Recently, the founder of 360Zhou HongyiAt the "2023 Fengma Niu Year-End Show", I shared my thoughts on 2024.Large ModelTen predictions of development trends, calling on enterprises to fully investAI, establish "AI faith".
Zhou Hongyi believes that future innovation opportunities will mainly focus on the field of large models, so he put forward ten predictions for the development trend of large models.
Zhou Hongyi's top ten predictions for the big model include:
- Large models have become standard in digital systems and are ubiquitous;
- Open source big models are experiencing an explosion;
- "Small models" emerge and run on more terminals;Industry level;
- The large-scale enterprise market will rise and develop in the direction of depth, industrialization and verticalization;
- In terms of technology development and application, Agent intelligence will stimulate the potential of large models and becomesuperProductivity tools;
- At the same time, 2024 will be the year of large-scale model application scenarios, and "killer" applications will emerge;
- Multimodality becomes standard for large models;
- AIGC features such as Wensheng pictures and Wensheng videos have experienced breakthrough growth;
- Embodied intelligence empowers the booming humanoid robot industry;
- Large models will drive breakthroughs in basic science.
In his exchange with foreign counterparts, Zhou Hongyi shared the current situation of the US industry going all in on AI, and stressed the importance of finding incremental markets through AI innovation. He said that he is a firm believer in development, and believes that the big model has already started a new round of industrial revolution, and that not developing will be amaximumunsafe factors.
Zhou Hongyi called on more companies to establish "AI faith" and fully invest in AI innovation. He emphasized that innovation is not just about inventing new things, but also about reshaping "old businesses" with new methods. He cited companies such as Microsoft as examples of companies that have successfully reshaped products and business processes through large models. Therefore, he suggested that companies include "AI content" in business assessment indicators to evaluate the performance of business departments in terms of resource investment in AI, talent concentration, product conversion efficiency, and employees' familiarity with AI open source projects and products from a more comprehensive perspective. This move is expected to help companies better adapt to future AI development trends.