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The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Patent No.:

US 12619815 B1

PDFFull Text
Date of Patent:
May. 05, 2026

Filed:

Oct. 08, 2024

Magnitude invariant multimodal agent for efficient image-text interface automation

Applicant:

Anthropic, Pbc, San Francisco, CA (US);

Inventors:

Curtis Hawthorne, San Francisco, CA (US);

Erich Elsen, San Francisco, CA (US);

Augustus Odena, San Francisco, CA (US);

Maxwell Nye, San Francisco, CA (US);

Arushi Somani, San Francisco, CA (US);

Kyle Vigen, San Francisco, CA (US);

Rohan Bavishi, San Francisco, CA (US);

Sagnak Tasirlar, San Francisco, CA (US);

Warut Vijitbenjaronk, San Francisco, CA (US);

Ulas Kirazci, San Francisco, CA (US);

Joe Gershenson, San Francisco, CA (US);

Shaya Zarkesh, San Francisco, CA (US);

Assignee:

Anthropic, PBC, San Francisco, CA (US);

Attorney:

Haynes and Boone, LLP

Primary Examiner:

Miranda M Huang

Assistant Examiner:

Sidney Vincent Bostwick

Int. Cl.
CPC ...
G06F 40/166 (2020.01); G06F 3/0481 (2022.01); G06F 3/0484 (2022.01); G06F 9/451 (2018.01); G06F 16/951 (2019.01); G06F 40/174 (2020.01); G06F 40/284 (2020.01); G06N 3/0455 (2023.01); G06N 3/091 (2023.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/40 (2022.01); G06V 30/19 (2022.01); G06V 30/41 (2022.01);
U.S. Cl.
CPC ...
G06F 40/166 (2020.01); G06F 3/0481 (2013.01); G06F 3/0484 (2013.01); G06F 16/951 (2019.01); G06F 40/174 (2020.01); G06F 40/284 (2020.01); G06N 3/0455 (2023.01); G06N 3/091 (2023.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 10/803 (2022.01); G06V 10/82 (2022.01); G06V 20/40 (2022.01); G06V 30/19147 (2022.01); G06V 30/41 (2022.01); G06F 9/451 (2018.02);
Abstract

A system for magnitude-invariant image-text agentic interface automation is disclosed. A bit vectorization logic is configured to convert image patches in a plurality of image patches into magnitude-invariant bit vectors, and generate a plurality of lines of magnitude-invariant bit vectors. A tokenization logic is configured to translate the input text sequence into a sequence of input text tokens, and to translate the successive lines of magnitude-invariant bit vectors interleaved with a newline character into a sequence of input magnitude-invariant bit vector tokens. A linear projection logic is configured to linearly project a single token stream of the sequence of input text tokens and the sequence of input magnitude-invariant bit vector tokens into a decoder-only Transformer logic, wherein the linear projection of the single token stream bypasses any embedding lookup.

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