Core Insights - Google has launched its next-generation large language model, Gemini 3, which is now integrated into key products such as Google Search, Gemini applications, API interfaces, and VertexAI, marking it as the company's "smartest model" to date [2] - The market's focus has shifted from model upgrades to the actual revenue generation and return on investment from these models, influenced by rapid iterations from competitors like OpenAI and Anthropic [2][5] Group 1: Gemini 3 Launch Strategy - Gemini 3 is deployed in Google Search on the same day of its release, unlike previous versions that took weeks to integrate, allowing AI-generated search results to cover billions of search queries immediately [4] - The consumer-facing generative search is more prominent, with Gemini 3 providing structured and visual responses, resembling interactive web pages rather than traditional link lists, potentially impacting websites reliant on traffic monetization [4] - Google emphasized the performance advantages of Gemini 3, showcasing its leading results in industry benchmarks and the ability to push updates to users more rapidly [4][5] Group 2: Gemini Agents and Enterprise Focus - Google introduced "Gemini Agents," a systematic AI assistant capable of executing multi-step tasks, such as organizing emails and planning travel itineraries, marking a significant step in creating a general-purpose assistant [7] - The company announced the "Antigravity" development platform for enterprise clients, allowing AI agents to perform coding tasks, which strengthens Google's position in the enterprise AI tools market [7] - The Gemini application interface has been revamped to focus on structured layouts and visual content, enhancing the ability to answer complex questions and increasing user engagement [7]