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公开(公告)号:US20230146689A1
公开(公告)日:2023-05-11
申请号:US18061884
申请日:2022-12-05
Applicant: Brown University
Inventor: Sherief REDA , Hokchhay TANN , Soheil HASHEMI , R. Iris BAHAR
Abstract: A hardware neural network system includes an input buffer for input neurons (Nbin), an output buffer for output neurons (Nbout), and a third buffer for synaptic weights (SB) connected to a Neural Functional Unit (NFU) and a control logic (CP) for performing synapses and neurons computations. The NFU pipelines a computation into stages, the stages including weight blocks (WB), an adder tree, and a non-linearity function.
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公开(公告)号:US20220012646A1
公开(公告)日:2022-01-13
申请号:US17378988
申请日:2021-07-19
Applicant: BROWN UNIVERSITY
Inventor: Brenda RUBENSTEIN , Jacob Karl ROSENSTEIN , Christopher ARCADIA , Shui Ling CHEN , Amanda Doris DOMBROSKI , Joseph D. GEISER , Eamonn KENNEDY , Eunsuk KIM , Kady M. OAKLEY , Sherief REDA , Christopher ROSE , Jason Kelby SELLO , Hokchhay TANN , Peter WEBER
IPC: G06N99/00
Abstract: The invention provides methods for computing with chemicals by encoding digital data into a plurality of chemicals to obtain a dataset; translating the dataset into a chemical form; reading the data set; querying the dataset by performing an operation to obtain a perceptron; and analyzing the perceptron for identifying chemical structure and/or concentration of at least one of the chemicals, thereby developing a chemical computational language. The invention demonstrates a workflow for representing abstract data in synthetic metabolomes. Also presented are several demonstrations of kilobyte-scale image data sets stored in synthetic metabolomes, recovered at >99% accuracy.
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公开(公告)号:US20230027270A1
公开(公告)日:2023-01-26
申请号:US17929279
申请日:2022-09-01
Applicant: Brown University
Inventor: Brenda RUBENSTEIN , Jacob Karl ROSENSTEIN , Christopher ARCADIA , Shui Ling CHEN , Amanda Doris DOMBROSKI , Joseph D. GEISER , Eamonn KENNEDY , Eunsuk KIM , Kady M. OAKLEY , Sherief REDA , Christopher ROSE , Jason Kelby SELLO , Hokchhay TANN , Peter WEBER , Dana Jo Biechele-Speziale , Selahaddin GUMUS
IPC: G06N99/00
Abstract: The invention provides methods for computing with chemicals by encoding digital data into a plurality of chemicals to obtain a dataset; translating the dataset into a chemical form; reading the data set; querying the dataset by performing an operation to obtain a perceptron; and analyzing the perceptron for identifying chemical structure and/or concentration of at least one of the chemicals, thereby developing a chemical computational language. The invention demonstrates a workflow for representing abstract data in synthetic metabolomes. Also presented are several demonstrations of kilobyte-scale image data sets stored in synthetic metabolomes, recovered at >99% accuracy.
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公开(公告)号:US20210166159A1
公开(公告)日:2021-06-03
申请号:US17253013
申请日:2019-06-20
Applicant: BROWN UNIVERSITY
Inventor: Brenda RUBENSTEIN , Jacob Karl ROSENSTEIN , Christopher ARCADIA , Shui Ling CHEN , Amanda Doris DOMBROSKI , Joseph D. GEISER , Eamonn KENNEDY , Eunsuk KIM , Kady M. OAKLEY , Sherief REDA , Christopher ROSE , Jason Kelby SELLO , Hokchhay TANN , Peter WEBER
IPC: G06N99/00
Abstract: The invention provides methods for computing with chemicals by encoding digital data into a plurality of chemicals to obtain a dataset; translating the dataset into a chemical form; reading the data set; querying the dataset by performing an operation to obtain a perceptron; and analyzing the perceptron for identifying chemical structure and/or concentration of at least one of the chemicals, thereby developing a chemical computational language. The invention demonstrates a workflow for representing abstract data in synthetic metabolomes. Also presented are several demonstrations of kilobyte-scale image data sets stored in synthetic metabolomes, recovered at >99% accuracy.
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