There are several reasons why artificial intelligence is booming now:
Technical level
- Algorithm innovation: Deep learning algorithms continue to break through, such as convolutional neural networks in image recognition, recurrent neural networks in natural language processing has achieved great success, so that AI can handle more complex tasks. New algorithms such as generative adversarial networks and reinforcement learning continue to emerge, enabling AI to have stronger learning and creative capabilities.
- Computing power enhancement: Dedicated hardware such as GPU and TPU provides powerful parallel computing capabilities for AI model training, greatly shortening training time. The development of cloud computing technology provides flexible and scalable computing resources, lowers the threshold of AI technology, and facilitates large-scale training and application by enterprises and research institutions.
- Rich data: The popularity of the Internet and the development of the Internet of Things produce massive data, providing rich materials for AI training. The improvement of data cleaning, labeling and other technologies enables AI to make more efficient use of data and improve model accuracy and reliability.
Market demand level
- Enterprise cost reduction and efficiency needs: production automation and intelligent quality testing can be realized in the manufacturing industry; Risk assessment and fraud detection in the financial sector; The medical industry can assist in diagnosing and analyzing images to help enterprises improve efficiency, reduce costs, and improve quality.
- Consumer personalized demand: Consumers expect to get more convenient and personalized services. The application of AI in smart home, intelligent customer service, intelligent recommendation and other fields can meet people's needs for improving the quality of life and provide personalized products and service experiences.
Policy and investment level
- Policy support: Governments regard artificial intelligence as a national strategy, issue policy documents, set up special funds, provide tax incentives, and strengthen talent training to create a favorable environment for AI development.
- Investment drive: The huge development potential of artificial intelligence has attracted a large number of venture capital, private equity and government investment funds. Sufficient funding allows AI companies to accelerate technology research and development, expand the market, and promote technological progress and commercial applications.
Industry convergence level
- Promote new business models: AI and the Internet of Things to achieve intelligent transportation, intelligent logistics; The combination of blockchain with improved data security and system transparency has spawned many new business models and formats.
- Promote industrial upgrading: traditional industries use AI technology to achieve digital and intelligent transformation, such as precision agriculture in the field of agriculture, and achieve accurate monitoring and management of farmland through AI technology to improve agricultural production efficiency and agricultural product quality.
Talent and scientific research level
- Perfect talent training system: Universities and scientific research institutions have opened AI related majors and courses, and trained a large number of professional talents. Enterprises have also set up professional artificial intelligence teams through internal training, talent recruitment and other ways to provide human support for the development of the industry.
- Increased research collaboration: Growing collaboration between global research institutions and companies is accelerating research and development and innovation in AI technologies by sharing data, technologies and resources. Interdisciplinary research is also deepening, and the integration of computer science, mathematics, physics, biology and other disciplines provides new ideas and methods for the development of artificial intelligence.