While the world still debates whether large models are merely an expensive "bubble," Liu Tao, Senior Vice President of Kingsoft Cloud Holdings Ltd, asserts that it is not. Supporting his argument is the ongoing "Vibe Coding" trend—when Claude Code can proficiently use its own written code to iterate itself, the "singularity" of robots building robots and code writing code has tangibly touched the spine of the industry. In response to this shift, Kingsoft Cloud has made its move. On January 21, Kingsoft Cloud announced a comprehensive upgrade of its intelligent computing platform, "Kingsoft Cloud Starstream," which not only includes a training and inference platform covering the entire model lifecycle but also officially released a robotics platform and model API services. This established cloud service provider is attempting to actively participate in the contest for future productivity dominance through a self-reinvention of its identity. Over the past year, the demand for intelligent computing has continued to grow, with the primary driver quietly shifting from the training needs of leading enterprises to an explosion on the inference side. The data is very直观; Volcano Engine's daily Token call volume has surged past the 50 trillion mark. The spillover demand for models like Doubao, Qianwen, and Yuanbao is expanding at an incredible speed. This explosive consumption of Tokens is essentially the process of AI landing in real-world scenarios. For enterprises, large models are no longer just embellishments in PowerPoint presentations but genuine tools for reducing costs and improving efficiency. "We have been monitoring when inference would explode; this growth rate surpasses all past understanding of IT infrastructure,"感慨ed Sun Xiao, Assistant President of Kingsoft Cloud. Against this backdrop, Kingsoft Cloud positions itself as an engineering companion, with a very pure logic: since large models are becoming the "brain" of the Internet of Everything, cloud vendors need to provide the corresponding "circulatory system"—stable, efficient, and extremely cost-effective Token services. Kingsoft Cloud is following a logic evolution path driven by "tasks." In 2023, the industry theme was "large-scale intelligent computing network infrastructure construction," competing on the ability to manage underlying heterogeneous resources. By 2024, the focus evolved to "platformization and Serverless," with the core being the shift from resource delivery to task delivery. Looking ahead to 2026, the upgraded "Kingsoft Cloud Starstream Platform" is anchored on three core themes: pursuing efficiency gains, building industry platforms, and accelerating inference deployment. This transformation lies in the fact that training tasks in the intelligent computing era are extremely fragile; under large-scale computing clusters, any slight hardware fluctuation can cause an entire training task to中断. To solve this "nail," Kingsoft Cloud developed a set of self-healing technology based on fault perception. This system can perform graded handling of hardware faults and combined hardware-software faults. Some faults can be resolved with a restart, while others require immediately initiating a replacement strategy. Sun Xiao revealed that this mechanism can achieve "second-level perception" and rapid processing. This means that even if underlying hardware fluctuates, a client's round of training tasks can proceed smoothly without interruption. Embodied intelligence is what Kingsoft Cloud sees as the "second half" of intelligent computing cloud and a key future focus. Whether it's autonomous driving or humanoid robots, the industry is still in a "chaotic scene," blooming with a hundred flowers yet plagued by固化的 pain points. Different manufacturers focus on the brain, some on the cerebellum, while others are stuck on data simulation. The "Kingsoft Cloud Starstream Robotics Platform" released by Kingsoft Cloud attempts to create a full-chain闭环 from data collection, storage, and labeling to model training, deployment, and simulation. Sun Xiao believes that the challenge robotic scenarios need to solve is the deployment难题 of "going from algorithm development to real-world scenario deployment." Taking autonomous driving as an example, the model resides in the vehicle, but training happens in the cloud. This might not require extremely high computing density, but places immense demands on memory and the ability to process multi-modal point cloud data. By constructing a闭环 data platform, Kingsoft Cloud enables clients to more conveniently receive and process these massive amounts of data. Looking to the future, Liu Tao painted a picture: starting from 2026, home-scenario robots will gradually become a reality. From initially helping the elderly pick up socks and towels to eventually assisting with daily life, this is a trillion-yuan track spanning 5 to 10 years. What Kingsoft Cloud aims to do is become the "foundation" and "engine" for this trillion-yuan赛道. As the traditional public cloud market enters a phase of存量博弈, intelligent computing cloud is bringing全新的 growth opportunities. The fact that Kingsoft Cloud achieved a 120% year-on-year growth rate in the third quarter of last year is essentially because it seized this wave of productivity restructuring. Adhering to its commitment of "not developing large models" has, conversely, made Kingsoft Cloud extremely open in terms of ecosystem building. Sun Xiao坦言 that their responsibility is to provide the most stable and cost-effective Token services based on open-source models and leveraging their self-developed technology. When popular models are released in the industry, Kingsoft Cloud can launch inference services on the same day, a response speed that ranks among the top in the sector. In the intelligent computing era, supporting products are undergoing dramatic changes. The past focused on compute, storage, and networking; now, the core is the technology stack centered on inference acceleration (including engines, operator optimization) and the ecosystem built around Agents. Kingsoft Cloud is aggressively reducing inference latency and improving throughput performance through techniques like PD separation (prefill and decode separation) and quantization. Even behind certain blockbuster games, Kingsoft Cloud is providing full-stack cloud services. During the heavy-load, high-concurrency server launch phase, Kingsoft Cloud, through a platform-based approach combined with heavy engineer support mechanisms, steadily supported the influx of massive numbers of players. This experience in极限压测, accumulated from game support, is now being移植 to the battlefield of large model inference. The cloud market of the past decade was a game about resource scale, where cloud vendors played a role akin to "public utilities" like water, electricity, and gas. By 2026, the "involution" on the technology front will continue. From larger parameter counts to more advanced computing methods (like MLA or linear Attention), domestic large model manufacturers are still疯狂 pursuing the limits of efficiency. However, the real watershed lies in "applications." The practical application of video generation, the generalization of VLA models in vehicles and robots, and the penetration of Agents into people's daily lives will cause inference demand to grow exponentially. The红利期 of intelligent computing cloud will not last forever. Only those vendors capable of solving极限 engineering challenges,打通ing industry data闭环s, and providing extremely cost-effective Tokens will remain standing when the tide recedes. "We have already laid a solid customer foundation; in the next 3 to 5 years, Kingsoft Cloud will undergo a significant change," Liu Tao said信心满满. As the gears of intelligent computing accelerate, this race concerning productivity dominance has just entered its most brutal, yet most thrilling, deep-water zone.
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