Integrated AI development platform
The integrated AI development platform, with its powerful integration capabilities and efficient workflow, is leading a new era of intelligent application development. This platform not only deeply integrates key aspects such as data import, refined data processing, efficient model development, intelligent model training, rigorous model evaluation, and seamless service launch, but also greatly accelerates the incubation and landing of intelligent businesses by providing a one-stop and comprehensive machine learning and deep learning modeling process.
Comprehensive modeling process
Integrating functions such as data import, data processing, model development, model training, model evaluation, and service launch, we provide a one-stop and comprehensive machine learning and deep learning modeling process to quickly build intelligent businesses. Provide visual low code development tools, automated model generation, continuous training and deployment for machine learning and deep learning, lower the threshold for developers, help users quickly create and deploy models, and manage the entire AI workflow cycle.
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Automation of data import and processing: The platform supports diverse data source access, including but not limited to databases, cloud storage, real-time data streams, etc., to ensure the comprehensiveness and timeliness of data. The built-in advanced data cleaning, conversion, normalization and other tools can automatically handle data quality issues, improve data quality, and lay a solid foundation for subsequent modeling.
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Intelligentization of model development and training: The platform is equipped with visual low code development tools, allowing even non professional AI developers to easily build complex machine learning or deep learning models by dragging and dropping components and configuring parameters. At the same time, the platform supports automated model generation, utilizing advanced algorithm libraries and strategies to quickly generate high-quality candidate models. During the model training phase, the platform can intelligently allocate computing resources, support distributed training, and significantly improve training speed and efficiency.
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Model evaluation and optimization: Through built-in evaluation metrics and visual analysis tools, users can intuitively understand the performance of the model, such as accuracy, recall, F1 score, etc. The platform also provides model tuning suggestions to help users further optimize model parameters and improve model performance.
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Service launch and continuous management: Once the model passes the evaluation, it can be deployed to the production environment with just one click through the platform. The Moirae service hosting feature supports flexible deployment strategies, whether it is single point deployment or distributed deployment across multiple nodes, it can meet different business needs. At the same time, the platform also provides full lifecycle management capabilities such as model monitoring, performance tuning, and version control to ensure the stable operation and continuous optimization of models in production environments.
Distributed model training and service hosting
Metis provides globally distributed computing power and supports various chip architectures such as GPU and FPGA in AI computing, forming a heterogeneous AI computing platform. AI developers can directly submit computing tasks such as data preprocessing, feature engineering, and model training at low cost, and computing resources can be automatically scheduled as needed.
- Distributed model training and global computing power scheduling: Metis serves as the computing power support for the platform, building a globally distributed heterogeneous AI computing platform. This platform integrates various high-performance computing chips such as GPU and FPGA, providing unprecedented computing power support for AI developers. Developers can submit computing tasks at low cost according to task requirements and enjoy the convenience of on-demand automatic scheduling of computing resources. This flexible and efficient computing power scheduling mechanism provides strong support for large-scale and complex AI model training.
Moirae provides service hosting capabilities, and successfully trained models can be deployed directly on the network. The model can be deployed to a single network node, or deployed in multiple network nodes through sharding. Multiple nodes make predictions through secure multi-party computation protocols.
- Secure multiparty computation protocol ensures privacy: During the model deployment phase, Moirae uses secure multiparty computation protocol to ensure strict protection of data privacy when the model makes predictions between multiple network nodes. The application of this innovative technology not only enhances the flexibility of model deployment, but also strengthens users’ confidence in data security.