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Generative AI (also known as GenAI or gen AI) is a field of
artificial intelligence (AI) that focuses on creating new content, such as
images, text, audio, and code. Unlike other AI systems designed to recognize
patterns and make predictions, generative AI models learn from input training
data and generate new data with similar characteristics.
Generative AI models are large enough to introduce the ability to understand and
generate natural language. Depending on the data the models are trained on,
these models can understand and generate content from multiple modalities,
including text and images. Models that work with multiple modalities of data are
called multimodal models.
Vertex AI on Google Distributed Cloud (GDC) air-gapped offers
various foundational Generative AI
models from Google for use
in your distributed workloads and applications without the need for connectivity
to Google Cloud.
Applications of Generative AI
Generative AI on GDC has a wide range of potential
applications across various industries, including the following:
Multimodal information understanding: Generate written content from text,
code, images, audio, and video inputs for a wide range of tasks such as text
classification, image captioning, video summarization, and audio
transcription.
Long-context understanding: Comprehend large amounts of text with a
context window of up to 32,000 tokens for tasks such as processing long
documents, thousands of lines of code, and hours of audio or video.
Multilingual support: Understand more than 100 languages to enable the
global community to prompt and receive responses.
Optimized inferencing performance: Meet the latency and scale demands of
enterprise-scale AI applications.
Secure and compliant data handling: Use APIs fully on premises to meet the
most stringent regulatory requirements.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[],[],null,["# Generative AI overview\n\n| **Important:** This content applies to version 1.14.4 and later.\n\nGenerative AI (also known as *GenAI* or *gen AI*) is a field of\nartificial intelligence (AI) that focuses on creating new content, such as\nimages, text, audio, and code. Unlike other AI systems designed to recognize\npatterns and make predictions, generative AI models learn from input training\ndata and generate new data with similar characteristics.\n\nGenerative AI models are large enough to introduce the ability to understand and\ngenerate natural language. Depending on the data the models are trained on,\nthese models can understand and generate content from multiple modalities,\nincluding text and images. Models that work with multiple modalities of data are\ncalled *multimodal* models.\n\nVertex AI on Google Distributed Cloud (GDC) air-gapped offers\n[various foundational Generative AI\nmodels](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/genai/genai-models) from Google for use\nin your distributed workloads and applications without the need for connectivity\nto Google Cloud.\n\nApplications of Generative AI\n-----------------------------\n\nGenerative AI on GDC has a wide range of potential\napplications across various industries, including the following:\n\n- **Multimodal information understanding**: Generate written content from text, code, images, audio, and video inputs for a wide range of tasks such as text classification, image captioning, video summarization, and audio transcription.\n- **Long-context understanding**: Comprehend large amounts of text with a context window of up to 32,000 tokens for tasks such as processing long documents, thousands of lines of code, and hours of audio or video.\n- **Multilingual support**: Understand more than 100 languages to enable the global community to prompt and receive responses.\n- **Optimized inferencing performance**: Meet the latency and scale demands of enterprise-scale AI applications.\n- **Secure and compliant data handling**: Use APIs fully on premises to meet the most stringent regulatory requirements."]]
