Discover and read the best of Twitter Threads about #dnn

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Thank you to @BloorStreetCap for yesterday's insightful #uranium discussion with some of the pioneers of the industry. A fantastic line up with in depth insight into all aspects of the #uranium sector.

Some of our highlights can be found the the thread below:
1/ “The world is recognising the science of nuclear power, not the false ideology.” – #NexGen CEO

“Price of #equities is screaming buy relative to the #spot price” – @uraniuminsider

“We’re on the cusp of a really really big move here [spot price]” – @UraniumEnergy
2/ #Sprott are seeing growing #institutional and #FO interest in the #uranium space. Very early stages of broad adoption by generalist #investors. Ciampaglia believes we are ‘just starting the second inning of this uranium cycle’.
Read 12 tweets
#Highlights2021 for me: our #survey on efficient processing of #sparse and compressed tensors of #ML/#DNN models on #hardware accelerators published in @ProceedingsIEEE.
Paper: dx.doi.org/10.1109/JPROC.…
arXiv: arxiv.org/abs/2007.00864
RT/sharing appreciated. 🧵
Context: Tensors of ML/DNN are compressed by leveraging #sparsity, #quantization, shape reduction. We summarize several such sources of sparsity & compression (§3). Sparsity is induced in structure while pruning & it is unstructured inherently for various applications or sources. Various sources induce stru...Common structures of sparsi...
Likewise, leveraging value similarity or approximate operations could yield irregularity in processing. Also, techniques for size-reduction make tensors asymmetric-shaped. Hence, special mechanisms can be required for efficient processing of sparse and irregular computations.
Read 12 tweets

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