Recently, a team of researchers from a number of universities worked with theAI technologyThe company Aizip joined forces to say that it is now possible to make large language models self-replicating to some extent. This breakthrough will provideAIfield opens up new possibilities and is expected to drive the development of small AI tools.
According to Aizip CEO Yan Su, they are utilizing thelarge modelto build smaller models, like a big brother helping his little brother progress. This is a step toward a largerartificial intelligence (AI)A first step in the work of self-evolution and a first step on the road to showing that AI models can be built.
The team is now focusing on developing miniature AI solutions with very specific functionality and at a fraction of the cost, and says that the design process can now be automated by smarter AI. This means that small, functionally specific AI tools can be created quickly and efficiently by utilizing the capabilities of larger models.
This breakthrough will bring many positive effects to the AI field. First, small AI tools will be more widely used in specific scenarios, such as in healthcare, education, and finance. These tools can be customized and developed according to specific needs, improving efficiency and accuracy.
Second, this technology is expected to reduce the development cost of AI tools. By utilizing the self-replicating capabilities of large models, the need for large amounts of data and computational resources can be reduced, thereby lowering development costs. This will enable more businesses and organizations to easily develop and deploy their own AI tools.
In addition, the success of this technology also proves that AI models have the ability to self-learn and evolve. Through continuous learning and optimization, AI models can gradually improve their performance and efficiency, laying the foundation for future AI development.
The realization that large models can now be self-replicating in the creation of small AI tools is a landmark development. It will bring more possibilities to the AI field and is expected to drive the development and application of small, function-specific AI tools. We look forward to more surprises and breakthroughs from this technology in the future.
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