GrAI Matter Labs
Overview
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HQ Location
France
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Year Founded
2016
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Company Type
Private
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Revenue
< $10m
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Employees
11 - 50
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Website
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Company Description
LEVERAGE NEXT GENERATION NEUROMORPHIC COMPUTING AT THE EDGE
GrAI Matter Labs utilizes brain inspired neural network architecture to overcome the limitations of traditional Von Neumann machines and application processors.
Our unique implementation is the only system that can leverage sparsity from an end-to-end perspective, a fully programmable approach for ease of implementation and offers ultra-low latency while preserving low power levels not feasible before.
GrAI Matter Labs utilizes brain inspired neural network architecture to overcome the limitations of traditional Von Neumann machines and application processors.
Our unique implementation is the only system that can leverage sparsity from an end-to-end perspective, a fully programmable approach for ease of implementation and offers ultra-low latency while preserving low power levels not feasible before.
IoT Solutions
CREATE MAGIC ON THE EDGE WITH GRAI ONE
Ultra-low power, fully programmable neuromorphic computing for sensor analytics and machine learning – powered by brain-inspired technology.
Real-time response for autonomous action
Only architecture that can leverage sparsity at the edge for low power
Fully programmable with standard frameworks and languages
Ultra-low power, fully programmable neuromorphic computing for sensor analytics and machine learning – powered by brain-inspired technology.
Real-time response for autonomous action
Only architecture that can leverage sparsity at the edge for low power
Fully programmable with standard frameworks and languages
IoT Snapshot
GrAI Matter Labs is a provider of Industrial IoT analytics and modeling technologies.
Technology Stack
GrAI Matter Labs’s Technology Stack maps GrAI Matter Labs’s participation in the analytics and modeling IoT Technology stack.
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Devices Layer
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Edge Layer
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Cloud Layer
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Application Layer
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Supporting Technologies
Technological Capability:
None
Minor
Moderate
Strong
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