TOOL FOR DESIGNING ARTIFICIAL INTELLIGENCE SYSTEMS

• US 20190318262A1
• Filed: 04/11/2019
• Published: 10/17/2019
• Est. Priority Date: 04/11/2018
• Status: Active Application

• Current Assignee: Christine Meinders
• Original Assignee: Christine Meinders
• Inventors: Meinders, Christine
• Application Number:
  US16/382,016
• Publication Number:
  US 20190318262A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 30/27 using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

The present disclosure is directed towards artificial intelligence systems and methods for receiving and analyzing data. An exemplary method provides for receiving input, at an interface on a computing device. The input includes a dataset, an analysis for the dataset, and an output medium. The method then provides for selecting, based on the received input, at least one algorithm from a plurality of algorithms. The method then provides for processing, via the computing device, the received input with the at least one algorithm to yield an output. The output is provided at the interface on the computing device.

Claims

1. A method, comprising:

receiving input, at an interface on a computing device, wherein the input comprises a dataset, an analysis for the dataset, and an output medium;

selecting, based on the received input, at least one algorithm from a plurality of algorithms;

processing, via the computing device, the received input with the at least one algorithm to yield an output; and

providing the output at the interface on the computing device.

2. The method of claim 1, wherein selecting at least one algorithm further comprises:

determining whether the received input corresponds to requirements associated with each algorithm in the plurality of algorithms; and

selecting algorithms of the plurality of algorithms, based on determining that the received input corresponds to requirements associated with the selected algorithms.

3. The method of claim 1, wherein the input further comprises any of:

a format for the output, a supplementary dataset, a type of the dataset, and input consideration variables.

4. The method of claim 1, wherein the at least one algorithm comprises an artificial intelligence model selected from a plurality of artificial intelligence approaches, including:

an artificial narrow intelligence approach, a non-symbolic artificial intelligence approach, a symbolic artificial intelligence approach, a hybrid symbolic and non-symbolic artificial intelligence approach, and a statistical artificial intelligence approach.

5. The method of claim 1, wherein the at least one algorithm comprises a machine learning model selected from a plurality of machine learning models, including:

a decision tree, a Bayesian network, an artificial neural network, a support vector machine, a convolutional neural networks, and a capsule network.

6. The method of claim 5, wherein the machine learning model was trained on the received input.

7. The method of claim 5, wherein the machine learning model was trained, via the computing device, on a subset of a database of artificial intelligence systems, the subset comprising artificial intelligence systems with at least one of:

datasets comprising metadata corresponding to metadata of the received dataset, and the output medium.

8. The method of claim 1, wherein the output comprises:

an indication of whether the at least one algorithm successfully processed the received input.

9. The method of claim 1, further comprising:

determining, via the computing device, whether the output comprises at least one bias in a plurality of biases;

identifying a portion of the received input corresponding to the determined bias based on determining that the output comprises at least one bias; and

displaying the identified portion of the received input at the interface on the computing device.

10. The method of claim 9, further comprising:

removing the identified portion from the received input to yield updated input;

retrieving, via the computing device, supplementary input data in a database of artificial intelligence systems, wherein the supplementary input data corresponds to the identified portion of the received input and does not comprise the at least one bias; and

displaying the supplementary input data at the interface on the computing device.

11. The method of claim 10, further comprising:

receiving a request, via the interface on the computing device, to process a second selection of input data comprising the received input with the supplementary input data in place of the identified portion; and

processing, via the computing device, the second selection of input data with the at least one algorithm to yield a second output; and

displaying the second output at the interface on the computing device.

12. The method of claim 9, wherein identifying the portion of the received input corresponding to the determined bias further comprises:

processing metadata associated with each of the received input, wherein the metadata comprises identification of biases in the plurality of biases corresponding to each of the received input.

13. A method, comprising:

receiving input, at an interface on a computing device, wherein the input comprises a dataset, an analysis for the dataset, an output medium, and a processed output, the processed output comprising an artificial intelligence system based on the dataset, the analysis for the dataset, and the output medium;

determining, via the computing device, whether metadata associated with the received input comprises at least one bias in a plurality of biases;

identifying a portion of the received input corresponding to the at least one bias;

displaying, at the interface on the computing device, the identified portion and the at least one bias.

14. The method of claim 13, further comprising:

retrieving, via the computing device, supplementary input data from a database of artificial intelligence systems, wherein the supplementary input data corresponds to the identified portion of the received input and does not comprise the at least one bias; and

displaying the supplementary input data at the interface on the computing device.

15. The method of claim 14, further comprising:

receiving a request, via the interface for the computing device, to process a second selection of input data comprising the received input with the supplementary input data in place of the identified portion; and

processing, via the computing device, the second selection of input data to yield an output; and

displaying the output at the interface on the computing device.

16. A non-transitory computer-readable medium in which is embedded computer-readable code that when loaded on a computing device causes the computing device to perform the steps of:

receiving input, at an interface on the computing device, wherein the input comprises a dataset, an analysis for the dataset, and an output medium;

selecting, based on the received input, at least one algorithm from a plurality of algorithms;

processing, via the computing device, the received input with the at least one algorithm to yield an output; and

displaying the output at the interface on the computing device.

17. The non-transitory computer-readable medium of claim 16, further comprising:

determining, via the computing device, whether the output comprises at least one bias in a plurality of biases;

identifying a portion of the received input corresponding to the determined bias based on determining that the output comprises at least one bias; and

displaying the identified portion of the received input at the interface on the computing device.

18. The non-transitory computer-readable medium of claim 17, further comprising:

removing the identified portion from the received input to yield updated input;

retrieving, via the computing device, supplementary input data in a database of artificial intelligence systems, wherein the supplementary input data corresponds to the identified portion of the received input and does not comprise the at least one bias; and

displaying the supplementary input data at the interface on the computing device.

19. The non-transitory computer-readable medium of claim 18, further comprising:

receiving a request, via the interface on the computing device, to process a second selection of input data comprising the received input with the supplementary input data in place of the identified portion; and

processing, via the computing device, the second selection of input data with the at least one algorithm to yield a second output; and

displaying the second output at the interface on the computing device.

20. The non-transitory computer-readable medium of claim 17, wherein identifying the portion of the received input corresponding to the determined bias further comprises:

processing metadata associated with each of the received input, wherein the metadata comprises identification of biases in the plurality of biases corresponding to each of the received input.