Batch processing in a neural network processor
US-2016342890-A1 · Nov 24, 2016 · US
Methods of chemical computation
US2022012646A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2022012646-A1 |
| Application number | US-202117378988-A |
| Country | US |
| Kind code | A1 |
| Filing date | Jul 19, 2021 |
| Priority date | Jun 20, 2018 |
| Publication date | Jan 13, 2022 |
| Grant date | — |
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Abstract
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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.
First claim
Opening claim text (preview).
We claim: 1 . An information storage system, comprising a solid surface with plurality of addressable locations, wherein each addressable location comprises a mixture of small molecules, and each mixture contains one set of small molecules per addressable location. 2 . The information storage system of claim 1 , wherein the small molecules are metabolomic elements. 3 . The information storage system of claim 1 , wherein the solid surface is a MALDI plate. 4 . The information storage system of claim 1 , wherein the addressable locations comprise at least 1024 independent mixture spots. 5 . The information storage system of claim 1 , wherein the addressable locations comprise thousands of spatially arrayed nanoliter spots. 6 . The information storage system of claim 1 , wherein the storage system comprises more than 100 kbits of data. 7 . The information storage system of claim 1 , wherein the storage system comprises a gigabyte of data.
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Activation functions · CPC title
Supervised learning · CPC title
Feedforward networks · CPC title
- G06N3/06Primary
Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons · CPC title
Learning methods · CPC title
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- What does patent US2022012646A1 cover?
- 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, th…
- Who is the assignee on this patent?
- Univ Brown
- What technology area does this patent fall under?
- Primary CPC classification G06N3/06. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Thu Jan 13 2022 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).