Machine learning (ml) infrastructure techniques

This invention describes a software system that helps data scientists build machine learning applications more easily. It works by taking inputs like where the data is, what problem needs solving, and what performance is expected. The system then uses a library of pre-built components to assemble, test, and even customize the machine learning application for different computer hardware.

Why it matters: Filed just as large language models (LLMs) were becoming widely capable. LLMs could now significantly enhance the system's ability to interpret user-defined problems and requirements, and then orchestrate the selection and generation of ML components.

Status: Not in forceListed as no longer active.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, ML, cloud infrastructure expertise.

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