PATENT CLAIM ANALYSIS

Application Number: 15971904
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2019-11
Patent Classification: ["708", "514000"]

Abstract:
A system for block floating point computation in a neural network receives a block floating point number comprising a mantissa portion. A bit-width of the block floating point number is reduced by decomposing the block floating point number into a plurality of numbers each having a mantissa portion with a bit-width that is smaller than a bit-width of the mantissa portion of the block floating point number. One or more dot product operations are performed separately on each of the plurality of numbers to obtain individual results, which are summed to generate a final dot product value. The final dot product value is used to implement the neural network. The reduced bit width computations allow higher precision mathematical operations to be performed on lower-precision processors with improved accuracy.

Claim (Index 8):
A computerized method for block floating point computation in a neural network, the computerized method comprising:\n receiving block floating point vectors comprising mantissas and exponents; decomposing each of the block floating point vectors into a plurality of block floating point vectors having reduced bit-width mantissas; scaling the block floating point vectors, wherein the scaling includes scaling the exponents based on the mantissas within the block floating point vectors having reduced bit-width mantissas; performing dot product operations on the plurality of block floating point vectors have reduced bit-width mantissas; and using a result of performing the dot product operations to implement the neural network.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 1.97059
- Patent Class: 708.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15592021', '10786332', '14106442', '12127898', '14295818']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4321876885335079
- 35 USC 102 Novelty (BERT): 0.5007335545456674
- Combined Prediction Score: 0.4390422751347239
- Mean Citation Score: 203.921026
- Max Citation Score: 222.03918
- Similarity Product: 150.44213422069072

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