Google patents shared data tables to speed up machine learning
Google has filed a patent for a method that creates 'multiplexed' tables to store data used in machine learning. Instead of giving every piece of data its own unique slot, this system allows different data points to share the same storage space. This approach is designed to make the calculations involved in processing large amounts of data more efficient.
In the filing’s own words
Provided are systems and methods for generating embedding tables that significantly improve computational efficiency. In particular, one aspect of the present disclosure is directed to the use of a multiplexed embedding table that provides an effective solution for handling embeddings for high-dimensional feature data in machine learning systems. Specifically, the multiplexed embedding table allows multiple features to share a single representation space. For example, in the multiplexed embedding table, at least two values that are respectively associated with at least two different features can be mapped to a shared vector (e.g., row) in the multiplexed embedding table.
What exactly they claim (claim 1)
1. A computer-implemented method to generate embedding tables with improved computational efficiency, the method comprising: obtaining, by a computing system comprising one or more computing devices, a set of feature data that corresponds to one or more items, wherein the set of feature data comprises a plurality of values for each of a plurality of features; establishing, by the computing system, a multiplexed embedding table in which at least two of the values that are respectively associated with at least two different features of the plurality of features are mapped to a shared vector in the multiplexed embedding table; and storing, by the computing system, a plurality of embeddings associated with the plurality of values in the multiplexed embedding table.
Facts
- Company
- Google (Google LLC)
- Official title
- Multiplexed Embedding Tables for Improved Computational Efficiency
- Publication number
- US20260320018A1
- Application number
- 19485246
- Filed
- May 17, 2024
- Published
- Oct 15, 2026
- Inventors
- 7
- Claims
- 11
Classified under
G06F 16/2255 Physics & computingMore from Google 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.