Insights on AIGC Development and Commercial Applications by Baidu's Chief Architect

AIGC (Artificial Intelligence Generated Content) has become a hot topic in the AI field, with generative large language models (LLM) delivering impressive performance in usability, multi‑turn dialogue understanding, and reasoning tasks.

Li Shuanglong, Baidu's Chief Architect for Commercial AI, discussed the current state of AIGC deployment and its future impact on business models during the first Baidu Commercial AI Technology Innovation Competition.

Current application scenarios

In NLP, the industry has entered the AGI stage, with generative LLMs becoming the mainstream research direction. Baidu launched the next‑generation knowledge‑enhanced LLM "Wenxin Yiyan" in March, iterating four times within a month and improving inference performance by nearly tenfold.

In multimodal AI, advances such as Vision‑Language Pre‑training (VLP) and Diffusion Models have greatly improved the controllability and quality of text‑to‑image generation. Baidu's "Wenxin Yige" exemplifies mature text‑to‑image generation with high usability.

In the digital‑human domain, 2D avatar humans are being adopted in marketing, short‑video, and live‑streaming scenarios, offering low production cost, realistic effects, and high technical maturity.

Commercial deployments by Baidu

• Creative text generation: Leveraging Baidu's large‑scale language model, a few prompts can automatically produce marketing copy, significantly boosting copy creation efficiency and ad conversion rates.

• Video content creation: An end‑to‑end 2D digital‑human solution automates script generation and avatar video production, reducing the cost and complexity of traditional video ads.

• Lead‑generation bots: A self‑developed lead‑robot powered by a massive dialogue model replaces manual dialogue templates, offering 24/7, scenario‑aware, personalized customer interactions.

These applications have already delivered measurable client value and business growth.

Future directions of AIGC

Li identified four key layers for AIGC evolution:

Engineering: Scaling model training, inference efficiency, and stability.

Algorithms: Enhancing multi‑turn dialogue understanding, long‑sequence generation, high‑fidelity image synthesis, and end‑to‑end long‑video generation.

Data: Prioritizing data quality over sheer volume to build a robust data production ecosystem.

Applications: Leveraging scenario‑driven user feedback for deep joint optimization of generation and usage.

The competition’s two main topics—"Commercial Conversion Behavior Prediction" and "AIGC Inference Performance Optimization"—reflect these challenges. Li invited young talent to join Baidu in tackling these problems and accelerating AIGC penetration across industries.