuous positioning by combining IMU, GNSS, and motion data into a unified navigation solution.
Learn moreCommunication
TALO-N1000
Time Networking Platform
Provide deterministic networking and precise time distribution across distributed autonomous systems.
Learn moreCompute
TALO-A1000
AI Controller
Process synchronized sensor data for AI inference, perception, planning, and decision making.
Learn moreAction
Motion Control Integration
Controller & Actuator Ecosystem
System Integration
Connect AI decisions with coordinated machine motion through industrial control infrastructure.
Integration ready