数据是人工智能发展的核心要素，特别是进入2023年大模型时代后，高质量数据集的重要性日益凸显，成为大模型产品研发的瓶颈和焦点。各类大模型的性能不仅取决于数据的数量，也依赖于数据的质量。国内在数据集的数量、质量，以及围绕数据集的生态上与国外存在差距，这限制了我国的人工智能产业的发展。合成数据技术有望解决未来各类大模型发展中的数据缺口问题，特别是在金融、医疗和自动驾驶等领域具有巨大潜力。
Data is a core element in the development of artificial intelligence，especially as we enter the era of large models in 2023，the importance of high-quality datasets is becoming increasingly prominent，becoming a bottleneck and focal point in AI product development. The performance of various large models depends not only on the quantity of data but also on the quality of data. There is a gap between domestic and international datasets in terms of quantity，quality，and the ecosystem surrounding the datasets，which limits the development of China’s artificial intelligence industry. Synthetic data technology is expected to address the data gap in the development of various large models in the future，especially in fields such as finance，healthcare，and autonomous driving，where it holds tremendous potential.
