Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment

Xavier Callens

doi:10.5281/zenodo.20392603

May 26, 2026Open Access

Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment

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Key Points

The aim is to develop a high-performance learning loop that bypasses traditional backpropagation to enhance efficiency.
Implemented WARS-CI-DFA on GCP Cloud TPU v5e.
Achieved energy efficiency with a 40% reduction in board power.
Formally verified the approach using Lean 4.
Demonstrated a significant reduction in power usage by 40%.
Achieved high performance in biomimetic learning tasks.
Verified the formal correctness of the learning loop.

Implication

Investigates learning efficiency via telemetry-guided feedback in machine learning, suggesting power savings.

Abstract

WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.

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Cite This Study

Xavier Callens (2026) studied this question.

synapsesocial.com/papers/6a17ddab3fad632b0f9da76d https://doi.org/10.5281/zenodo.20392603

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Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment

Key Points

Implication

Abstract

Discussion

Cite This Study

Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment

Key Points

Implication

Abstract

Discussion

Cite This Study

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