MCP UI extends the Model Context Protocol to enable AI agents to return fully interactive UI components, solving the challenge of delivering commerce experiences that require visual and interactive elements like product selectors and cart flows. It uses an intent-based messaging system to maintain agent control.
A list of patents assigned to Quixey, Inc. including inventions related to application search, deep linking, application functionality access, and user intent identification.
A deep dive into the unseen systems behind Google Search – uncovering live experiments, entity-based infrastructure, AI agents, and more. The article details findings from a research project into Google's internal workings, including a list of nearly 1,200 experiments, the importance of entities and the Knowledge Graph, the development of AI agents, and how Google profiles users.
Here's a summary of the most interesting facts from the Search Engine Land article, presented as bullet points:
* **Extensive Experimentation:** Google is running approximately 1,200 experiments within its search system, with over 800 currently active as of June 2025. This highlights a continuous, iterative approach to search improvement.
* **Key Systems Still Active:** Systems previously revealed in leaks (Mustang, Twiddlers, QRewrite, Tangram, QUS) remain central to Google Search.
* **AI Agent Focus:** Google is developing a "constellation" of over 90 specialized AI agents (e.g., MedExplainer, Travel Agent) rather than a single all-purpose assistant, all under the "Project Magi" umbrella.
* **Knowledge Graph as Central Nervous System:** The Knowledge Graph isn’t just a side panel feature; it’s the core infrastructure powering many Google services, with a focus on data verification using a layered namespace hierarchy (kc, ss, hw).
* **Ghost Entities:** Google utilizes "ghost entities" – temporary, unanchored entities – to react quickly to emerging events and trends.
* **User Embedding (Nephesh):** Google creates mathematical embeddings representing user preferences and behaviors across all its products, influencing personalization.
* **Real-time Query Scoring:** Google employs a complex real-time scoring system for query terms, factoring in various elements like term placement and entity recognition.
* **Specialized Embeddings:** Beyond the main Knowledge Graph, Google uses specialized embeddings for verticals (shopping, travel) and temporal data.
* **AI Mode UI Changes:** Google is experimenting with integrating AI Mode into various UI elements, including the search bar and "I'm Feeling Lucky" button.
* **Focus on Entity Validation:** The article emphasizes the importance of brands establishing themselves as validated entities within Google’s Knowledge Graph for improved visibility.
Guide
Here's a summary of the most interesting facts from the Search Engine Land article, presented as bullet points:
* **Extensive Experimentation:** Google is running approximately 1,200 experiments within its search system, with over 800 currently active as of June 2025. This highlights a continuous, iterative approach to search improvement.
* **Key Systems Still Active:** Systems previously revealed in leaks (Mustang, Twiddlers, QRewrite, Tangram, QUS) remain central to Google Search.
* **AI Agent Focus:** Google is developing a "constellation" of over 90 specialized AI agents (e.g., MedExplainer, Travel Agent) rather than a single all-purpose assistant, all under the "Project Magi" umbrella.
* **Knowledge Graph as Central Nervous System:** The Knowledge Graph isn’t just a side panel feature; it’s the core infrastructure powering many Google services, with a focus on data verification using a layered namespace hierarchy (kc, ss, hw).
* **Ghost Entities:** Google utilizes "ghost entities" – temporary, unanchored entities – to react quickly to emerging events and trends.
* **User Embedding (Nephesh):** Google creates mathematical embeddings representing user preferences and behaviors across all its products, influencing personalization.
* **Real-time Query Scoring:** Google employs a complex real-time scoring system for query terms, factoring in various elements like term placement and entity recognition.
* **Specialized Embeddings:** Beyond the main Knowledge Graph, Google uses specialized embeddings for verticals (shopping, travel) and temporal data.
* **AI Mode UI Changes:** Google is experimenting with integrating AI Mode into various UI elements, including the search bar and "I'm Feeling Lucky" button.
* **Focus on Entity Validation:** The article emphasizes the importance of brands establishing themselves as validated entities within Google’s Knowledge Graph for improved visibility.
Guide
Katanemo Labs introduces Arch-Router, a 1.5B parameter model that intelligently maps user queries to the most suitable LLM, achieving 93% accuracy without the need for costly retraining. It uses a preference-aligned routing framework based on a Domain-Action Taxonomy, allowing for flexible adaptation to evolving models and use cases.
This paper introduces Arch-Router, a preference-aligned routing framework for large language models (LLMs). It addresses limitations in existing routing approaches by focusing on matching queries to user-defined preferences (domain and action types) rather than solely relying on benchmark performance. The framework includes a 1.5B parameter model, Arch-Router, and a data creation pipeline. Experiments demonstrate state-of-the-art results in matching queries with human preferences and improved adaptability.
This paper proposes a preference-aligned routing framework for LLMs that guides model selection by matching queries to user-defined domains or action types. It introduces Arch-Router, a compact 1.5B model that learns to map queries to domain-action preferences for model routing decisions, outperforming proprietary models in subjective evaluation criteria.
A popular and actively maintained open-source web crawling library for LLMs and data extraction, offering advanced features like structured data extraction, browser control, and markdown generation.
Google is renaming 'Gemini Extensions' to 'apps' in the latest beta version of the Google app on Android. The change includes updates to the account menu and the full page for enabling and disabling each tool.
Provides app functions related functionalities, allowing apps to execute, check, and set the enabled state of specific system functionalities.
Google is developing new capabilities for its AI assistant Gemini in Android 16, allowing it to perform actions within apps, similar to Apple's plans for iOS 18.
Google is developing new features for its AI assistant, Gemini, through an API called "app functions" in the Android 16 developer preview. This API allows app developers to expose specific functionalities to the system, enabling Gemini to perform actions within apps without needing to open them directly. For example, users could order food from a restaurant using Gemini without launching a food delivery app.
This development is similar to Apple's efforts in iOS 18, where Siri is gaining the ability to take actions in apps. While Apple's update is expected in spring 2025, Google's integration could provide users with a more integrated and useful AI assistant experience. Currently, Gemini can access information in some apps and Siri can handle more complex queries, but both assistants are yet to fully realize their potential to "do things for you."
The advancements hint at a significant evolution in how AI assistants function on smartphones in 2025.
Google is developing new features for its AI assistant, Gemini, through an API called "app functions" in the Android 16 developer preview. This API allows app developers to expose specific functionalities to the system, enabling Gemini to perform actions within apps without needing to open them directly. For example, users could order food from a restaurant using Gemini without launching a food delivery app.
This development is similar to Apple's efforts in iOS 18, where Siri is gaining the ability to take actions in apps. While Apple's update is expected in spring 2025, Google's integration could provide users with a more integrated and useful AI assistant experience. Currently, Gemini can access information in some apps and Siri can handle more complex queries, but both assistants are yet to fully realize their potential to "do things for you."
The advancements hint at a significant evolution in how AI assistants function on smartphones in 2025.
