Strengthen high-quality data supply capabilities and promote innovation in the field of general artificial intelligence large models

In recent years, large-scale pre-training models have been one of the important driving forces for breakthroughs in artificial intelligence, accelerating the development process of artificial intelligence engineering and popularization, and are expected to become the cornerstone of a new generation of intelligent technology. Breakthroughs in large artificial intelligence models stem from the continuous development of high-quality data. Improving the ability to supply high-quality data is the key to promoting innovation in the field of general artificial intelligence large models

In an important study in 2020, it was found that there is a power law development law between the effect of the model and its parameters, data and calculation amount, namely "Scaling Laws". The parameters, data and calculation amount of the model increase exponentially, while the loss of the model on the test set decreases exponentially, indicating that the performance of the model is better

In other words, when the amount of calculation is fixed and the parameter scale is small, the impact of increasing the number of model parameters on model performance far exceeds the contribution of the amount of data and number of training times

Therefore, the industry generally recognizes that the performance of a model is directly proportional to its parameters and capacity, that is, the more parameters and capacity of the model, the better the performance

According to the development and future trends of the AI ​​industry chain, the market size of China's AI data service industry is gradually increasing. As the demand for training data increases and the requirements for service standards increase, the professional division of labor in the industry chain becomes more clear

Jia Yuhang emphasized at the Youth Pioneer Forum event that the quality of AI data is a key factor in artificial intelligence, which directly affects the final results of large models. The higher the quantity and quality of data, the more fully the model can be trained and performance optimized, and the better the performance will be. Therefore, high-quality AI data will provide more powerful service capabilities for artificial intelligence applications

Jia Yuhang said that cloud measurement data has many advantages in meeting the demand for high-quality data for large models. They regard data quality as the core of AI data services. They not only focus on technology research and development optimization, but also extend to talent training and product services, providing enterprises with high-quality scenario-based AI data services. At the business level, they introduce AI data processing to enterprises through data collection, data cleaning, and data annotation, and provide standard API interfaces to support data import and export, as well as pre-annotation functions for existing algorithms. They can provide multiple AI data product applications and AI data services, and connect with any enterprise's database, quickly accumulate the process from raw data to annotated data, and accelerate the development process of AI models

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