Adaptive Data Loader for Bridging Legacy Data Sources and Artificial Intelligence Model Training
Summary
USPTO published patent application US20260099766A1 titled 'Adaptive Data Loader for Bridging Legacy Data Sources and Artificial Intelligence Model Training.' The application discloses a process for identifying legacy data sources, adapting data loaders to process data into a training format, and training AI models using the processed batches. Application No. 19064832 was filed on February 27, 2025.
What changed
USPTO published patent application US20260099766A1 for an Adaptive Data Loader designed to bridge legacy data sources with AI model training systems. The application discloses methods for identifying multiple legacy data sources with unique formats, selecting compatible data loaders for each source, processing data into a standardized training format, and using the processed batches to train artificial intelligence models.
For affected parties, this publication serves as prior art notice and provides public disclosure of the technical approach to integrating legacy systems with modern AI training pipelines. Inventors Jeffrey Daniel Esposito, Aishwarya Dharani Arul, and Henry Svendsgaard are named on the application. No compliance obligations or regulatory deadlines are imposed by this publication.
What to do next
- Monitor for updates
Archived snapshot
Apr 13, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
ADAPTIVE DATA LOADER FOR BRIDGING LEGACY DATA SOURCES AND ARTIFICIAL INTELLIGENCE MODEL TRAINING
Application US20260099766A1 Kind: A1 Apr 09, 2026
Inventors
Jeffrey Daniel Esposito, Aishwarya Dharani Arul, Henry Svendsgaard
Abstract
A process includes identifying a plurality of legacy data sources, wherein each legacy data source has a unique legacy data format, and identifying, for each of the legacy data sources, a data loader that is adapted to process data from the legacy data source to form training data having a training data format that is different than the legacy data format. The process further includes causing, for each of the legacy data sources, the identified data loader to process at least a portion of the data from the legacy data source to form a batch of training data having the training data format. Still further, the operations comprise training an artificial intelligence model using the batches of training data formed from each of the legacy data sources.
CPC Classifications
G06N 20/00
Filing Date
2025-02-27
Application No.
19064832
Related changes
Get daily alerts for USPTO Patent Applications - AI & Computing (G06N)
Daily digest delivered to your inbox.
Free. Unsubscribe anytime.
Source
About this page
Every important government, regulator, and court update from around the world. One place. Real-time. Free. Our mission
Source document text, dates, docket IDs, and authority are extracted directly from USPTO.
The summary, classification, recommended actions, deadlines, and penalty information are AI-generated from the original text and may contain errors. Always verify against the source document.
Classification
Who this affects
Taxonomy
Browse Categories
Get alerts for this source
We'll email you when USPTO Patent Applications - AI & Computing (G06N) publishes new changes.
Subscribed!
Optional. Filters your digest to exactly the updates that matter to you.