The training process is done using the parallel computing technique. This made it possible to complete the training process much faster than if it was done on a single GPU or processor. Before training the system, the data was processed in such a way that personal identifying data was removed from it
Nvidia partnered with OpenAI to train a 6 billion parameter version of ChatGPT using 30,000 Nvidia GPUs. According to reports, the training process took several months and consumed a significant amount of energy
The training process is done using the parallel computing technique, which includes breaking down the large-scale training task into smaller sub-tasks that can be performed simultaneously across several graphics processors. This allowed the training process to be completed much faster than if it was done on a single GPU or processor.
The goal of training such large linguistic models is to improve their ability to generate human-like responses that are indistinguishable from those of a human. This technology has many potential applications, including in chatbots, virtual assistants and automated customer service systems.
OpenAI addressed the ethical concerns surrounding the development and deployment of large language models, including the potential for these models to perpetuate biases and misinformation. OpenAI and other organizations are working to address these issues by implementing safeguards and transparency in the development and deployment of these models.
The model's training data was preprocessed to remove any personally identifiable information or sensitive data that could be used to identify individuals or groups. In addition, OpenAI and Nvidia have implemented various safeguards to ensure that the model is not biased or elicits inappropriate responses.
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