Future opportunities and development measures for AI commercial implementation

Future opportunities and development measures for AI commercial implementation The application of artificial intelligence (AI) in the business field is ushering in unprecedented opportunities and development. As technology continues to advance and business needs continue to grow, AI has shown great potential in various industries. In the future, AI business implementation will become an important direction that enterprises are competing to explore. In terms of future opportunities for AI commercial implementation, the first is the widespread application of data. AI requires large amounts of data for training and learning, and the amount of data companies now have is growing. By making full use of this data, enterprises can better apply AI technology and improve business efficiency and innovation capabilities. Secondly, the commercial implementation of AI will also bring more intelligent products and services. With the continuous development of AI technology, various intelligent products and services will gradually emerge. For example, intelligent customer service, intelligent recommendation systems, intelligent logistics, etc. These products and services will bring more business opportunities and competitive advantages to enterprises. In terms of development measures for AI commercial implementation, the first step is to strengthen technology research and development and innovation. Only by continuously promoting the research and development and innovation of AI technology can we better meet business needs and provide better products and services. Secondly, strengthening talent training and team building is also crucial. The commercial implementation of AI requires professional technical talents and team support. Only with high-quality talents and teams can we better cope with business challenges and promote the application of AI technology. In short, the future of AI commercial implementation is full of opportunities and challenges. By making full use of data, promoting technology research and development and innovation, and strengthening talent training and team building, enterprises can seize opportunities and achieve better business development

Future opportunities and development measures for AI commercial implementation

Edge AI will usher in a development peak in the short term (1-2 years)

Highlighted technological advantages and increased market demand are two factors that jointly accelerate the arrival of the peak of edge AI development. The technical advantages of edge AI such as low latency, low cost and high privacy protection can effectively help the development of multiple AI implementation scenarios; the cloud-edge architecture with edge AI as an important component helps realize cloud-edge resources, data, applications, Integrated development of operation, maintenance, scheduling and security.

Embodied intelligence and general artificial intelligence are technologies with development potential in the mid-term (3-5 years) and long-term (more than 5 years) respectively

Embodied IntelligenceWith the development of large models and the increasing maturity of AI basic technology, it is expected to become the next wave of AI development in the medium term; General artificial intelligence is the key to the development of AI Goal, relying on its characteristics of "having similar human intelligence and being able to make independent decisions, learn and execute", has become an area of ​​long-term concern and exploration in academia and business circles.

Supply side: Data, algorithms and computing power are the key breakthroughs to improve the value of solutions

The supply side, represented by the government and service providers, should continue to improve the comprehensive value that AI technology brings to end customers by improving data quality, increasing algorithm flexibility, and breaking through computing power limitations.

Demand side: An all-round development path helps to unleash the scenario value of AI technology

There are problems on the demand side such as unclear AI cognition, unreasonable business teams, and lack of implementation planning. It is necessary to cultivate good AI technology implementation and value improvement from the dimensions of strategy formulation, team formation, and technology implementation evaluation plan formulation. soil.

What the big guys say

The following is an excerpt from the report:

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