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    SYSTEM AND METHOD FOR AUTOMATED CATALOGING AND BUILDING MACHINE LEARNING MODELS
    4.
    发明公开
    SYSTEM AND METHOD FOR AUTOMATED CATALOGING AND BUILDING MACHINE LEARNING MODELS 审中-公开

    公开(公告)号：US20230385653A1

    公开(公告)日：2023-11-30

    申请号：US17752203

    申请日：2022-05-24

    Applicant: AT&T Intellectual Property I, L.P.

    Inventor： Mukundan Sarukkai ,  Eshrat Huda

    IPC: G06N3/12 ,  G06N20/00

    CPC classification number: G06N3/123 ,  G06N20/00

    Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, including: selecting a first building block pattern function (bbDNA) having a first weight from a catalog, wherein the first bbDNA is based on a first mature pattern reaching a first bbDNA frequency threshold, wherein the first bbDNA is associated with at least one machine learning (ML) model of a plurality of ML models; selecting a second bbDNA having a second weight from the catalog, wherein the second bbDNA is associated with at least one ML model in the plurality of ML models; and creating a new ML model based on a combination of the first bbDNA and the second bbDNA. Other embodiments are disclosed.

    NUCLEIC ACID-BASED DATA STORAGE
    5.
    发明公开
    NUCLEIC ACID-BASED DATA STORAGE 审中-公开

    公开(公告)号：US20230376788A1

    公开(公告)日：2023-11-23

    申请号：US18230385

    申请日：2023-08-04

    Applicant: Catalog Technologies, Inc.

    Inventor： Nathaniel Roquet ,  Hyunjun Park ,  Swapnil P. Bhatia

    IPC: G06N3/123 ,  G06F5/08 ,  C12N9/22

    CPC classification number: G06N3/123 ,  G06F5/08 ,  C12N9/22 ,  C12N2310/20 ,  G16B20/00

    Abstract: Methods and systems for encoding digital information in nucleic acid (e.g., deoxyribonucleic acid) molecules without base-by-base synthesis, by encoding bit-value information in the presence or absence of unique nucleic acid sequences within a pool, comprising specifying each bit location in a bit-stream with a unique nucleic sequence and specifying the bit value at that location by the presence or absence of the corresponding unique nucleic acid sequence in the pool. But, more generally, specifying unique bytes in a bytestream by unique subsets of nucleic acid sequences. Also disclosed are methods for generating unique nucleic acid sequences without base-by-base synthesis using combinatorial genomic strategies (e.g., assembly of multiple nucleic acid sequences or enzymatic-based editing of nucleic acid sequences).

    Neural networks implemented with DSD circuits
    8.
    发明授权
    Neural networks implemented with DSD circuits 有权

    公开(公告)号：US11704575B2

    公开(公告)日：2023-07-18

    申请号：US16230928

    申请日：2018-12-21

    Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

    Inventor： Karin Strauss ,  Luis Ceze ,  Johannes Staffan Anders Linder

    IPC: G06N3/12 ,  G06N3/04 ,  G06N3/08 ,  G06N3/123

    CPC classification number: G06N3/123 ,  G06N3/04 ,  G06N3/08

    Abstract: Neural networks can be implemented with DNA strand displacement (DSD) circuits. The neural networks are designed and trained in silico taking into account the behavior of DSD circuits. Oligonucleotides comprising DSD circuits are synthesized and combined to form a neural network. In an implementation, the neural network may be a binary neural network in which the output from each neuron is a binary value and the weight of each neuron either maintains the incoming binary value or flips the binary value. Inputs to the neural network are one more oligonucleotides such as synthetic oligonucleotides containing digital data or natural oligonucleotides such as mRNA. Outputs from the neural networks may be oligonucleotides that are read by directly sequencing or oligonucleotides that generate signals such as by release of fluorescent reporters.

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