With the emergence of artificial intelligence technologies like deep learning, there has been a significant surge in demand for large-scale computing resources. This has greatly facilitated the rapid development of the artificial intelligence computing industry. In recent years, scientific and technological concepts such as big data, cloud computing, blockchain, and artificial intelligence have experienced exponential growth. The application of these technologies heavily relies on robust computing power, commonly referred to as "AI computing." AI computing encompasses various components including AI chips, AI servers, intelligent computing centers, large models, cloud computing services, edge computing, etc. Over time, AI computing has evolved from merely providing hardware and software resources to offering comprehensive computational services and creating an application service ecosystem. This transformation plays a crucial role in ensuring the advancement of China's society and digital economy. Consequently, China is actively pursuing a multi-faceted strategic layout for AI computing.
Within the entire AI industry chain lies Nvidia's involvement in producing AI chips – often likened to being the provider of shovels during a gold rush era. However powerful these computational chips may be on their own accord; they require server infrastructure along with compute clusters that can deliver immense processing power necessary for training large models. And behind this requirement lies one essential component: optical modules! These optical modules facilitate data communication between computer cards through fiber optics – acting as on-ramps onto highways if we were to compare them metaphorically speaking. While Nvidia boasts world-leading capabilities in manufacturing high-performance AI chips without high-speed optical modules it would be limited in its potential impact within this domain.
In essence then - optical modules serve as vital conduits within the computa.
The GPU capacity is insufficient, leaving Nvidia's CEO Jensen Huang in a state of exhaustion. Each GPU must be equipped with 6-8 high-speed optical modules. In response to this challenge, Jensen Huang can only resort to placing frantic orders with optical module manufacturers. This not only addresses Nvidia's immediate needs but also prepares for the future. As Nvidia gears up for the release of its next generation GPUs, it is internally testing new high-speed optical modules. Beyond cloud computing, the artificial intelligence revolution has created an even more explosive market for all optical module manufacturers.
In 2012, on the other side of the ocean, Jensen Huang spearheaded Nvidia's comprehensive integration of AI. In the subsequent years, the company introduced a series of groundbreaking GPUs that revolutionized the AI industry and reshaped our world. Despite their distinct architectures, these GPUs rely heavily on interconnection and require more robust cluster computing power, which is impossible without optical modules and manufacturers specializing in them. By 2023, with unprecedented global frenzy to acquire Nvidia GPUs along with 400G/800G optical modules. Optical modules serve as vital components in optical communication networks by facilitating the conversion between optical signals and electrical signals—a crucial mode for data transmission. The current landscape heavily relies on immense computing power to support artificial intelligence and large-scale models; thus making optical communication networks fundamental to this computational prowess.
Consequently, there are instances where computing power necessitates leveraging optical modules. Thanks to rapid advancements in cloud computing, digital economy expansion, as well as East-West computation developments in recent years——the demand for optical modules has experienced a significant surge alongside its corresponding industry growth trajectory.