Cold Thinking under the AI Boom Large models have moved from generalists to experts .

Mondo Technology Updated on 2024-01-30

In 2012, a breakthrough in the field of image classification was triggered by deep learning XiArtificial intelligenceof the craze. Subsequently, the rise of large-scale pre-trained models gave a further boostArtificial intelligenceTechnological developments. From the initial image and language tasks to the presentUniversalLarge models, AI technology continues to evolve, has become manyTechnologyStandard for businesses.

However, although large models have a wide range of applications in various fields, there are many of them at presentUniversalThe large model is still in the stage of "open chat", which is difficult to bring actual productivity improvement to enterprises, and it is difficult for entertainment products to win the favor of enterprises. Therefore, the craze for large models in June of this yearFlowAfter the peak, it began to show a downward trend.

1. Limitations of general large models

UniversalThe large model was originally designed to meet the needs of people for human-computer interactionNatural language processingand other tasks, to be able to have an open small talk conversation. However, the limitation of this model is that it solves complex decision-making tasks and improves workEfficiencyand limited capacity in terms of production efficiency.

In other words, companies need a big model that can solve complex decision-making tasks in a real way, not just a model that "chats well". For example, in the field of speech translation, companies need a large model with the ability of professional translators to accurately give reliable translation results, and even be able to recognize dialects and reject mistranslations. In order to meet this demand, large models need to abide by the rules of their own domain and avoid the "illusion" problem. However, this is exactly what it isUniversalCapabilities that are difficult to possess with large models.

2. Commercialization of large models

With the development of large-scale model technology, many enterprises are beginning to realizeUniversallimitations of large models, and began to promote the implementation and commercialization of large models in specific industries and application scenarios. Google, Microsoft,Ali, and other leading enterprises have begun to accelerate the exploration of large models in subdivided vertical fieldsBusiness value。These companies are gradually realizing that they should not just be satisfied with developing a big model that "chats well", but should apply it to real industries and scenarios to improve their workEfficiencyand production efficiency.

When some companies shout that "the big model that can't be landed is meaningless", it also indicates that the big model has entered a crucial inflection point. From the technical competition toBusiness valueMonetization, the development process of large models has undergone an important shift.

3. The application of large models in vertical fields

UniversalThe development of large models has led to the emergence of vertical large models. ExceptUniversalLarge models, such as finance, pharmaceutical R&D, retail and other vertical large models, are also actively developing. In June this year, New H3C Group put forward the concept of "private domain model" and released a private domain model with industry and regional attributes - Baiye Lingxi (Linseer). This private domain model provides personalized intelligent services for specific industries and application scenarios by opening up vertical application data.

The private domain model has the characteristics of industry focus, region exclusivity, data exclusivity, and value exclusivity, which can meet the specific needs of different industries. It can be placedUniversalThe large model is built as an enterprise and industry large model for domain adaptation and industry optimization, and realizes experts in solving professional problems.

In China, there are more than 80 large models with a data volume of more than 1 billion, but these large models are mainly concentrated inUniversalField. withUniversalWith the popularity of large models, enterprises need to think more calmly and look for those areas that are not limited by established objective factors to gain a competitive advantage.

From a technical point of view, the data of the large model belongs to the customer, and even if the large model is powerful, it cannot read the private data and information of the enterprise. Just as the public cloud can't dominate the world in ChinaUniversalLarge models also don't solve all the needs of an enterprise. Therefore, the domestic large-scale model industry is also facing the realization of combining industry scenarios with foreign large-scale modelsEfficiencyHeightened demand. It can be seen that whether it is from the technology itself or the market demand, enterprises need to push large models to specific scenarios and commercial markets faster. Therefore, Xinhua III believes that the commanding heights of future large-scale model competition must be in the "private domain".

Either wayUniversal, vertical or private domain large models, the core of which lies in the landing scenario and commercialization. However, the private domain model has advantages in finding living space and growth points in the specific business environment. Taking H3C's Baiye Lingxi private domain model as an example, it has the characteristics of industry focus, regional exclusivity, data exclusivity, and value exclusivity, and can provide secure, customized, exclusive and sustainable intelligent services for customers in vertical industries and exclusive regions, and more accurately meet the specific needs of different industries.

By integrating vertical application data, Baiye Lingxi creates accurate, accurate and efficient large models in the private domain, making large models experts in solving professional problems. It provides full-process services such as data processing, model development, model training, model deployment, and model fine-tuning to help enterprises achieve intelligent transformation and enhance competitiveness in specific fields.

For enterprises, choosing a private domain model can better meet their own needs, and have greater control and data security. At the same time, the private domain model can also establish cooperative relations with the industry, achieve win-win cooperation, and promote the coordinated development of the industry. Therefore, in the development trend of large models, private domain large models will become the focus of enterprises, and the commercialization and value maximization of technologies can be realized by applying large models to specific industries and scenarios.

In the face of the trend of large-scale model boom, enterprises need to think calmly and find their own opportunities and development direction from the boom. First of all, enterprises need to have an in-depth understanding of large models and understand the technology of large modelsArchitecture, application scenarios and commercialization paths, and choose a large model that suits your needs.

Secondly, enterprises should work closely with partners such as scientific research institutions and technology providers to jointly create a large model suitable for enterprise industries and scenariosSolution。Partners can provide technical support, data processing, model training and other professional capabilities to realize the implementation and commercialization of large models. Finally, enterprises need to actively explore business opportunities in vertical fields, and apply large models to specific industries and scenariosUniversalCompetitive advantage with large model limitations.

In short, the development of large models has been made fromUniversalThe large model is changing to specialization and verticalization. Only by thinking coldly in the boom of large models, moving from "generalists" to "specialists", and applying large models to specific fields and scenarios, can the goals of landing and commercialization be achieved, and the actual value and competitiveness of enterprises can be improved.

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