Large Language Models (LLMs)

Extract and summarize valuable information from complex documents, such as 10-K forms, research papers, third-party news services, and financial reports—with a click of a button. Watch how Enterprise Search uses natural language to understand semantic queries, offer summarized responses, and provide follow-up questions in the demo on the right.

The solution uses Vertex AI Agent Builder as its core component. With Vertex AI Agent Builder, even early career developers can rapidly build and deploy chatbots and search applications in minutes.

With Generative AI Document Summarization, deploy a one-click solution that helps detect text in raw files and automate document summaries. The solution establishes a pipeline that uses Cloud Vision Optical Character Recognition (OCR) to extract text from uploaded PDF documents in Cloud Storage, creates a summary from the extracted text with Vertex AI, and stores the searchable summary in a BigQuery database.

Powered by AI technologies such as natural language processing, generative AI, and text and speech recognition, Contact Center AI (CCAI) offers a Contact Center as a Service (CCaaS) solution that helps build a contact center from the ground up. It also has individual tools that target specific aspects of a call center, for example Dialogflow CX for building a LLM powered chatbot, Agent Assist for real-time assistance to human agents, and CCAI Insights for identifying call drivers and sentiment.

Cloud TPUs are Google’s warehouse scale supercomputers for machine learning. They are optimized for performance and scalability while minimizing the total cost of ownership and are ideally suited for training LLMs and generative AI models.

With the fastest training times on five MLPerf 2.0 benchmarks, Cloud TPU v4 pods are the latest generation of accelerators, forming the world's largest publicly available ML hub with up to 9 exaflops of peak aggregate performance.