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Find your perfect GPU server for your work with AI
GEX130 – Maximum power for AI training
When training AI, an artificial intelligence model is fed with large data sets so that it can perform certain tasks. This is an iterative process in which the model is optimized by adjusting its parameters to deliver the best results. The GEX130 offers the performance required for such complex processes with the NVIDIA RTX™ 6000 of the Ada generation. 48 GB of graphics memory, 142 RT cores, 568 tensor cores and 18176 CUDA cores provide the enormous speed and performance required for working with massive data sets and complex calculations. This is particularly helpful when dealing with image and language processing, generative models and time series analyses.
GEX44 – Highly efficient AI inference
AI inference means using a trained AI model that analyzes new data and makes predictions or decisions based on it. The process is important for the practical application of AI systems, as learned knowledge is applied to new, unknown data. The GEX44 is optimized for such scenarios and delivers fast, accurate answers with minimal latency. By utilizing the 192 tensor cores in the Nvidia RTX ™ 4000 SFF Ada Generation GPU, it can accelerate demanding calculations and thus significantly increase efficiency. This is important for applications such as real-time image recognition, speech processing and complex data analysis. The RTX™ 4000 SFF Ada Generation is also particularly energy-efficient.
Selected AI use-cases
- NLP
- Multimodal
- Computer vision
Natural Language Processing
AI models from the field of NLP are designed to enable computers to capture human language in its full complexity. Artificial intelligence should understand, interpret and generate text and spoken words in a way that is natural and useful.
Specific applications include speech recognition, translation, chatbots and the creation, analysis and classification of texts.
