Yes, as strange as it may seem at first glance, since the chat It’s not a video game, its operation depends in part on graphics cards and in fact… a lot of them!
In detail, recent years in IT have seen GPUs being used to speed up more and more processes, as they can perform very well in applications that can be parallelized, such as workloads. artificial intelligence. Somehow, h nvidia It is expected to benefit greatly from the trend, as Trendforce points out.
Specifically, the research firm did the calculations and estimated that the latest version of ChatGPT was needed At least 20,000 graphics cards And of course not simple models for the general consumer, but GPUs of 5 petaflops performance. In fact, there are many opportunities to dramatically increase this number of cards in the future, as OpenAI becomes more popular, exceeds 30,000.
More specifically, the trendforce pointing to:
In the case of the Generative Pre-Training Adapter (GPT) that forms the basis of ChatGPT, the number of training parameters used to develop this model has increased from about 120 million in 2018 to nearly 180 billion in 2020. According to an estimate by TrendForce, the number of GPUs that The GPT model needs to process training data in 2020 about 20,000. From now on, the number of GPUs needed to commercialize the GPT (or ChatGPT) model is expected to exceed 30,000.
Note that these estimates use NVIDIA’s A100 as the basis for the calculations. Therefore, with generative AI becoming a trend, the demand for GPUs is expected to increase exponentially and thus benefit the relevant supply chain participants. NVIDIA, for example, is likely to benefit the most from developing generative AI. DGX A100, a global platform for AI workloads, provides 5 petaflops, and has become almost the best choice for big data analysis and AI acceleration.
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