Why has DeepSeek become the new favorite in the industry? Uncovering the AI ​​strategies behind major applications

introduction

Recently, from social platforms to e-commerce applications, from intelligent customer service to content generation tools, more and more domestic Internet products have begun to deploy an AI model called "DeepSeek". Is this phenomenon a technological breakthrough or a strategic choice? This article will analyze the underlying logic of DeepSeek's rapid rise from four dimensions: technology, cost, policy, and ecology.

1. Technological breakthrough: the dual advantages of lightweight and multi-modality

1. Industry-leading inference efficiency

   DeepSeek's core models (such as DeepSeek-V2 with MoE architecture) use **dynamic weight allocation** technology to complete complex tasks with only a small number of active parameters, and the inference cost is only 1% of GPT-4. This means that application manufacturers can achieve real-time response with lower computing power, which is especially suitable for high-concurrency scenarios (such as the customer service system for the 618 promotion).

2. Deep optimization of Chinese scenes

   Compared with international open source models, DeepSeek has been pre-trained on **10 trillion Chinese tokens**, and has a more accurate understanding of idioms, dialects, and new Internet words. For example, after a short video platform was connected, the accuracy of barrage keyword filtering increased by 37%.

3. Seamless integration of multimodal capabilities

   The newly released DeepSeek-R1 series supports **cross-modal generation of images and texts**, which can process product descriptions and main image designs at the same time, helping an e-commerce APP shorten the content production cycle from 3 days to 2 hours.

2. Cost Revolution: Open Source Ecosystem Reshapes Business Logic

Free commercial license: DeepSeek-MoE and other models use the Apache 2.0 protocol, so enterprises do not need to pay high licensing fees. Compared with a certain international closed-source model, the annual cost of medium-sized applications can be reduced by more than 8 million yuan.

Flexible deployment solutions: Support multi-level deployment from cloud API to end-side devices (such as mobile phone chips). A reading app can provide AI annotation functions even without a network connection through local deployment.

3. Policy support: a safe choice under the wave of localization

Data compliance advantage: Training data is processed throughout the country to avoid cross-border transmission risks. A financial APP successfully passed the Level 3 certification of Information Security Protection 2.0 by using DeepSeek.

Autonomous and controllable architecture: A government service platform uses the self-developed full-stack from the underlying framework to the training tool chain to achieve domestic substitution of AI modules, responding to the policy of "de-IOE in key areas".

4. Ecosystem Co-construction: The Fission Effect of the Developer Community

 Minimalist development experience: Providing a "5-line code quick fine-tuning" tool chain, attracting more than 200,000 developers. For example, a college student team used DeepSeek-7B to develop a campus psychological counseling robot in three days.

Enterprise-level support network: We have collaborated with Huawei Ascend, Alibaba Cloud, and others to launch customized optimization solutions, based on which a smart car brand has created the 2.0 version of its in-car voice assistant.

Future Outlook: The cornerstone of the AI ​​inclusive era

As DeepSeek launches the 100 billion-level MoE model and industry vertical solutions, its application scenarios will be further expanded to education, medical care, industry and other fields. Driven by both technological iteration and policy dividends, choosing DeepSeek is not only a technical decision, but also a strategic layout to seize the initiative in the AI ​​2.0 era.

Conclusion

The rise of DeepSeek reflects the transformation of China's AI industry from "following" to "running side by side". For ordinary users, a smoother intelligent experience is coming; for developers, this is a golden window period for "low-cost innovation".