Page 116 - AI for Good-Innovate for Impact Final Report 2024

AI for Good-Innovate for Impact

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Domain Business, economy
Model Training • Main training process: The proposed method utilizes a multi-interest and
and fine-tuning entity-oriented pre-training architecture designed to learn generalized
knowledge across various granularities. This architecture benefits from
the inclusion of structural information in the entity graph, setting the
stage for effective knowledge transfer.
• Main fine-tuning process: After the pre-training phase over source
domains, prototype learning is integrated. This involves the use of a
contrastive prototype learning module and a prototype enhanced
attention mechanism. These components work together to improve the
representations of users and items by leveraging adaptive knowledge
utilization.
Case Studies China (i.e. SDG 8,10).

Testbeds or APE is deployed on Alipay Mini Program Cloud: link
pilot deploy- APE is published in the publicly available paper PEACE: link
ments

25�2� Use case description

25�2�1 Description:

Amidst the surge in e-commerce, accelerated by the COVID-19 pandemic, SMEs are
increasingly turning to online platforms like mini-programs to maintain operations. However,
they encounter stiff competition from larger companies in reaching their desired customers.
Ant Personalization Engine (APE), an autonomous machine learning system, is thus proposed,
empowering small and medium-sized enterprises (SMEs) to connect with their target customers
more effectively, despite resource constraints.

APE aims to mitigate this inequality by providing SMEs with a personalized recommendation
engine that leverages large models, knowledge graph technology and AI-generated content
to enhance user engagement and drive business growth. APE delivers precise personalized
recommendations tailored specifically for SME-owned mini-programs. Additionally, integration
of AI-generated content enhances user experience, while multi-dimensional cold-start
technology ensures rapid engagement with new users, driving increased visibility and traffic.
Moreover, MLops automation streamlines operations, reducing manual intervention and
cutting operational costs.

The engine's personalized recommendation accuracy is currently being enhanced, while further
expansion across industry sectors and mini programs is in progress.

Across the world, SMEs play a vital role, contributing substantially to tax revenue, GDP,
technological innovation, and urban employment. They serve as the backbone of national
economic and social development, playing a crucial role in expanding employment
opportunities and improving living standards for people worldwide.

This case study is intricately linked to United Nations Sustainable Development Goal 8(Decent
Work and Economic Growth) and Goal 10(Reduced Inequalities). Goal 8, which focuses on
promoting sustained, inclusive, and sustainable economic growth, emphasizes the importance

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