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Driven by technologies and applications, enterprises‘ digital intelligence transformation has undergone three changes: high-density terminals, always-assured applications, and intelligent O&M. These changes have driven campus networks from the connectivity-centric era to the experience-centric era.

▪ Terminal access: The terminal access mode is changed from wired to wireless, freeing users and terminals from wired connections and allowing them to move freely on demand.

▪ Application assurance: As users pursue application experience, ensuring that applications are distortion-free becomes a basic requirement for improving user experience.

▪ Intelligent O&M: Big data analysis and artificial intelligence are used to implement intelligent O&M, which significantly improves O&M efficiency, quality, and reliability and provides better O&M experience for enterprises.

Huawei's high-quality 10 Gbps campus network solution: experience-centric, improving campus network experience in terms of wireless, application, and O&M.

Huawei's high-quality 10 Gbps campus network solution can be widely used in large- and medium-sized campus scenarios, such as government, education, and healthcare. It helps customers build leading digital infrastructure and facilitate digital transformation of enterprises.

As digital transformation sweeps across all industries, enterprises are presented with new opportunities for revenue growth. However, with these opportunities come challenges, such as difficulties in ensuring user experience, a lack of operational tools, and complex management in operations. These issues can hinder the digital transformation of enterprise campuses.

Huawei is leading the industry by introducing the concept of the campus network digital map. This map serves as the digital foundation of the campus network, creating a four-dimensional digital space that helps deliver ultimate user experience. The campus network digital map enables comprehensive digitalization of campus networks and empowers enterprises to capitalize on the opportunities it presents.

Huawei’s Medical Technology Digitalization Solution is designed to optimize healthcare processes across the board, improving efficiency through state-of-the-art digital technologies. It comprehensively covers a range of medical domains, including digital pathology, medical imaging, laboratory automation, and telemedicine, helping to build the future of healthcare.

In digital pathology and medical imaging, for example, scale-out storage, intelligent interaction advancements, and videoconferencing platforms — calling on Artificial Intelligence (AI), image recognition, and more — combine to improve the speed and accuracy of diagnosis, with improved image quality and heightened data security.

Indeed, the digitalization of medical technology in general promotes innovation in diagnosis and treatment, improving the quality and efficiency of healthcare services, with renewed focus on the most important thing of all: the people they’re designed to help. This solution is a powerful demonstration of the potential of digital technology in modern healthcare.

Large AI model parameters have grown exponentially in scale, from the hundreds of billions to trillions. Training sets have also evolved from unimodal to multi-modal (images, videos, etc.) paradigms, resulting in a data explosion that has increased volumes by thousands, and brought unprecedented challenges.
First, poor loading performance among massive numbers of small files has undermined training efficiency.
Second, large model parameters are frequently being optimized, which has led to unstable training platforms, with service interruptions occurring every two days on average, and frequent, time-consuming read and write of TB-level checkpoints.
Third, training 100-billion-parameter models requires massive GPU resources, since individual GPUs are not efficient enough, and ensuring millisecond-level real-time inference for conversational applications is quite challenging.

OceanStor A800 delivers a staggering 24 million IOPS and 500 GB/s bandwidth within a single controller enclosure, serving as the high-performance AI knowledge repository storage solution. With four times the performance of the next runner-up, a single storage system is all you need for small file loading of training sets and high-bandwidth-based resumable training. You'll also benefit from access to a leading intrinsic vector knowledge repository, which supports large model inference applications with over 250,000+ QPS, achieving accelerated vector retrieval and millisecond-level inference response.