Sees Co., Ltd.

Autonomous Decentralized AI Cell & Hashchain Are the Core Technology of the Physical AI Era.
Sees Co., Ltd.

Sees Autonomous Decentralized AI Cell

AI CELL

Pioneering Our Proprietary Technology "Autonomous Distributed AI" Ahead of the Physical AI Era

In fields like smart mobility and humanoids, the era of "Physical AI"—systems that act and make decisions autonomously based on sensor data—has begun.
Anticipating the peak of the Physical AI era, we have developed "Autonomous Distributed AI Cells" ahead of the competition.

Realizing the "Child AI" Concept and On-Chip Integration

The "Autonomous Distributed AI Cell" logicizes the very learning process of a newborn child through senses like vision and touch. We have successfully brought this "Child AI" concept to life and integrated it onto a silicon chip.

Achieving "Ultimate Physical AI" Through Collective Education

The "Autonomous Distributed AI Cell" features automatic integration of learnings from other cells, self-correction based on missing or conflicting information, and re-education capabilities for collective learning across multiple cells.
Here lies the Ultimate Physical AI: multiple "Autonomous Distributed AI Cells" learning independently, fostering mutual growth, and autonomously executing coordinated group behaviors.

Module

Autonomous Distributed AI Cell

Evaluation Version of the Autonomous Decentralized AI Cell

  • Evaluation Version

  • Size: 85mm x 85mm
  • Wired LAN / Wireless LAN Supported
  • Power and sensor input signals accepted via pins

USE CASE

Autonomous Decentralized AI Cell
Use case

The "Autonomous Distributed AI Cell" is a world-first technology enabling fully unmanned factory operations and automated facility monitoring/management.
Requiring no individual pre-configuration for sensors or environments upon factory shipment, this composite chip behaves like an artificial neural cell—autonomously sensing its surroundings the moment it is installed and continuously learning various operational elements through active deployment.
Blockchain acts as the synaptic pathways of a neural network, guaranteeing data transmission integrity and enabling distributed processing.
In addition to artificial neural cell capabilities, it is built on highly distinctive, advanced logic that incorporates autonomous audiovisual sensory cells and autonomous nervous system functions akin to the cerebellum.

Use Case 1
Application in Factory Control

Equipment installed in a factory autonomously learns local operating conditions and behaviors through visual, tactile, and other sensory inputs, establishing its own "individual identity."
Even among identical machines, slight variations occur—such as subtle discrepancies in motor RPM—so each unit collects operational data to optimize itself for its specific site.
An edge server compares and analyzes data collected from individual units to execute "identity calibration," automatically adjusting voltage and other parameters so all machines deliver uniform output.
By sharing and adjusting (re-educating) the individual variations and experiences of each machine across the entire system, this approach prevents quality inconsistencies and builds a next-generation industrial infrastructure that continues to operate with high precision.

Application in Factory Control
Application in Factory Control

Use Case 2
Application in Autonomous Drone Control

Based on collective action instructions from a master drone (Autonomous Distributed AI Cell [Master]), multiple slave drones (Autonomous Distributed AI Cell [Slave]) execute autonomously controlled flights while coordinating with one another.
Information such as obstacle avoidance and optimal routing learned by a single drone is shared across the entire fleet (collective education) via an edge server.
As the number of operating units increases, it unleashes a powerful collective network effect where the entire drone fleet automatically becomes smarter, enabling multiple AIs to drive mutual growth while executing autonomous group actions.

Application in Autonomous Drone Control
Application in Autonomous Drone Control

Use Case 3
Application in Predictive Maintenance

"Autonomous Distributed AI Cells" can be integrated into predictive maintenance systems for individual production lines or entire factories.
For example, anomaly detection models can be individually optimized based on the unique operational variations of each robotic arm, enabling significantly more accurate failure predictions.

Application in Predictive Maintenance
Application in Predictive Maintenance

LOGIC

Autonomous Decentralized AI Cell
Special Logic

Autonomous Distributed AI Cell incorporates special logic to make it autonomous.

Individual Establishment Logic
For example, some motors vibrate at 1000 rpm (revolutions per minute) and overheat abnormally, while others rotate normally even at 2000 rpm. The "Autonomous distributed AI cell" installed in each motor learns the individual characteristics of the motor it manages and sets a limiter to determine what is the normal line.
Comparative learning logic for others
"Autonomous distributed AI cell" share data with other "Autonomous distributed AI cell" to understand how the devices they manage are unique compared to other devices.
Verbal Consciousness and Intention Logic
"Autonomous Distributed AI Cell" simultaneously outputs human verbal information such as consciousness and intention, in addition to the usual sensor output digital data. For example, "It is a little hot" or "I feel a lot of vibration." This linguistic information can be directly connected to the existing linguistic input type AI to convey intentions and ask it to think and decide.
Self-correcting logic
Unlike ordinary monitoring systems, the "Autonomous Decentralized AI Cell" does not need to seek the judgment of the central monitoring system, but rather uses its own judgment to take action to output an alarm or extinguish a fire using localized sprinklers, etc., if the situation is dangerous enough to warrant urgent action.
Ethical logic
The off-premises higher-level servers and edge servers educate each "autonomous distributed AI cell" while making total predictions and judgments. (e.g., correction of output language information)
Self-positioning logic
By attaching GPS and altitude sensors to each "autonomous distributed AI cell," it is possible not only to notify the host server of the location where it is installed and the location/device where an abnormality is detected on a 3D map, but also to identify and grasp the location by itself.
Re-education Logic
Periodically poll the "Autonomous Distributed AI Cell" to create a 3D map based on normal operation availability, location movement, status, etc., and constantly update the version. This allows the system to autonomously update its latest position and role without the need for human configuration.
Special Logic Diagram
Special Logic Diagram of Autonomous Distributed AI Cell

While AI for manufacturing equipment requires identical movements and precision, autonomous humanoids such as collaborative robots demand a wide variety of motions.
It is ideal for integrated control and maintenance that understands the unique characteristics of each unit.

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