PATENT CLAIM ANALYSIS

Application Number: 16041497
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-04
Patent Classification: ["706", "025000"]

Abstract:
A device, system, and method is provided for storing a sparse neural network. A plurality of weights of the sparse neural network may be obtained. Each weight may represent a unique connection between a pair of a plurality of artificial neurons in different layers of a plurality of neuron layers. A minority of pairs of neurons in adjacent neuron layers are connected in the sparse neural network. Each of the plurality of weights of the sparse neural network may be stored with an association to a unique index. The unique index may uniquely identify a pair of artificial neurons that have a connection represented by the weight. Only non-zero weights may be stored that represent connections between pairs of neurons (and zero weights may not be stored that represent no connections between pairs of neurons).

Claim (Index 22):
The system of  claim 21 , wherein the one or more memories are configured to store a triplet of values identifying each weight comprising:\n a first value of the index identifying a first neuron of the pair in a first one of the different layers, a second value of the index identifying a second neuron of the pair in a second one of the different layers, and the value of the weight.

Metadata:
- Claim Count in Document: 77.0
- Percentile: 95.0
- Lexical Diversity: 2.39344
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['12158134', '14449101', '15055161', '14699778', '14513497']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3864022954862891
- 35 USC 102 Novelty (BERT): 0.5061167855057668
- Combined Prediction Score: 0.3983737444882369
- Mean Citation Score: 238.614632
- Max Citation Score: 249.7984
- Similarity Product: 150.9142137546539

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

Dataset: test