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Intel Loihi: programmable event-driven spiking compute and learning

Contribution grade

Programmable AI accelerators · Human-designed research method or resource

Reference score150,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Combined asynchronous spike routing, local synaptic state and programmable learning engines; the Loihi2 extension added microcoded state dynamics, graded spikes and richer connectivity for streaming computation.

Scientific scope

Combined asynchronous spike routing, local synaptic state and programmable learning engines; the Loihi2 extension added microcoded state dynamics, graded spikes and richer connectivity for streaming computation. One architecture family with separate2018/2021 bylines. Core memory, fan-in/fan-out and mapping limits apply; deadlock-freedom requires management activity restricted to the specified synchronization phase. Loihi2 examples in the2021 paper are hardware-constrained simulations, not measured silicon speed/energy. No biological modelling or medical outcome is catalogued; approximate sparse-coding gains do not imply superiority at arbitrary numerical tolerance.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. One architecture family with separate2018/2021 bylines. Core memory, fan-in/fan-out and mapping limits apply; deadlock-freedom requires management activity restricted to the specified synchronization phase. Loihi2 examples in the2021 paper are hardware-constrained simulations, not measured silicon speed/energy. No biological modelling or medical outcome is catalogued; approximate sparse-coding gains do not imply superiority at arbitrary numerical tolerance.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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