Mulai 29 April 2025, model Gemini 1.5 Pro dan Gemini 1.5 Flash tidak tersedia di project yang belum pernah menggunakan model ini, termasuk project baru. Untuk mengetahui detailnya, lihat Versi dan siklus proses model.
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Simpan dan kategorikan konten berdasarkan preferensi Anda.
Dalam AI generatif, grounding adalah kemampuan untuk menghubungkan output model dengan sumber informasi yang dapat diverifikasi. Saat Anda memberi model akses ke sumber data tertentu, grounding akan menghubungkan outputnya ke data ini dan mengurangi peluang model membuat konten. Hal ini sangat penting dalam situasi yang memerlukan akurasi dan keandalan yang signifikan.
Grounding ini memberikan manfaat berikut:
Mengurangi halusinasi model: Perujukan membantu mencegah kejadian saat model menghasilkan konten yang tidak faktual.
Menghubungkan respons model: Membantu memastikan bahwa respons model didasarkan pada sumber data spesifik Anda.
Meningkatkan auditabilitas: Perujukan menyediakan link ke sumber yang digunakan, sehingga memungkinkan verifikasi.
Anda dapat mendasarkan output model yang didukung di Vertex AI dengan cara berikut:
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-08-25 UTC."],[],[],null,["# Grounding overview\n\n| To see an example of grounding,\n| run the \"Intro to grounding\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/generative-ai/blob/main/gemini/grounding/intro-grounding-gemini.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fgenerative-ai%2Fmain%2Fgemini%2Fgrounding%2Fintro-grounding-gemini.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fgenerative-ai%2Fmain%2Fgemini%2Fgrounding%2Fintro-grounding-gemini.ipynb)\n|\n|\n| \\|\n|\n[View on GitHub](https://github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/grounding/intro-grounding-gemini.ipynb) \n\nIn generative AI, grounding is the ability to connect model output to verifiable\nsources of information. If you provide models with access to specific data\nsources, then grounding tethers their output to these data and reduces the\nchances of inventing content. This is particularly important in situations where\naccuracy and reliability are significant.\n\nGrounding provides the following benefits:\n\n- Reduces model hallucinations, which are instances where the model generates content that isn't factual.\n- Anchors model responses to your data sources.\n- Provides auditability by providing grounding support, which are links to sources.\n\nYou can ground supported-model output in Vertex AI in the following ways:\n\nFor language support, see\n[Supported languages for prompts](/gemini/docs/codeassist/supported-languages#supported_languages_for_prompts).\n\nWhat's next\n-----------\n\n- To learn more about responsible AI best practices and Vertex AI's safety filters, see [Responsible AI](/vertex-ai/generative-ai/docs/learn/responsible-ai).\n- To ground with your Google Search API, see [Grounding with\n Google Search\n API](/vertex-ai/generative-ai/docs/grounding/grounding-with-google-search-api)."]]
