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Introduction:

The rise of large language models (LLMs) has sparked a wave of innovation across various industries, and search advertising is no exception. Alimama, Alibaba’s marketing technology platform, is at the forefront of exploring how these powerful models can revolutionize search advertising. This article delves into Alimama’s 2024 strategies and practical implementations of LLMs in search advertising, examining the potential for a new era of model evolution.

Historical Evolution and Key Routes:

As transformative technologies emerge, understanding the historical evolution of search advertising models is crucial. Alimama has identified three key routes – a main line, a hidden line, and an auxiliary line – to guide its understanding of the underlying logic behind technological upgrades.

Harnessing Computational Power and Scale:

A core focus for Alimama is leveraging computational power to uncover scale laws within the search advertising domain. This involves systematically exploiting computational advantages to drive technological advancements.

The Frontier of Exploration: Perception and Reasoning:

Alimama’s exploration focuses on two key areas: perception and reasoning.

  • Enhanced Perception: Alimama aims to improve the model’s ability to understand and integrate diverse information, including both system content and user behavior. This involves optimizing the quality of multi-modal representations, moving beyond traditional ID-based representations, and building richer models of the perceived world.
  • Advanced Reasoning: Alimama is developing large models for user sequence analysis, combining generative and discriminative methods to continuously enhance reasoning capabilities.

LLMs Transforming Search Advertising Systems:

Large models are fundamentally reshaping Alimama’s search advertising systems. This transformation relies on a new paradigm of model iteration, encompassing both pre-training and post-training techniques.

Conclusion:

Alimama’s exploration of LLMs in search advertising demonstrates the immense potential for innovation and value creation. By focusing on key areas such as perception, reasoning, and model iteration, Alimama is paving the way for a new generation of search advertising models that are more intelligent, effective, and adaptable to the evolving needs of users and advertisers. The integration of LLMs promises to unlock new levels of performance and personalization in the search advertising landscape.

References:


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