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    Home » CLO » Big Model + Big Computing Power Convergence What Cloud Computing Can Do for AIGC
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    Big Model + Big Computing Power Convergence What Cloud Computing Can Do for AIGC

    AIGC, or AI Generated Content, Artificial Intelligence Generated Content, usually includes areas such as writing, painting, music, and video, and has a variety of functions such as text-generated text, text-generated graphics, and text-generated audio and video.
    Updated: Jul 18, 2025
    Big Model + Big Computing Power Convergence What Cloud Computing Can Do for AIGC

    AIGC, or AI Generated Content, Artificial Intelligence Generated Content, usually includes the fields of writing, painting, music, video, etc., and has various functions such as text-generated text, text-generated graphics, text-generated audio and video. After ChatGPT came out of nowhere, the AIGC industry quickly became the focus of the world.

         Outbreak of AIGC Industry

    However, behind the operation of such large models as ChatGPT, powerful arithmetic power is needed to support it. According to relevant information, OpenAI's GPT-3 reference number reaches 175 billion, and the volume of pre-training data reaches 45 TB. ChatGPT's daily user access corresponds to the initial investment cost of the arithmetic facility, which is estimated to be about 3-4 billion U.S. dollars. ChatGPT often goes down due to the surge in access, which all reflects the massive demand for arithmetic and other infrastructure in the AIGC industry.

         What the cloud can offer AIGC

    The AIGC industry needs to process large amounts of data and perform complex calculations, and cloud computing platforms can provide efficient and stable services. Cloud computing can provide computing resources, network connection, data storage and model management capabilities for building the arithmetic base of large models, solving the hosting, storage, deployment, and operation of large models, helping users to quickly create and deploy models and so on.

    Arithmetic power

    Large models have high requirements for arithmetic power when running, and need computing resources with strong and stable performance. The advantage of cloud platform is that it can provide unified scheduling and management of various heterogeneous computing resources, such as CPU, GPU, etc., based on general-purpose servers and proprietary hardware. through the virtualization management capability, it can deploy the underlying computing resources and run the models with one click, and make full use of the hardware acceleration capability of different heterogeneous resources to accelerate the operation and generation speed of the models. the computation demand of AIGC is usually uncertain, and may require some elasticity computing power to cope with peak demand. Cloud computing can provide the ability to allocate computing resources on-demand and scale when needed.

    Data storage

    Large models use and generate large amounts of data when running, requiring reliable data storage and backup mechanisms. The cloud platform's distributed storage, which supports multiple storage type protocols, can provide stable, reliable, open and compatible, elastic and scalable block, file and object storage services. Meanwhile, combined with data protection mechanisms such as multi-copy, multi-level fault domain, and fault self-recovery, it can ensure the safe and stable operation of models and data.

    Network

    The training and reasoning of AI models require large amounts of data transmission and storage, which requires high network performance for the underlying base. Cloud computing can provide network and storage of arithmetic resources, and forwarding through distributed network mechanisms, transmitting physical network performance, based on 25G, 40G network can significantly improve the efficiency and performance of model arithmetic.

    Security

    Cloud computing can guarantee the security of models and data at multiple levels. The cloud platform supports multi-tenant and VPC isolation network, combined with cloud firewalls, which can strictly carry out data isolation and access rights control; in terms of model hosting, the model warehouse implements a strict rights management mechanism; in terms of data storage, security and control are ensured through private deployment and data disk encryption; in the process of model distribution and operation, it also provides comprehensive account authentication and log auditing functions, which can guarantee the security of models and data in all aspects. model and data security.

    Model management

    Cloud vendors can provide unified hosting services and large model warehouses, and AI enterprise users can customize the uploading, downloading, permission control, distribution, deployment and operation of models. Provide a variety of model deployment modes, can be flexibly customized API release and one-click packaging application, convenient for users to manage AI models.

    Huge Market Potential

    AIGC is becoming the engine of digital content innovation. Looking ahead, the accelerated development of AIGC and the increased demand for arithmetic power, communication and storage will drive the development of cloud computing and other related industries.

    According to IDC, global AI IT investment will be $92.95 billion in 2021 and is expected to increase to $301.43 billion in 2026, a compound annual growth rate of about 26.5%. That's a pretty big market. According to the China Academy of Information and Communications Technology (AICT), the total global computing device arithmetic scale reached 615EFlops in 2021, including 369EFlops of basic arithmetic, 232EFlops of intelligent arithmetic, and 14EFlops of supercomputing arithmetic, and it is expected that the global arithmetic scale will reach 56ZFlps in 2030, with an average annual growth rate of 65%.

    Overall, cloud computing can provide high-performance infrastructure, efficient and secure AI model management and services for related enterprises and organizations in the AIGC industry, effectively protect data privacy and model security, and promote AI innovation.

    cloud computing ChatGPT AIGC
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