In an article published by Jiazi Guangnian, MIT scholar Luo Hongyin deeply explores the reasoning defects of GPT-4 and its potential solution NLEP. The article points out that although GPT-4 performs well in handling natural language generation tasks, there are irreparable shortcomings in complex inference tasks. This flaw is mainly due to the extreme empiricism of GPT-4, which is over-reliance on large amounts of data for training, and lacks an in-depth understanding of logical and symbolic reasoning.
The NLEP (Natural Language and Precision Inference Model) proposed by Luo Hongyin is regarded as the key to solving GPT-4 defects. NLEP not only generates smooth natural language, but also performs well in handling precise reasoning tasks. The proposal of this model marks the further exploration of the potential of symbolic AI in processing unstructured data and generating natural language. The emergence of NLEP may provide a new solution to the limitations of the current language model.
The article also explores the school dispute in the field of artificial intelligence, especially the opposition between empiricism and symbolism. Empiricism emphasizes learning and training through large amounts of data, while symbolism focuses more on logical reasoning and symbolic processing. Luo Hongyin believes that the current GPT-4 model is too dependent on empiricism, which leads to its poor performance in complex reasoning tasks. Symbolist AI, such as NLEP, may occupy an important position in the future development of AI.
Luo Hongyin stressed that although the current language model performs well in dealing with scenarios that tolerate noise, its reliability still has significant flaws in complex tasks requiring precise reasoning. This problem is particularly prominent in high-risk areas such as medical diagnosis and legal analysis. Therefore, developing AI models that can handle both natural language generation and precise reasoning tasks has become an important direction in current artificial intelligence research.
At the end of the article, the proposal of NLEP is not only a response to GPT-4 defects, but also an exploration of the future development direction of AI. With the continuous advancement of AI technology, the combination of symbolism and empiricism may bring new breakthroughs to the field of artificial intelligence. Luo Hongyin's research provides new thinking directions for scholars in the field of AI and opens up broader prospects for future AI applications.