The article discusses the rise of advanced language models like ChatGPT and DeepSeek, which are nearing the limits of available data needed for training. A study from the Epoch research group warns that by 2028, AI development could stagnate due to a lack of new training data. To maintain progress towards Artificial General Intelligence, researchers advocate for the use of synthetic data, which can successfully replicate existing data types, protect sensitive attributes, and enhance model training without the need for extensive real-world inputs.
As language models like ChatGPT and Llama gain popularity, researchers caution that data scarcity may hinder their improvement, emphasizing the need for synthetic data innovation.
The Epoch research group highlights a looming data limitation for AI training by 2028, urging the exploration of synthetic data as a solution to enhance model capability.
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