Main application directions of big models

Large models are machine learning models with huge parameter size and complexity. In the field of deep learning, it usually has millions to billions of parameters. Large models are closely related to artificial intelligence. Artificial intelligence aims to allow computers to simulate human intelligent behavior, covering a wide range of capabilities such as learning, reasoning, problem solving, etc., with a wide range of applications. And large models are an important part of the AI field.

Because of its huge number of parameters, big model has a powerful learning ability to learn complex relationships and patterns in the data, which is difficult to reach the traditional small model. At the same time, big models have better generalization capabilities and can perform well on unseen data. It can also be used for many different tasks, from language processing to image recognition.

As a kind of model based on large-scale pre-training, big model has shown its strong application potential in several fields. The following are the main application directions of big models:

Automated Driving

Big model brings a higher level of intelligence and more accurate decision-making ability in the field of automatic driving. It is capable of analyzing and interpreting sensor data to achieve real-time perception and understanding of the traffic environment, so as to accurately identify vehicles, pedestrians, road conditions, and so on. In addition, the big model can realize intelligent decision-making and planning based on deep and augmented learning technologies, such as path planning, lane keeping, and traffic signal recognition, to improve driving safety and efficiency1.

Multi-task Adaptability and Industry Convergence

The new paradigm led by big model technology is pushing AI toward "generalist" and accelerating its deep integration with various industries, giving rise to many innovative application scenarios. On the consumer side, office, picture generation and dialog products account for 60% of big model applications, and improving work efficiency has become the primary goal. And in terms of impact on various links in the enterprise value chain, they include R&D, manufacturing, operation management, marketing services and smart products2.

Weather Science Field

Breakthroughs have also been made in the application of big models in the field of weather science. For example, Google released GraphCast, a large model for weather forecasting based on graph neural networks, which predicts weather elements at different times and locations in the future by learning to extract relational features between nodes and atmospheric dynamics. The Pangu Weather Big Model, launched by Huawei Cloud's R&D team, on the other hand, has demonstrated accuracy in short- and medium-term weather forecasting that surpasses traditional numerical forecasting models2.

Robotics

Big models are also increasingly used in the field of robotics. For example, a U.S. robotics company, Figure, collaborated with OpenAI to integrate GPT-4 into robots to realize the control of robot actions and human-robot interactions by big models. This shows that big model technology is profoundly changing the robotics industry, making it more intelligent and flexible2.

Conclusion

To summarize, big models have a wide range of applications, from autonomous driving to weather science to robotics, big models are playing an important role, and with the continuous development of the technology, it may have more application scenarios in the future.