租户标识:
行业趋势

SenseTime's AI R&D solutions aim at the business pain points of the great majority of AI R&D personnel, provide full-stack AI R&D services from underlying computing power resources to platform tool applications, and realize consulting empowerment based on SenseTime's rich practical experience in the industry to accelerate the digital transformation of enterprises.

Industry trends

The AI R&D process involves tedious tasks such as data processing, operator development, model optimization, and edge-end adaptation, and also faces a large and continuous consumption of computing power. How to help millions of AI practitioners in China to obtain flexible and elastic computing resources, accelerate the efficiency of algorithm iteration, improve the output of training and inference models, and accumulate data, models, and codes is the common goal that SenseTime and even many AI companies continue to focus on.

方案优势
方案架构

For the rapidly growing business computing power demand, provide flexibleGPU and CPU computing power services of various specifications.

For the network requirements in the model development process, provide high-performance network services with a transmission rate of up to 200Gb per second.

For the storage requirements in the model training process, provide storage services that are optimized for the model development process.

For full-link data management, provide rich dataset management functions, automatic annotation tools, and intelligent data labels.

For large-scale distributed training, provide a self-developed deep learning training framework to meet the needs of high-performance distributed parallel training.

For the deployment of heterogeneous back-end devices, provide a unified deployment framework with heterogeneous chips to simplify the deployment process.

For the visual monitoring of the development process, provide full-link visual development support for model training, deployment, and evaluation.

Solution Architecture
应用场景
提供丰富的实例类型,面向各类企业应用场景
  • 01Data Processing
  • 02Algorithm Development
  • 03Distributed Training
  • 04Model Deployment
Data Processing
Data Processing

The platform supports the parallel processing of large-scale data annotation tasks involving more than 1,000 people, meeting the needs of data management and sharing across departments and teams.

Algorithm Development
Algorithm Development

The platform has a built-in world-leading open source algorithm library, which supports the development of algorithms in multiple fields such as autonomous driving, smart city, and intelligent manufacturing.

Distributed Training
Distributed Training

The platform provides industry-leading distributed training support, which has heterogeneous computing power such as Nvidia and localization, provides flexible large-scale computing power scheduling strategies, and is deeply optimized for communication and computing of distributed tasks.

Model Deployment
Model Deployment

The platform provides a deployment framework that adapts to various devices such as ARM, X86, Nvidia, Huawei, and Cambricon, and generates a deployable SDK with one click to solve the “persistent problem” of deployment for developers.

核心应用/产品
  • Flexible Computing Power Resources of Various Specifications
    Flexible Computing Power Resources of Various Specifications

    Include mainstream and localizedGPUs, CPUs, and other computing power resources.

  • Sound SPE Cloud AI Cloud Services
    Sound SPE Cloud AI Cloud Services

    Include data services, training services, inference services, and other PaaS services required for AI R&D.

  • Comprehensive Data Security System
    Comprehensive Data Security System

    Include multi-faceted security services such as host machines, network layers, container layers, application layers, and data asset layers.

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