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Your location: Home > Related Articles > Artificial intelligence promotes business model innovation, and predicting behavioral changes is more sought after

Artificial intelligence promotes business model innovation, and predicting behavioral changes is more sought after

Author:QINSUN Released in:2024-03 Click:31

Currently, major countries around the world attach great importance to the development of the artificial intelligence industry. China has regarded the new generation of artificial intelligence as a driving force for promoting technological leaps, industrial optimization and upgrading, and overall productivity growth. Under the joint efforts of the government, research institutions, enterprises, and other parties, the domestic artificial intelligence industry has developed rapidly, demonstrating a thriving development trend.

Recently, relevant leaders of the Ministry of Industry and Information Technology attended the World Internet Conference ▪ The Internet Development Forum said that China's artificial intelligence industry has made positive progress, with technology products such as special-purpose chips, application algorithms and open platforms continuously optimized, and the application level of computer vision, natural language understanding and other technologies has reached an advanced level. In the first half of this year, the scale of China's core artificial intelligence industry reached 77 billion yuan, with over 260 artificial intelligence enterprises, making it one of the main concentration areas for unicorn enterprises.

With artificial intelligence, businesses can shift towards data-based models and simulations. The updated artificial intelligence system starts from scratch and feeds itself with a conventional diet of big data. This is wisdom in action, ultimately providing complex data models that can be used for precise decision-making.

Artificial intelligence tools and platforms are in place to help businesses understand how customers adapt to new realities. In recent years, institutions that have lagged behind in the adoption of digital channels in business and relationship development have gradually realized the urgency of this situation and are quickly mastering concepts such as behavior analysis and personalization.

In practical applications, combining machine learning prediction models can predict sales, and intelligent devices can also understand production data. Real time optimal production plans and rhythms can be obtained through cloud computing. The collected production data includes timely feedback from intelligent machines on production and idle conditions, real-time monitoring of inventory in intelligent warehouses, and dynamic prediction of vehicle and component demand by intelligent research systems.

With the efforts of multiple parties, modern AI models have made great strides in development through algorithmic trading. The difference between these models is that they not only analyze massive amounts of data, but also fully automate the analysis process. The entire model continuously learns and improves, which can overcome the difficulties that arise solely from relying on human resources. This "intelligence" originates from complex machine learning techniques, such as genetic search algorithms and Bayesian networks.

Some analysts believe that AI tools extract massive amounts of data from global resources, learn from it, and make corresponding predictions. The data collection is very thorough: it extracts information from books, financial exchanges, news reports, social media platforms, and even television programs, and then extracts, analyzes, and integrates this information. It is then used for business behavior model prediction in industries such as automobiles, transportation, construction, and energy, thereby opening up more space for enterprises to optimize their service systems.

Taking the automobile manufacturing industry as an example, there are certain differences in the welding method during the welding process of the automobile body due to the different materials at different positions of the body. Therefore, researchers use big data technology to input welding methods corresponding to different materials into computers.

The automatic welding center can clarify the actual situation of the vehicle body structure through all-round scanning, confirm the material properties of each welding point, use big data technology to draw the vehicle body structure model in the computer, and then calculate the optimal welding path and welding method. This method is very suitable for some non mass production vehicle manufacturing processes.

In summary, artificial intelligence has the ability to collect data, analyze data, and apply data at the right time. This potential also has high value in the field of digital marketing. Therefore, in order to make data-driven decisions, more and more marketers are relying on artificial intelligence technology. In the future, artificial intelligence will play a more important role in marketing segmentation scenarios.

With the vigorous promotion of new infrastructure plans and the development and implementation of 5G communication, cloud computing, big data, and the Internet of Things, artificial intelligence technology will be applied to more scenarios. With the steady implementation of favorable policies, infrastructure construction, and basic scientific research, the artificial intelligence sector has experienced rapid development. At the same time, relevant AI products, services, and solutions will gradually mature and enter the stage of large-scale monetization. Enterprises with strong comprehensive strength and fast technological research and development pace are expected to receive rich revenue returns.

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