Baidu Finds Its Groove After Another Top Ranking

Nine years ago, when AlphaGo defeated Lee Sedol in a Go match, few could have predicted the powerful way artificial intelligence would enter our lives.

Initially, it seemed AI was less a mysterious enigma and more a readily available tool – a chatbot on demand or an image and video generation tool triggered by a simple sentence.

Before long, however, AI’s reach extended far and wide.

New phone and computer launches feel incomplete without AI integration hype. Medical imaging diagnostics might be initially performed by AI rather than a doctor. And the sheer number of AI-powered features popping up in apps is head-spinning.

Especially noteworthy is the rise of embodied AI, manifesting in a way that blurs the line between science fiction and reality, putting humans and robots in shared spaces.

Beyond robotic performances at Spring Festival galas, you might encounter a marketing robot or robotic dog on the street. Companies are increasingly leveraging robots to energize marketing events.

These robots are getting more sophisticated. Once clunky and slow, they can now run, jump, perform backflips, and even box. There are even humanoid robot sporting events.

The pace of development in the AI industry is breathtaking.

Frankly, if you’re still talking “Internet+,” it’s time to catch up. We’re already firmly in the “AI+” era.

Businesses across sectors are actively exploring or implementing AI to reshape and disrupt existing models, fearing being left behind.

This progress is undoubtedly fueled by groundbreaking technological advances. However, a closer examination reveals cloud service providers are the unsung heroes behind these seemingly dazzling AI applications.

While cloud service providers might not be the most exciting topic, let’s explore something interesting first.

Consider embodied AI. Do you think these running, jumping robots evolved entirely on their own? Think again.

The hurdles facing embodied AI are no joke.

Data scarcity, algorithmic shortcomings, and limited generalization capabilities are all significant challenges. In essence, robots aren’t yet intelligent enough; they can show off some moves, but they’re not ready for real work.

Data scarcity alone is a major obstacle.

The industry is actively addressing the lack of high-quality data.

Real-world data is expensive and scarce, so Nvidia developed the Omniverse platform to stress-test robots in a digital-twin physical world. Some companies also specialize in real-world robot data collection.

Building datasets is another common approach. The Beijing Humanoid Robot Innovation Center, for example, is accelerating the creation of million-level high-quality datasets.

However, generating this amount of data isn’t simple; it involves production, collection, and labeling, which can be a daunting task if done in-house.

This is where specialized teams come in.

The Beijing Humanoid Robot Innovation Center partnered with Baidu AI Cloud, leveraging their expertise in data collection and annotation from their experience with autonomous driving.

Moreover, Baidu AI Cloud is the clear leader in the AI public cloud market share, demonstrating its capabilities with hard data.

However, if only data was needed, any data company would suffice.

Acquiring data is just the first step in the journey; resource-intensive model training, simulation testing, and model inference are also crucial.

That’s why partnering with a full-stack AI development cloud service provider like Baidu AI Cloud is more efficient.

In terms of computing power, Baidu AI Cloud’s leading GPU cluster, Baige, excels at training and inference.

For scenarios requiring repetitive simulation and strategy optimization, such as robotics, single-card performance isn’t enough. Baige excels in its ability to ensure the stable, efficient collaboration of thousands of cards simultaneously.

With ample computing power, developers can boldly pursue their goals.

To enhance robot intelligence, Baidu AI Cloud offers the Qianfan large model platform, empowering developers to innovate freely.

The Beijing Humanoid Robot Innovation Center’s robots utilize the Qianfan platform to understand human language (precise natural language parsing) and perceive the world (multi-modal information processing).

The TianGong robot’s success in winning 100-meter and half-marathon races is, at least in part, attributable to Baidu AI Cloud.

This collaborative model has become the industry standard for embodied AI.

Leading manufacturers like Unitree Robotics have also opted for Baidu AI Cloud’s AI services.

Baidu AI Cloud embraces its position as industry infrastructure and is consistently evolving.

At the recent Baidu Create AI developer conference, Baige and Qianfan received significant upgrades.

Baige 5.0 further enhances training and inference efficiency. The upcoming launch of the Kunlun Xin ultra-node supporting trillion-parameter models promises even more sophisticated capabilities. Perhaps robot figure skating will be added to next year’s sporting event schedule.

The upgraded Qianfan 4.0 features the RFT toolchain, achieving model fine-tuning results with just a few hundred data points compared to the previous tens of thousands. This is a game-changer for data-hungry industries like embodied AI.

Beyond the real-world applications of robotics, AI is transforming the gaming world.

Even game NPCs are striving for human-like realism.

The Hong Kong University of Science and Technology’s AI village, Aivilization, features 100,000 intelligent agents, each behaving remarkably like a real person.

Creating human-like NPCs manually is impractical. While large models can be used, ensuring they are sufficiently intelligent and enabling seamless interactions with numerous players simultaneously presents a challenge.

NetEase Fuxi’s *Justice Mobile* game features AI NPCs that can engage in free-flowing conversations with players, essentially providing a beautiful game skin for a ChatGPT-like experience.

Some players are so invested in chatting with NPCs that they almost turn *Justice Mobile* into an otome game.

NetEase Fuxi partnered with Baidu AI Cloud. Baidu AI Cloud’s Wenxin character model infuses AI NPCs with the ability to understand, think, and possess distinct personalities.

Furthermore, Baige’s underlying computing resources ensure game stability under high-concurrency access, guaranteeing a smooth player experience.

With the Qianfan 4.0 upgrade, Baidu AI Cloud has not only expanded its model library but also streamlined Agent development, offering even greater possibilities for the gaming industry.

Finally, AIGC applications, such as text-to-image and text-to-video, are also resource-intensive.

Technically, ensuring the stability and consistency of generated results requires continuous model training, and hardware, system configurations, and software failures can disrupt the process.

Therefore, many prefer to outsource these tasks to cloud service providers.

For instance, Baidu AI Cloud provides ShengShu Technology with the Baige heterogeneous computing platform, boasting an effective training time ratio exceeding 98.8%.

In terms of training stability, Baige offers a suite of O&M tools to prevent cluster failures at critical moments.

The Baige 5.0 upgrade includes optimizations in network and reasoning systems. Faster communication, lower latency, and smarter scheduling strategies improve reasoning system throughput, pushing AI training and inference efficiency to new heights.

These examples highlight the critical role of cloud service providers, including Baidu AI Cloud, in laying the foundation for AI advancements across a wide range of industries, including smart terminals, smart vehicles, manufacturing, finance, and education.

With so many cloud service providers available, how should one choose?

According to a recent IDC report, the domestic market is primarily dominated by Baidu, Alibaba, Tencent, and Huawei.

Baidu AI Cloud’s performance demonstrates that the industry is increasingly competitive.

In the AI era, cloud services have evolved beyond simply stacking hardware; ensuring the efficient collaboration of thousands of GPUs is the real engineering challenge.

Baidu pioneered the “AI cloud” concept. Each product upgrade and ecosystem integration, including the “cloud-intelligence integration” strategy, addresses the question: What kind of cloud services are needed in the AI era?

Today, they have a clearer answer: The intelligent economy requires “cloud-intelligence integration and intelligence-first” cloud services.

From underlying computing power to model training to full-stack AI application development, Baidu AI Cloud allows developers to focus on refining AI applications without being bogged down by complex hardware and model deployment issues.

Just as the Industrial Revolution relied on steel, gas, and electricity, today’s AI revolution needs its own utilities.

Our imagination for AI depends on the evolution of cloud service providers.