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Developers interested in a solution offering data and AI algorithms to support their AI applications
About IBM Distributed AI APIs
Distributed AI is a computing paradigm that bypasses the need to move vast amounts of data and provides the ability to analyze data at the source. Distributed AI APIs built by IBM Research is a set of RESTful web services with data and AI algorithms to support AI applications across hybrid cloud, distributed, and edge computing environments. Each Distributed AI API addresses the challenges in enabling AI in distributed and edge environments with APIs. The Distributed AI APIs do not focus on the basic requirements of creating and deploying AI pipelines, for example, model training and model serving. You would use your favorite open-source packages such as TensorFlow or PyTorch. Then, you can containerize your application, including the AI pipeline, and deploy these containers at the distributed locations. In many cases, it’s useful to use a container orchestrator such as Kubernetes or OpenShift operators to automate the deployment process.
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Extensive Model Library: 200+ pre-trained models for rapid prototyping and deployment
Developer-Friendly Integration: RESTful APIs and SDKs for seamless incorporation into your stack
Serverless Architecture: Focus on coding, not infrastructure management
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Rapid Time-to-Market: Leverage advanced AI without building from scratch
Scalability: From MVP to enterprise-grade solutions, AI/ML API grows with your business
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IBM
United States
developer.ibm.com/apis/catalog/edgeai--distributed-ai-apis/Introduction/
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