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li yanhong believes that the gap between large models is multi-dimensional. the gap in understanding, generation, logic, memory and other capabilities makes people pay more attention to the comparison of these aspects, but ignores the dimensions of cost and reasoning speed. although some models have achieved the same level of effect, they are still inferior to advanced models due to their high cost and slow reasoning speed.
he further explained, "before the era of big models, people were used to the idea that open source meant free and low cost." for example, open source linux, because people already had computers, using linux was free. but this is not the case in all fields. inference of big models is a very expensive process, and open source models do not provide computing power. people have to buy equipment themselves, which makes it impossible to achieve efficient use of computing power. "open source models are not efficient."
li yanhong believes that in the fields of teaching and scientific research, the open source model is valuable; but in the commercial field, when the pursuit is efficiency, effect and minimum cost, the open source model has no advantage. he analyzed the development direction of different models and believed that intelligent agents are the key direction of future development. through artificial intelligence technology, the integration of humans and machines can be achieved, allowing machines to complete work independently.
robin li believes that with the advancement of ai technology, the future society will rely more on intelligent agents, which will play an important role and gradually replace traditional working methods. he pointed out that "although many people are optimistic about the development direction of intelligent agents, to date, intelligent agents are not a consensus" and "there are not many companies like baidu that regard intelligent agents as the most important strategy and development direction of large models."
li yanhong's views reflect that in the era of artificial intelligence, efficiency and effectiveness have become the core goals. as technology continues to develop, we will witness more new breakthroughs and more powerful ai applications.
