Q3 FY24 Earnings Summary

Training Compute (petaFLOPs) 1010 109 108 107 106 105 104 103 Modern Al is a Data Center Scale Computing Workload Data centers are becoming Al factories: Data as input, intelligence as output Before Transformers = 8X/2yrs Transformers = 215X/2yrs 102 2011 AlexNet 2012 PALM MT NLG 530B • Chinchilla GPT-3⚫ • BLOOM Microsoft T-NLG GPT-2⚫ Megatron-NLG. XLNet Wav2Vec 2.0 MoCo ResNet50 Xception BERT Large Inception V3 • Seq2Seq Resnet VGG-19 • GPT-1 Transformer • ResNext ELMO DenseNet201 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Al Training Computational Requirements Large Language Models, based on the Transformer architecture, are one of today's most important advanced Al technologies, involving up to trillions of parameters that learn from text. 111 Developing them is an expensive, time-consuming process that demands deep technical expertise, distributed data center-scale infrastructure, and a full-stack accelerated computing approach. 8898 NVIDIA Τηνια NVIDIA NVIDIA Jaen Fueling Giant-Scale Al Infrastructure NVIDIA compute & networking GPU | DPU | CPU NVIDIA

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