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SpikingBrain 7B – More efficient than classic LLMs

12 somethingsome 5 9/14/2025, 5:49:42 AM github.com ↗

Comments (5)

cpldcpu · 56m ago

>The current implementation adopts pseudo-spiking, where activations are approximated as spike-like signals at the tensor level, rather than true asynchronous event-driven spiking on neuromorphic hardware.

Isn't that in essence very similar to Quantization Aware Training (QaT)?

spwa4 · 8m ago

Can you explain more? Why would that be the case? What is being passed from one layer to the next is not a linear value but the delay until the next spike, which is very different.

asdfasdf1 · 1h ago

SpikingBrain Technical Report: Spiking Brain-inspired Large Models https://arxiv.org/abs/2509.05276

bob1029 · 41m ago

https://news.ycombinator.com/item?id=45206420

cpldcpu · 22m ago

Well, it would still allow to deploy the trained model to SNN hardware, if it existed.