Building a frontier AI search experience

Full Title

Building a frontier AI search experience

Summary

Google Search is evolving into a frontier AI product, powered by Gemini models, to enhance information retrieval and task execution for billions of users. This transformation aims to make search more intuitive and efficient, enabling natural language queries and complex task completion.

Key Points

• Google Search is undergoing a significant transition to become a leading AI product, utilizing advanced Gemini models at a massive scale to serve 1.5 billion users monthly, fundamentally changing how people seek information. This evolution facilitates more natural and conversational interactions beyond traditional keyword searches.
• AI Mode introduces a frontier search experience where users can ask complex, natural language questions, enabling the AI model to "think" and "plan" by generating multiple internal Google Search queries (query fan-out) to gather comprehensive information and provide detailed, helpful responses, significantly reducing user research time.
• Multimodal search capabilities, including visual search via Google Lens and voice interaction, are rapidly growing, particularly among younger users, allowing for natural queries about physical objects or on-screen content and driving significant user engagement. This expands how users can bring context into their search queries.
• Personalization is a key future direction, allowing Google Search to leverage a user's personal context, with their permission (e.g., from Gmail or past activity), to provide uniquely relevant and efficient results. This aims to create a more tailored and less repetitive search experience by understanding individual preferences and history.
• Google Search is moving towards agentic functionalities, exemplified by initiatives like Project Mariner, where AI models can perform multi-step tasks on behalf of the user, such as planning trips or finding and booking specific event tickets. This seeks to automate complex processes, saving users considerable time and effort beyond simple information retrieval.

Conclusion

The integration of AI into Google Search is fundamentally aimed at increasing human productivity, efficiency, and access to information by simplifying complex queries and automating tasks.

The future roadmap for Search includes continuous expansion of multimodal capabilities (like video input), richer visual experiences, deeper personalization through user context, and advanced agentic features.

This comprehensive transformation is a collaborative effort across Google's various teams, including Search, DeepMind, and infrastructure teams, to deliver state-of-the-art AI experiences at scale.

Discussion Topics

• How do you anticipate AI's integration into search will change your personal habits for finding information or completing tasks online?
• What are your thoughts on AI models performing "deep research" and generating "query fan-outs" to answer complex questions? Does this enhance trust or raise concerns?
• As Google Search becomes more personalized and agentic, what ethical considerations or privacy aspects do you think are most important for companies to address?

Key Terms

Frontier AI product

An AI product operating at the leading edge of AI capabilities, often implying the use of the most advanced large language models.

Gemini

Google's family of powerful, multimodal large language models designed to be highly capable in various tasks.

AI Overview

A feature in Google Search that provides AI-generated summaries or direct answers to queries, often appearing at the top of search results.

AI Mode

A specific frontier search experience in Google Search that allows for more natural, complex questions and leverages AI to perform deeper research.

Multimodal experiences

AI capabilities that allow interaction and processing of information across multiple data types, such as text, images, audio, and video.

Query fan-out

A process where an AI model, given a complex user query, generates multiple underlying, more specific search queries to gather comprehensive information from various sources.

Agentic AI

AI systems capable of understanding goals, planning steps, and executing actions to achieve those goals, often by interacting with external tools or systems on a user's behalf.

Project Mariner

An initiative mentioned in the podcast focused on building agentic functionalities within Google's AI ecosystem, likely for task automation.

Timeline