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.

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.

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.

Abstract: A system for providing artificial intelligence agents that automate software usage includes training servers configured to train agents during training, production servers configured to execute the trained agents during inference, a plurality of training datasets, and data flow logic. The data flow logic is configured to, provide, during the training, the agents and the plurality of training datasets to the training servers to cause the training servers to train the agents on the plurality of training datasets and thereby produce the trained agents, configure the production servers with the trained agents for use during the inference, provide, during the inference, prompts issued by clients to the production servers to cause the production servers to translate the prompts into agent calls to the trained agents that in turn cause the trained agents to generate outputs that are responsive to the prompts, and make the outputs available to the clients.

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.

Abstract: A system for image-text agentic interface automation is disclosed. A multimodal agent is configured to process arbitrary-length text sequences and arbitrary-resolution images. A newline insertion logic is configured to interleave a newline character between successive lines of image patches in a plurality of lines of image patches, wherein the newline character specifies an end of a line in an input image. 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 image patches interleaved with the newline character into a sequence of input image 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 image tokens into a decoder-only Transformer logic, wherein the linear projection of the single token stream bypasses any embedding lookup.