AI Development
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Substrate is an inference API designed specifically for multi-step AI programs. It allows users to connect nodes from a curated library that includes optimized machine learning models, built-in file and vector storage, a code interpreter, and logical control flow components. This setup enables the creation of complex AI workflows that run efficiently and quickly, thanks to the system's ability to maximize parallelism, throughput, and data locality. With Substrate, users can achieve perfect parallelism, opportunistic batching, zero roundtrips, and near-instant communication between nodes without needing to write complex code. This contrasts with traditional methods that often require multiple requests to various API providers, resulting in slower, more expensive, and less reliable operations due to unnecessary roundtrips and unoptimized program flows. Substrate simplifies the development of AI programs by allowing users to describe graphs in a natural, imperative manner. Nodes are automatically connected when their outputs and inputs are referenced, reducing the amount of code needed and eliminating the need for infrastructure management. The platform ensures that entire graphs of many nodes often run on a single machine with microsecond communication between tasks, leading to high-performance execution. Substrate's models are continuously optimized for performance using the latest techniques, making it a powerful tool for developers looking to build and run sophisticated AI programs efficiently.
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Optimized machine learning models
Built-in file and vector storage
Code interpreter and logical control flow
Perfect parallelism and zero roundtrips
Microsecond communication between nodes
Developers can create complex AI workflows with minimal code.
Achieve high performance with optimized data locality and parallelism.
Reduce infrastructure management and operational costs.
Enable near-instant communication between nodes for faster execution.
Simplify the integration of multiple AI models and components.
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