AI large models are reshaping software development. What are the implementation prospects and pain points? | ArchSummit

With the revolutionary release of Open AI’s ChatGPT, the entire IT ecosystem is facing the reshuffle and baptism of large models (LLM).

AIG Code and AIG Action represent code generation and AI-driven software development respectively. The former helps everyone become a ten times more efficient programmer, while the latter injects the power of AI into existing software, large models Combined with end-to-end low-code development, oral requirements can be directly transformed into complete software functions.

With the rapid development of application development frameworks and the emergence of experimental autonomous models, large models are reshaping the shape of software development, allowing us to see a future where software development may be subverted.

With an AI-first and data-first mindset, many requirements can be generated automatically within the software without the need for advance planning. In terms of autonomous driving in software development, one person working with an AI team can achieve fully autonomous driving in software development. This may be a new trend in software development in the future.

Technical expert from Tencent Intelligent Creation and Content Platform Department Ji Guangfa Teacher will introduce the use of large models in business at the Shenzhen ArchSummit Architect Summit on July 21-22 to help everyone understand AI Applications in Software Development, learn how AI is used in code generation and software development, and how they improve development efficiency and software functionality.

At the same time, it helps everyone gain insight into future development trends and learn about new software interaction experiences, software development autonomous driving and other new trends, as well as the rapid development of application development frameworks and the emergence of experimental autonomy models, which will help the audience Grasp future industry trends.

Secondly, architects think about their career development and inspire new innovative thinking. By understanding the new applications and attempts of AI in software development, they can generate new innovative thinking about their own work or projects.

Dr. Li Wei, engineering VP from Mobvoi, is a senior expert in the field of NLP. This time he will come to the ArchSummit Architect Summit to introduce the prospects and pain points of AI large model implementation, and also talk about it. Opportunities and challenges faced by engineers and architects.

It is only a matter of time before LLM can be implemented on a large scale in various IT field scenarios. There are two trends in the value generated by LLM implementation that deserve attention.

LLM Prompt Project can be directly applied to education, other languages ​​and knowledge-based work, thereby empowering related fields. This is the reshuffling effect brought by LLM, which brings opportunities for nationwide entrepreneurship and scenario penetration to product managers, domain experts, data workers, and Power Users.

The other is the baptism of large-scale field applications for existing field applications. This requires combining the capabilities of general LLM with domain data (such as industry specifications, operation manuals, etc.) and domain knowledge bases or knowledge graphs, and designing application processes based on business logic to provide services in domain scenarios.

Although the latter method faces some challenges, it is still actively explored in the industry and has broad development prospects. Architects and engineers need to actively pay attention to and embrace the application trends of this technological revolution and invest in it.

In this speech, Dr. Levi will introduce the shuffling scenario caused by large models: it is happening (education, such as ToC Copilot, plug-ins, prompt engineering). For example, the baptism scene is in progress (such as the ToB module that interfaces with database and scene data)

Help everyone understand what the revolutionary changes in AI (large model LLM) mean, and its impact on the entire IT ecosystem: the arrival of the national entrepreneurship wave; have a general understanding of LLM prompt projects and plug-in forms, and embrace large models instead of Fear of large models.

Mr. Li Bo, Technical Director of SF Technology has been deeply involved in cloud native applications, edge computing, HPC high-performance computing, enterprise AI empowerment and hybrid cloud data compliance for many years. He is good at applying advanced industrial practices. Develop advanced AI engineering technology to create sustainable, low-cost AI enterprise-level solutions.

This time Li Bo will share the application scenarios of LLM in enterprise digital transformation and upgrading at the ArchSummit conference, the model selection principles for each type of scenario, and how to understand and comprehensively apply Embedding Model, Vector Database, Plugin System, and Prompt Tuning. LLM and other technical means achieve our application goals.

The technical points included here, such as LLM application platform architecture design and core technologies: NLP multi-task system, Prompt self-optimization, enhanced front-end small model design, knowledge segmentation, etc. At the same time, the evolution direction of new technologies in the LLM field will be introduced, and discussions from multiple angles will prove that it has a broad and far-reaching impact on the digital transformation and upgrading of enterprises.

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