Artificial Intelligence: Addressing Challenges in Moving from Weak AI to Strong AI

According to reports, the main forum of the “Artificial Intelligence Big Model Technology Summit Forum” hosted by the Chinese Artificial Intelligence Society opened in Xiaoshan, Hangzhou. At the forum, Zheng Qinghua, President of Tongji University, pointed out when discussing the future research direction of AI that currently, Al technology is not suitable for scenarios such as boundary uncertainty, strong adversarial game, high real-time response, high complexity of the environment, and incomplete information. This is the pilot for the development of weak Al to strong AI and super Al. Meanwhile, Zheng Qinghua pointed out that currently, we are facing three challenges. The first challenge lies in the limitations of current methods in obtaining common sense, implicit, and abstract knowledge, which are difficult to mine; The second challenge lies in the integration of memory and cognitive knowledge, while the current methods face limitations such as strong perception but weak cognitive ability and high computational costs; The third challenge lies in interpretable knowledge reasoning. The current methods are limited to issues such as difficulty in causal inference, weak anti factual reasoning ability, and poor interpretability.

Zheng Qinghua, President of Tongji University: Three Major Challenges Faced by Current AI Technology

Artificial intelligence (AI) has come a long way since its inception. However, we are still far from achieving the goal of strong AI, which appears to be the ultimate dream of the technology. At the “Artificial Intelligence Big Model Technology Summit Forum” hosted by the Chinese Artificial Intelligence Society in Xiaoshan, Hangzhou, Zheng Qinghua, President of Tongji University, pointed out some challenges we are currently facing as we attempt to shift from weak AI to strong AI.

Understanding AI’s Limitations

AI is not suitable for all scenarios, which has made it challenging for researchers to develop its potential to the fullest. Strong adversarial games, complex environments, high real-time response, incomplete information, and boundary uncertainty limit the capabilities of AI. Therefore, developing weak AI to strong AI or even super AI requires much effort.

The Three AI Development Challenges

Zheng Qinghua highlighted three main challenges that AI needs to overcome before it can advance to strong AI:

1. Limitations of Current AI Methods

One of the significant challenges of AI development involves the inability to obtain common sense, implicit, and abstract knowledge. This knowledge is vital in developing AI that can function independently. However, most AI models struggle to process and analyze information beyond their training dataset.

2. The Integration of Memory and Cognitive Knowledge

Many AI models can recognize patterns and provide predictions based on the data they have encountered. However, current methods face limitations in integrating memory and cognitive knowledge. This limitation results in strong perception but weak cognitive ability and high computational costs.

3. Interpretable Knowledge Reasoning

The current AI models lack the ability to reason based on interpretability, leaving researchers to rely on statistical models to identify patterns. Causal inference and weak antifactual reasoning ability represent some of the issues that researchers face when reasoning based on AI.

Conclusion:

The current AI research faces several challenges. Understanding and addressing these challenges would be a significant milestone in the development of strong AI. The limitations of current methods in obtaining common sense and integrating memory and cognitive knowledge, as well as interpretability, present significant roadblocks that innovative research must address.

FAQs

1. What are some limitations of AI?
Ans: Currently, Al technology is not suitable for scenarios such as boundary uncertainty, strong adversarial games, high real-time response, high complexity of the environment, and incomplete information.
2. What is the biggest challenge in AI development?
Ans: AI development faces several challenges, but the most significant challenge is integrating memory and cognitive knowledge.
3. Why is developing strong AI challenging?
Ans: Developing strong AI is challenging because of limitations in current models to obtain implicit and abstract knowledge, integrate memory and cognitive knowledge, and reason based on interpretability.