Using a Signature-Based Approach,
Autobrains Brings Full Autonomy Closer

Autobrains’ revolutionary self-learning AI
mirrors how humans learn.

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  Signatures

  Simulate the human brain, by shifting from traditional AI labels to generic representations. Information is indexed and compressed into neural responses, with efficient data processing.

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  Self-learning

  The neural network algorithms are self-learned in a dynamic environment, independent from manually labelled data and immune against data biases.

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  Adaptive architecture

  Brain-like, scenario-focused contextual adaptivity. A sparse set of resources are applied during processing, translating into superior performance and higher efficiency.

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  Perception fields

  Extending perception to forces, capturing real-world interactions and dynamics. Closing the gap between perception and action, the input immediately propels the vehicle's behavior.

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  EON AI – Ensemble of Narrow AI Agents

  Routing sensor input to a handful of specialized narrow AI agents, by context.