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GPU Cloud
AI Training
AI training is the process of optimizing model parameters using labeled data and compute resources.
Definition
AI training is the computationally intensive process of optimizing neural network parameters using large datasets. Training large language models (LLMs) like GPT-4 or LLaMA requires thousands of GPU-hours and can cost millions of dollars. The training process involves forward propagation, loss calculation, backpropagation, and weight updates — repeated millions of times. Harch Corp provides GPU cloud infrastructure optimized for distributed training, with high-speed interconnects (InfiniBand 400G), NVLink, and proven configurations for Megatron-LM, DeepSpeed, and FSDP.
Related Keywords
ai trainingmodel trainingllm trainingdistributed traininggpu training
Related Terms
GPU Cloud
GPU cloud is a cloud computing service that provides access to graphics processing units (GPUs) on-demand for AI, ML, and HPC workloads.
AI Inference
AI inference is the process of using a trained model to make predictions on new data.
Distributed Training
Distributed training splits AI model training across multiple GPUs or nodes for faster convergence.