Invention Grant
- Patent Title: Data pipeline and access across multiple machine learned models
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Application No.: US17837806Application Date: 2022-06-10
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Publication No.: US11803335B2Publication Date: 2023-10-31
- Inventor: Arulkumaran Chandrasekaran , Brainerd Sathianathan
- Applicant: ITERATE STUDIO, INC.
- Applicant Address: US CO Highlands Ranch
- Assignee: ITERATE STUDIO, INC.
- Current Assignee: ITERATE STUDIO, INC.
- Current Assignee Address: US CO Highlands Ranch
- Agency: Dorsey & Whitney LLP
- Main IPC: G06F3/06
- IPC: G06F3/06 ; G06F8/51

Abstract:
The present disclosure describes systems and methods for storing incoming data and providing access to that data to multiple machine learned models in a data type-agnostic and programming language-agnostic manner. Operationally, a computing device may receive in coming data (e.g., from sensors, etc.). The computing device may store the incoming data in memory blocks, and index the memory blocks with a unique index (e.g., tag). The index may correspond to a determined tier for the memory blocks, and may enable the system to both locate the data once stored and enable the system to read (or use) the data upon receiving, for example, a data access request. In this way, systems and methods described herein provide for a robust data access and transfer mechanism that allows data to be stored a single time, but accessed by one or more different applications, machine learned models, and the like, simultaneously.
Public/Granted literature
- US20220398044A1 DATA PIPELINE AND ACCESS ACROSS MULTIPLE MACHINE LEARNED MODELS Public/Granted day:2022-12-15
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