Sparsity in Neural Networks
Tim and Vitaliy discuss the challenges of achieving sparsity in both activations and weights simultaneously in neural networks, highlighting the impact on memory complexity and the trade-offs involved in dataflow architecture.In this clip
From this podcast
Machine Learning Street Talk (MLST)
#77 - Vitaliy Chiley (Cerebras)
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