When a digitally replicated "Daniel Wu" begins serving as your dedicated English coach, a completely new species is born. This isn't a preview from a science fiction movie, but rather a new business card that Baidu presented for its intelligent cloud strategy at the 2025 Baidu Cloud Intelligence Conference.

Behind "Daniel Wu" lies the integrated application of Baidu's self-developed end-to-end speech-semantic large model and "HuiBo Star" digital human technology. This represents a clear signal: Baidu is pushing AI from backstage to front stage, evolving from complex "technical availability" to universally accessible "product usability."

This sophisticated digital human is merely the tip of the iceberg. Its creation stems from Baidu Intelligent Cloud's profound self-revolution.

At the August 28th conference, Baidu Group Executive Vice President Shen Dou set the tone for this transformation: "The intelligent economy era calls for AI-first intelligent cloud." He stated frankly that AI cloud is transitioning from a cost center that spends money to a new profit center that generates revenue. Baidu Intelligent Cloud's strategy has accordingly shifted from scale-first to efficiency-first.

Behind this rhetoric lies a reconstruction of the cloud computing value system. Previously, cloud vendors competed on who had more servers and cheaper storage - this was a war about scale. Baidu believes that in the second half of the AI era, the competition is about whose intelligence is smarter, more efficient, and better able to create value for customers' profit statements. This is a war about efficiency.

To win this new war, Baidu unveiled its two core engines - Baige and Qianfan.

Baige 5.0 serves as the power engine of this revolution, representing the robust foundation that Baidu Intelligent Cloud built for the AI era. In today's environment where reinforcement learning and integrated training-inference have become the mainstream computing paradigm, simple computational power accumulation is outdated - the core lies in "efficiency-price ratio." Baige's upgrade comprehensively addresses AI computing efficiency challenges across four major directions: networking, computing power, inference systems, and integrated training-inference.

Its newly launched Kunlun chip super nodes significantly enhance computational density and inference efficiency, powerful enough to enable anyone to run trillion-parameter open-source models with a single cloud instance in just minutes. This extreme computational power has attracted cutting-edge institutions like the Beijing Humanoid Robot Innovation Center, whose released embodied world model is built on Baige's foundation, resulting in doubled research and development efficiency. Meanwhile, through partnerships with Intel and others, integrating next-generation Xeon 6 processors and Gaudi accelerator cards into the platform, Baige demonstrates an open and powerful hardware ecosystem.

While Baige 5.0 provides surging energy, Qianfan 4.0 serves as the precise, bustling "intelligent agent factory" on the ground. Baidu makes no attempt to hide its ambition, directly defining it as the industry-leading "Agent Infra" (intelligent agent infrastructure), a platform specifically designed for nurturing and deploying agents.

The factory's sophistication lies in its attempt to solve the most challenging problems enterprises face when building their own agents: making models understand you better, making agents perceptive and intelligent, turning data into fuel, and enabling agent teams to launch coordinated attacks.

Qianfan's model library has upgraded to over 150 models, not only encompassing cutting-edge video generation models like "Baidu Steam Engine," but also launching specialized models such as Qianfan Huijin financial industry model and Qianfan VL visual understanding model, capable of surpassing hundred-billion-parameter model performance on specific tasks with just billion-parameter scale.

Additionally, the newly released RFT (Reinforcement Feedback Tuning) toolchain enables enterprises to achieve ideal model fine-tuning results with one-tenth of the previous data volume (reducing from thousands to hundreds of samples), dramatically lowering technical and data barriers.

Previously, large models were bookworms living in historical data. Qianfan's exclusively launched "Baidu AI Search MCP Server" acts like installing antennas connecting agents to the real world, enabling them to obtain real-time, authoritative information and escape the hallucinations of nonsensical responses.

To address data governance challenges in the large model era, Baidu officially released the Qianfan Data Intelligence Platform DataBuilder. It helps users efficiently manage multimodal data, achieving remarkable results: 600% improvement in processing efficiency, 30% reduction in computing costs, and up to 80% decrease in retrieval and storage costs.

Facing complex tasks, Qianfan has added multi-agent collaboration modes, enabling different agents to coordinate like an organization, breaking through single agent capability bottlenecks.

When this factory operates at full capacity, we see the birth of more new species beyond the "Daniel Wu Digital English Coach." In Sany Energy's factory workshops, a visual large model named "Yijian" is becoming the "AI master craftsman" on production lines. Simply uploading a standard operation video generates an SOP detection task within minutes. When workers make operational errors, the system immediately alerts, and managers can see details in real-time, significantly reducing manual on-site inspection time.

More radical transformation occurs in the coding world. Baidu simultaneously provides weapons for two types of people: for ordinary people who don't understand code, it launched the "MiaoDa" platform. Development tasks that previously cost tens of thousands of yuan and took weeks are compressed to 10 minutes and under 5 yuan.

Since launch, users have generated over 250,000 applications on the platform, with daily active applications growing by over 500%. For professional programmers, it provides "Wenxin Kuaima," a tool positioned as an enterprise-level intelligent R&D productivity engine.

According to Baidu Engineering Efficiency Director Zang Zhi, AI can already contribute over 30%-40% of code output in enterprise R&D, and will eventually free 80%-90% of developers' energy for creative work.

This series of radical investments and transformations raises the most critical question: where does the confidence come from?

The answer lies in Baidu's financial reports. Just before this conference, Baidu's interim report showed that AI new business, built on intelligent cloud and autonomous driving, achieved quarterly revenue exceeding 10 billion yuan for the first time, running at a high 34% year-over-year growth rate. This rapidly growing business segment has built a solid safety cushion for Baidu Intelligent Cloud's own evolution and transformation.

The market is also placing real money bets on Baidu's new path. This isn't a PPT vision, but a business practice that has already gained recognition from China's core economic forces.

Data shows that over 65% of central state-owned enterprises, 80% of systemically important banks, and 95% of mainstream automakers chose Baidu Intelligent Cloud when implementing large models. Zhilian Zhaopin's case is even more direct: based on the Qianfan platform, their job-candidate matching solution not only reduced inference costs by 70%, but also dramatically shortened response time from the original 14 seconds while improving transaction conversion rates.

Shen Dou stated that AI is entering a true "super cycle." Baidu's bold gamble is precisely on the future form of this cycle. From the stunning glimpse of "Daniel Wu" at the table to the massive AI infrastructure roaring behind him, Baidu is using actions to prove that it no longer wants to be a patcher of old maps - it wants to be the rule-maker of the new world.