Machine learning engineering through hybrid knowledge representation

This invention describes a system that takes a detailed request for a machine learning task, including specifics about the data, model, and performance goals. It then searches a specialized database of machine learning components. If a suitable component is found, it's provided; otherwise, the system combines existing machine learning fragments to create a new component that fits the request.

Why it matters: Filed before large language models (LLMs) could parse complex specifications and generate code or model architectures. The core idea of interpreting a specification to find or build ML components is now significantly more feasible and powerful with current generative AI capabilities.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedComplex software system, AI/ML expertise, knowledge base

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