PATENT CLAIM ANALYSIS

Application Number: 16046337
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-04
Patent Classification: ["709", "203000"]

Abstract:
Data transformation caching in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: identifying, in dependence upon one or more machine learning models to be executed on the GPU servers, one or more transformations to apply to a dataset; generating, in dependence upon the one or more transformations, a transformed dataset; storing, within one or more of the storage systems, the transformed dataset; receiving a plurality of requests to transmit the transformed dataset to one or more of the GPU servers; and responsive to each request, transmitting, from the one or more storage systems to the one or more GPU servers without re-performing the one or more transformations on the dataset, the transformed dataset.

Claim (Index 17):
The apparatus of  claim 15  wherein transmitting, from the one or more storage systems to the one or more GPU servers without re-performing the one or more transformations on the dataset, the transformed dataset further comprises transmitting the transformed dataset from the one or more storage systems directly to application memory on the GPU servers.

Metadata:
- Claim Count in Document: 32.0
- Percentile: 95.0
- Lexical Diversity: 2.39344
- Patent Class: 709.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16040996', '16046102', '16040846', '16045814', '15883333']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3847423841888409
- 35 USC 102 Novelty (BERT): 0.5705583921104278
- Combined Prediction Score: 0.4033239849809996
- Mean Citation Score: 388.734246
- Max Citation Score: 437.28946
- Similarity Product: 421.3372145139908

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test