Recently, Nueva Serpent Petty Group released its first global general medicine AI Large Model Vet1, based on a billion-grade real case training that simulates veterinary clinical thinking, provides diagnostic aids, case writing, etc.
With the rapid development of our pet economy, the demand for medical care for pets continues to grow and the pains of the industry continue to surface. On the one hand, there are still significant gaps in the practice of veterinary medicine in the country, and the concentration of high-level doctors in front-line cities and the uneven level of primary care, on the other hand, the inability of pets to describe their symptoms, the reliance on doctor experience for diagnosis and the high risk of misdiagnosis in complex cases. Moreover, medical research is rapidly iterative, but it is difficult for doctors at the grass-roots level to absorb up-to-date guidance in a timely manner and lack systematic training resources. In the future, there is a need for greater talent development to meet industry needs.
As the capability of the generic large model grows, artificial intelligence will be integrated into all aspects of the pet treatment. Traditional models are no longer able to meet the medical needs of pets, and AI technology is an important force in breaking down the problem. In this context, the New Ripper Group's large-scale Vet1 model of pet care general medicine marks the beginning of a new era of “smart assistive diagnosis” for the pet medical industry.
The Chairman and Managing Director of the New Serpent Group, Peng Yong-hoon, stated that the health industry, as a front-line position for artificial intelligence, was being supported by multisectoral policies in the health-care sector, and that the practice of artificial intelligence in pets and pets was leading to industrial change and ecological innovation in the health-care sector as a result of a large and professional vertical model.
Vet1 supports telemedicine and personalized treatment through pre-training, fine-tuning and enhanced learning optimization, which can analyze minor differences in medical data. Its application will alleviate the shortage of grass-roots veterinary doctors and improve diagnostic accuracy. In the future, an AI doctor for the pets will be introduced to manage the whole scene. The technology was seen as a critical breakthrough in the medical inclusion of pets.