Training a large language model like GPT-3 requires a significant amount of computational resources, which can be very expensive. OpenAI, the organization that developed GPT-3, has not disclosed the exact cost of training the model, but estimates range from several million to tens of millions of dollars.

The cost of training a language model depends on various factors such as the size of the model, the amount of data used to train it, and the computing resources used. For example, GPT-3 is one of the largest language models to date, with 175 billion parameters and was trained on a vast dataset of text from the internet, books, and other sources.

Moreover, training a model of that scale requires a large amount of computing resources, such as graphics processing units (GPUs) and tensor processing units (TPUs). The cost of renting these resources can quickly add up, and it can take several weeks or even months to train a model like GPT-3.

Therefore, training a large language model like GPT-3 can be a significant investment, requiring a considerable amount of money, specialized expertise, and access to high-end computing resources.
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