Cluster-level AI computing server
Category:
This product is a computing unit specifically designed to meet the challenges of training artificial intelligence models with trillions of parameters. During the pre-training and fine-tuning of large language models and multimodal large models, this module can effectively support large-scale distributed training tasks lasting several months, ensuring the stability and efficiency of the computation process and significantly shortening the model iteration cycle. It is particularly well-suited for building ultra-large-scale computing clusters, providing core computational power support for national-level AI infrastructure development and cutting-edge scientific and technological exploration.
Core application scenarios:
1. Cutting-edge large model R&D: Supporting the training from scratch of next-generation foundational models with trillions of parameters, meeting the demand for extreme computing power from top-tier AI labs and research institutions.
2. AI for Science: Accelerate the scientific discovery process in fields such as protein structure prediction, new materials design, climate change modeling, and astrophysical research by leveraging AI capabilities to tackle complex scientific challenges.
3. Ultra-large-scale synthetic data generation: To train more powerful AI models, efficiently generate massive volumes of high-quality synthetic data and build the digital content required for virtual worlds.
Cluster-level AI computing server
Category:
- Description
-
This product is a computing unit specifically designed to meet the challenges of training artificial intelligence models with trillions of parameters. During the pre-training and fine-tuning of large language models and multimodal large models, this module can effectively support large-scale distributed training tasks lasting several months, ensuring the stability and efficiency of the computation process and significantly shortening the model iteration cycle. It is particularly well-suited for building ultra-large-scale computing clusters, providing core computational power support for national-level AI infrastructure development and cutting-edge scientific and technological exploration.
Core application scenarios:
1. Cutting-edge large model R&D: Supporting the training from scratch of next-generation foundational models with trillions of parameters, meeting the demand for extreme computing power from top-tier AI labs and research institutions.
2. AI for Science: Accelerate the scientific discovery process in fields such as protein structure prediction, new materials design, climate change modeling, and astrophysical research by leveraging AI capabilities to tackle complex scientific challenges.
3. Ultra-large-scale synthetic data generation: To train more powerful AI models, efficiently generate massive volumes of high-quality synthetic data and build the digital content required for virtual worlds.
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