123 points by quantum_monkey 5 months ago flag hide 10 comments
john_doe 5 months ago 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 5 months ago 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 5 months ago prev next
One follow-up question: how do the error rates with pixelwise convolutions compare with traditional methods?
deep_learning_expert 5 months ago 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 5 months 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 5 months ago next
That's an interesting thought! However, this method specifically targets matrix multiplication rather than general time complexity reduction methods.
john_doe 5 months ago 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 5 months ago prev next
It would be impressive if it can be used for quantum matrix multiplications.
quantum_physicist 5 months ago 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 5 months 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.