Nvidia patents method to store video data inside neural network settings
Nvidia describes a way to turn a sequence of data, such as video frames, into a set of numbers that define how a neural network behaves. Instead of saving the video file directly, the system trains the network to recreate the video from random noise and saves the network's settings as the data.
In the filing’s own words
Apparatuses, systems, and techniques to encode sequence data in one or more neural networks. In at least one embodiment, a video frame sequence is generated using a neural network to map noise frames to video frames.
What exactly they claim (claim 1)
1. One or more processors, comprising: circuitry to encode a data sequence, wherein to encode the data sequence, the circuitry at least: generates, using one or more neural networks, a noise sequence; generates, using the one or more neural networks, one or more mappings between noise elements in the noise sequence to elements of the data sequence; and stores the generated parameters of the one or more neural networks, wherein the generated parameters are usable as an encoding of the data sequence.
Facts
- Company
- Nvidia (NVIDIA Corporation)
- Official title
- PROCESSOR AND SYSTEM TO ENCODE SEQUENCE DATA IN NEURAL NETWORKS
- Publication number
- US20260320351A1
- Application number
- 19467351
- Filed
- Feb 2, 2026
- Published
- Oct 15, 2026
- Inventors
- 2
- Claims
- 1
Classified under
G06N 3/045 Physics & computingG06F 17/15 Physics & computingG06F 17/18 Physics & computingG06T 5/70 Physics & computingMore from Nvidia in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.