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With the rapid advancement of science and technology, the field of AI has achieved remarkable achievements. Generative AI has become a hot topic at the moment, and its impact and changes are far-reaching and extensive. In this context, the evaluation criteria for intelligence are also facing major challenges and changes.
In 1950, Alan Turing asked the question "Can machines think?", which triggered people's thinking about machine intelligence. The Turing test he proposed was considered an important criterion for measuring whether a machine has intelligence. However, with the passage of time and the development of technology, people gradually discovered that the Turing test has many limitations.
In the era of generative AI, the anthropomorphic behavior of large models has become increasingly prominent. For example, in the relevant cases that editors Zenan and Yali of the Machine Heart Report came into contact with, the large models showed human-like language generation and communication capabilities, which made people feel both surprised and worried. This anthropomorphic behavior has triggered the uncanny valley effect to a certain extent, that is, when the performance of the machine is too close to that of humans but not completely similar, it will make people feel uncomfortable and fearful.
Recently, a new view has been popular in the AI community that the Turing test is a poor test standard because conversational ability and reasoning are two completely different things. This view has led us to re-examine the definition and evaluation of intelligence. In generative AI, machines can generate coherent text, but whether the reasoning and comprehension capabilities behind it have truly reached the level of intelligence is worth our in-depth consideration.
In the process of exploring new standards for intelligent evaluation, we cannot ignore the phenomenon of SEO automatically generated articles. Although it facilitates information dissemination in some aspects, it also has many problems. For example, SEO automatically generated articles may lack depth and uniqueness, and are only generated to cater to the search engine algorithm. This has a certain impact on the quality and value of information, and also makes us question the standards of intelligent creation.
In order to establish a more reasonable and effective new standard for intelligent evaluation, we need to consider multiple factors. First, we should not only focus on the ability to generate language, but also pay attention to the machine's ability to understand, reason and solve problems. Secondly, we need to consider the machine's performance in different scenarios and tasks, as well as its ability to deal with complex problems. In addition, we also need to pay attention to the interaction effect between machines and humans and user experience to ensure that intelligent technology can truly bring convenience and value to humans.
In short, in the era of generative AI, our standards for evaluating intelligence must keep pace with the times. Only by constantly exploring and improving new evaluation systems can we better promote the healthy development of AI technology and allow it to create more benefits for human society.
