OpenAI Patent List

We researched OpenAI’s patents and curated them in an Airtable as a convenient reference. To our surprise, OpenAI only has nine active granted (B1 and B2) public patents and three A1 patents. 

When exploring patent documents, you will encounter various publication types that indicate the status and stage of the patent application process; here is a quick summary. 

A1: Pending application, published 18 months after the priority date. 

B1: Granted patent, not previously published as A1.

B2: Granted patent, previously published as A1.

It’s interesting to note how quickly OpenAI was granted these patents. OpenAI averaged 11 months from the application date to the grant date, which is impressive compared to the industry average of 24 months. 

Note: This list will remain updated as an easy-to-reference point for upcoming OpenAI patents from newest to oldest. 

Features Overview

• Patent Number: Unique identifier for the patent.
• Title: Title of the patent.
• Issue Date: Date the patent was issued.
• Inventors: Names of the inventors.
• Abstract: Brief summary of the patent.
• Link to Patent: URL to the full patent document (Google Patents)
• Potential Use Cases: Possible applications or uses of the patent.

Overview of Patents 

1. Systems And Methods For Interacting With A Large Language Model

Patent Number: US 12051205 B1
Application Date: 2023-09-27
Published Date: 2024-07-30
Inventors: Deutsch; Noah, Zweig; Benjamin
Link to Patent: US12051205B1

Abstract: 

Disclosed embodiments may include a method of interacting with a multimodal machine learning model; the method may include providing a graphical user interface associated with a multimodal machine learning model. The method may further include displaying an image to a user in the graphical user interface. The method may also include receiving a textual prompt from the user and then generating input data using the image and the textual prompt. The method may further include generating an output at least in part by applying the input data to the multimodal machine learning model, the multimodal machine learning model configured using prompt engineering to identify a location in the image conditioned on the image and the textual prompt, wherein the output includes a first location indication. The method may also include displaying, in the graphical user interface, an emphasis indicator at the indicated first location in the image.

2. System And Methods For Using Contrastive Pre-Training To Generate Text And Code Embeddings

Patent Number: US 20240249186 A1
Application Date: 2023-01-23
Published Date: 2024-07-25
Inventors: Neelakantan; Arvind, XU; Tao
Link to Patent: US20240249186A1

Abstract: 

Embodiments of the present disclosure may include systems, methods, and computer readable media for generating a vector representation, including receiving a training data set, the training data set including a plurality of paired data samples corresponding to positive example pairs, each positive example pair including a first data unit and a second data unit. Embodiments may also include converting the training data set into at least one first vector of a vector representation. Embodiments may further include accessing one or more negative example pairs to contrast against the positive example pairs. Embodiments may also include converting the one or more negative example pairs into one or more second vectors of the vector representation. Embodiments may further include training an artificial machine learning model to generate additional vectors of the vector representation. Further embodiments may include systems, methods, and media for determining semantic similarity based on one or more vector representations.

3. Systems And Methods For Interacting With A Multimodal Machine Learning Model

Patent Number: US 12039431 B1
Application Date: 2023-09-27
Published Date: 2024-07-16
Inventors: Deutsch; Noah, Turley; Nicholas, Zweig; Benjamin
Link to Patent: US12039431B1

Abstract: 

The disclosed embodiments may include a method of interacting with a multimodal machine learning model; the method may include providing a graphical user interface associated with a multimodal machine learning model. The method may further include displaying an image to a user in the graphical user interface. The method may also include receiving a textual prompt from the user and then generating input data using the image and the textual prompt. The method may further include generating an output at least in part by applying the input data to the multimodal machine learning model, the multimodal machine learning model configured using prompt engineering to identify a location in the image conditioned on the image and the textual prompt, wherein the output comprises a first location indication. The method may also include displaying, in the graphical user interface, an emphasis indicator at the indicated first location in the image.

4. Systems and methods for generating natural language using language models trained on computer code

Patent Number: US 20240020116 A1
Application Date: 2023-05-23
Published Date: 2024-06-11
Inventors: Chen; Mark, Tworek; Jerry, Sutskever; Illya, Zaremba; Wojciech, Jun; Heewoo, Ponde De Olivera Pinto; Henrique
Link to Patent: US20240020116A1

Abstract: 

Disclosed herein are methods, systems, and computer-readable media for generating natural language based on computer code input. In an embodiment, a method may comprise one or more of: accessing a docstring generation model configured to generate docstrings from computer code; receiving one or more computer code samples; generating, using the docstring generation model and based on the received one or more computer code samples, one or more candidate docstrings representing natural language text, each of the one or more candidate docstrings being associated with at least a portion of the one or more computer code samples; identifying at least one of the one or more candidate docstrings that provides an intent of the at least a portion of the one or more computer code samples; and/or outputting, via a user interface, the at least one identified docstring with the at least a portion of the one or more computer code samples.

5. Systems and methods for generating natural language using language models trained on computer code

Patent Number: US 12008341 B2
Application Date: 2023-05-23
Published Date: 2024-06-11
Inventors: Chen; Mark, Tworek; Jerry, Sutskever; Illya, Zaremba; Wojciech, Jun; Heewoo, Ponde De Olivera Pinto; Henrique
Link to Patent: US12008341B2

Abstract: 

Disclosed herein are methods, systems, and computer-readable media for generating natural language based on computer code input. In an embodiment, a method may comprise one or more of: accessing a docstring generation model configured to generate docstrings from computer code; receiving one or more computer code samples; generating, using the docstring generation model and based on the received one or more computer code samples, one or more candidate docstrings representing natural language text, each of the one or more candidate docstrings being associated with at least a portion of the one or more computer code samples; identifying at least one of the one or more candidate docstrings that provides an intent of the at least a portion of the one or more computer code samples; and/or outputting, via a user interface, the at least one identified docstring with the at least a portion of the one or more computer code samples.

6. Systems And Methods For Language Model-based Text Editing

Patent Number: US 11983488 B1
Application Date: 2023-03-14
Published Date: 2024-05-14
Inventors: Puri; Raul, Yuan; Qiming, Paino; Alexander, Tezak; Nikolas, Ryder; Nicholas
Link to Patent: US11983488B1

Abstract: 

Disclosed herein are methods, systems, and computer-readable media for automatically generating and editing text. In an embodiment, a method may include receiving an input text prompt and receiving one or more user instructions. The method may also include accessing a language model based on the input text prompt and the one or more user instructions. The method may also include outputting, using the accessed language model, language model output text. The method may also include editing the input text prompt based on the language model and the one or more user instructions by replacing at least a portion of the input text prompt with the language model output text.

7. Systems And Methods For Image Generation With Machine Learning Models

Patent Number: US11983806B1
Application Date: 2023-08-30
Published Date: 2024-05-14
Inventors: Ramesh; Aditya, Nichol; Alexander, Dhariwal; Prafulla
Link to Patent: US11983806B1

Abstract: 

Disclosed herein are methods, systems, and computer-readable media for regenerating a region of an image with a machine learning model based on a text input. Disclosed embodiments involve accessing a digital input image. Disclosed embodiments involve generating a masked image by removing a masked region from the input image. Disclosed embodiments involve accessing a text input corresponding to an image enhancement prompt. Disclosed embodiments include providing at least one of the input image, the masked region, or the text input to a machine learning model configured to generate an enhanced image. Disclosed embodiments involve generating, with the machine learning model, the enhanced image based on at least one of the input image, the masked region, or the text input.

8. Schema-based Integration Of External APIs With Natural Language Applications

Patent Number: US 11922144 B1
Application Date: 2023-03-20
Published Date: 2024-03-05
Inventors: Mishchenko; Andrey, Medina; David, McMillan; Paul, Eleti; Athyuttam
Link to Patent: US11922144B1

Abstract: 

Disclosed herein are methods, systems, and computer-readable media for integrating a particular external application programming interface (API) with a natural language model user interface. In one embodiment, a method includes receiving a first input at the natural language model user interface, determining the first input includes a request to integrate the particular external application programming interface (API) with the natural language model user interface, identifying the particular external API based on the received input, integrating the particular external API with the natural language model user interface, accessing the particular external API based on the first input or a second input at the natural language model user interface, and transmitting, based on the accessing, a response message to the natural language model user interface, the response message including a result of the accessing.

9. Systems And Methods For Hierarchical Text-conditional Image Generation

Patent Number: US 11922550 B1
Application Date: 2023-03-30
Published Date: 2024-03-05
Inventors: Ramesh; Aditya, Dhariwal; Prafulla, Nichol; Alexander, Chu; Casey, Chen; Mark
Link to Patent: US11922550B1

Abstract: 

Disclosed herein are methods, systems, and computer-readable media for generating an image corresponding to a text input. In an embodiment, operations may include accessing a text description and inputting the text description into a text encoder. The operations may include receiving, from the text encoder, a text embedding, and inputting at least one of the text description or the text embedding into a first sub-model configured to generate, based on at least one of the text description or the text embedding, a corresponding image embedding. The operations may include inputting at least one of the text description or the corresponding image embedding, generated by the first sub-model, into a second sub-model configured to generate, based on at least one of the text description or the corresponding image embedding, an output image. The operations may include making the output image, generated by the first second sub-model, accessible to a device.

10. Systems And Methods For Language Model-based Text Insertion

Patent Number: US 11886826 B1
Application Date: 2023-03-14
Published Date: 2024-01-30
Inventors: Bavarian; Mohammad, Jun; Heewoo
Link to Patent: US11886826B1

Abstract: 

Disclosed herein are methods, systems, and computer-readable media for automatically generating and inserting text. In an embodiment, a method may include receiving an input text prompt comprising a prefix portion and a suffix portion. The method may also include accessing a language model based on the input text prompt, and determining a set of context parameters based on the input text prompt and the language model. The method may also include generating an output text prompt based on the set of context parameters and the language model, and inserting the output text prompt into the input text prompt.

11. Using Machine Learning To Train And Use A Model To Perform Automatic Interface Actions Based On Video And Input Datasets

Patent Number: US 11887367 B1
Application Date: 2023-04-19
Published Date: 2024-01-30
Inventors: Baker; Bowen, Akkaya; Ilge, Zhokhov; Peter, Huizanga; Joost, Tang; Jie, Ecoffet; Adrien, Houghton; Brandon, Gonzalez; Raul Sampedro, Clune; Jeffrey
Link to Patent: US11887367B1

Abstract: 

Disclosed herein are methods, systems, and computer-readable media for training a machine learning model to label unlabeled data and/or perform automated actions. In an embodiment, a method comprises receiving unlabeled digital video data, generating pseudo-labels for the unlabeled digital video data, the generating comprising receiving labeled digital video data, training an inverse dynamics model (IDM) using the labeled digital video data, and generating at least one pseudo-label for the unlabeled digital video data, wherein the at least one pseudo-label is based on a prediction, generated by the IDM, of one or more actions that mimic at least one timestep of the unlabeled digital video data. In some embodiments, the method further comprises adding the at least one pseudo-label to the unlabeled digital video data and further training the IDM or a machine learning model using the pseudo-labeled digital video data.

12. Systems and methods for generating code using language models trained on computer code

Patent Number: US 20240020096 A1
Application Date: 2023-05-23
Published Date: Pending
Inventors: Chen; Mark, Tworek; Jerry, Sutskever; Illya, Zaremba; Wojciech, Jun; Heewoo, Ponde De Olivera Pinto; Henrique
Link to Patent: US 20240020096 A1

Abstract:

Disclosed herein are methods, systems, and computer-readable media for generating computer code based on natural language input. In an embodiment, a method may comprise one or more of: receiving a docstring representing natural language text specifying a digital programming result; generating, using a trained machine learning model, and based on the docstring, a computer code sample configured to produce respective candidate results; causing the computer code sample to be executed; identifying, based on the executing, a computer code sample configured to produce a particular candidate result associated with the digital programming result; performing at least one of outputting, via a user interface, the identified computer code sample, compiling the identified computer code sample, transmitting the identified computer code sample to a recipient device, storing the identified computer code sample, and/or re-executing the identified computer code sample.