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During the 2024 World Artificial Intelligence Conference in Shanghai, Baidu founder Li Yanhong's comments sparked a heated debate in the AI community.

Tech 2024-08-02 12:27:06 Source: Network
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During the 2024 World Artificial Intelligence Conference in Shanghai, Baidu founder Li Yanhong's comments sparked a heated debate in the AI community. He compared open-source to "intellectual tax," arguing that closed-source models, such as ChatGPT, are superior to open-source models

During the 2024 World Artificial Intelligence Conference in Shanghai, Baidu founder Li Yanhong's comments sparked a heated debate in the AI community. He compared open-source to "intellectual tax," arguing that closed-source models, such as ChatGPT, are superior to open-source models. This viewpoint immediately ignited online discussions.

Li Yanhong's argument primarily stems from the current performance of open-source models and large-scale data models. He believes closed-source models have an advantage in data processing and result presentation. He cited ChatGPT as an example, highlighting its powerful capabilities and outstanding performance as evidence of the superiority of closed-source models. However, Li Yanhong failed to mention specific representatives of open-source models with large data sets. In reality, the open-source camp possesses significant strength.

Companies like Tesla, Facebook, as well as domestic giants like Alibaba Cloud and HarmonyOS have all launched open-source models with large data sets. They boast extensive project support and provide a crucial path for future domestic replacements. Li Nan, former Vice President of Meizu, directly criticized Li Yanhong, stating that his remarks were an attempt to denigrate open-source for self-interest. He emphasized that open-source will become a crucial direction for AI development as OpenAI tightens its grip. He further questioned Li Yanhong, asking what Baidu has done for domestic replacement.

Li Nan's comments garnered support from numerous netizens. Baidu, as a company with significant influence, has enjoyed development opportunities amidst the wave of domesticization. However, it has yielded little fruit in the past two decades. It has neither contributed to domestic replacement nor achieved breakthrough advancements in technology. Conversely, its commercialization atmosphere is thick, even integrating a large number of Fukuda-affiliated hospitals into Baidu search. The infamous keyword bidding, notorious in the past, continues to harm many individuals today.

Li Yanhong's remarks have been interpreted as Baidu veering further down the path of pursuing commercial interests. Netizens widely expressed that a company lacking confidence and relying on external forces is destined to falter. Li Yanhong's remarks may represent the thoughts of some who are unwilling to engage in independent research or support domestic development, blindly believing that foreign technology is inherently superior to domestic technology. This mentality severely hinders the progress of domestic replacement.

Open Source vs. Closed Source: Which is Better?

Li Yanhong's comparison of open-source to "intellectual tax" has sparked widespread debate. Open source and closed source each have their advantages and disadvantages; it's not a simple matter of one being superior to the other.

Advantages of Open Source:

  • Openness: Open-source code can be viewed, modified, and used by anyone, fostering rapid technological development and iteration.
  • Transparency: The transparency of open-source code prevents black box operations and improves system security.
  • Community Building: Open-source communities comprise developers worldwide who collaborate to continuously enhance and refine open-source projects.
  • Reduced Costs: Companies can save on research and development costs by utilizing open-source code.

Disadvantages of Open Source:

  • Security: The public nature of open-source code poses potential security risks, allowing hackers to more easily find vulnerabilities.
  • Stability: Open-source code maintenance and updates are handled by the community, which can lead to version incompatibility or missing features.
  • Lack of Professional Support: Companies may lack professional technical support when using open-source code.

Advantages of Closed Source:

  • Security: Closed-source code has higher security, as the code is not publicly available, making it harder for hackers to find vulnerabilities.
  • Stability: Maintenance and updates for closed-source code are handled by the development team, ensuring code stability and functional integrity.
  • Professional Support: Companies using closed-source code can receive professional technical support.

Disadvantages of Closed Source:

  • Closed Nature: Closed-source code cannot be viewed or modified by anyone, limiting technological development and innovation.

During the 2024 World Artificial Intelligence Conference in Shanghai, Baidu founder Li Yanhong

  • Controllability: Control of closed-source code resides with the development team, potentially leading to monopolies.
  • High Costs: Companies need to pay substantial licensing fees to use closed-source code.

The Need for Collaborative Development between Open Source and Closed Source in AI

AI advancement requires the collaborative development of open-source and closed-source. Open source promotes technological innovation and reduces development costs, while closed-source ensures system security and stability.

Open Source Drives Technological Innovation:

The openness of open-source code allows developers to freely view, modify, and use code, leading to innovation and improvements. This accelerates technological iteration and development, driving progress in the AI field.

Closed Source Guarantees System Security:

Closed-source code has higher security since the code is not public, making it more difficult for hackers to exploit vulnerabilities. This is particularly crucial for applications demanding high security, such as financial and medical systems.

Collaborative Development between Open Source and Closed Source:

Open source and closed source can complement each other, working together to advance AI. For instance, companies can use open-source code to build foundational frameworks and develop closed-source code atop those frameworks to realize specific functionalities.

Future Trends in AI Development:

The future of AI development rests in the coexistence and collaboration of open source and closed source. Open-source code will continue to drive technological innovation, while closed-source code will ensure system security and stability. Companies need to choose the appropriate code model based on their specific needs.

Domestic Replacement Requires Collective Efforts from Open Source and Closed Source

Domestic replacement necessitates collaborative efforts from open source and closed source. Open source can assist companies in swiftly establishing foundational frameworks, while closed source can safeguard system security and enhance user experience.

Open Source Propels Domestic Replacement:

Open-source code helps companies quickly build foundational frameworks, reducing development costs and accelerating the process of domestic replacement.

Closed Source Supports Domestic Replacement:

Closed-source code ensures system security, enhances user experience, and boosts user confidence in domestic products.

Conclusion:

Open source and closed source each have their advantages and disadvantages; it's not a simple matter of one being superior to the other. AI development requires the collaborative development of open source and closed source; domestic replacement also needs collective efforts from open source and closed source. Companies should carefully choose the appropriate code model based on their specific needs and work together to promote the healthy development of the AI industry.

Here are some related discussion points that can expand the article content:

During the 2024 World Artificial Intelligence Conference in Shanghai, Baidu founder Li Yanhong

  • How can open-source communities better promote technological development?
  • How to balance the interests of open source and closed source?
  • How to mitigate security risks associated with open-source code?
  • How to improve the competitiveness of domestic AI products?

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