Google’s LLMs and Search
Google uses LLMs to improve its search engine in several ways:
- Understanding search intent: LLMs can analyze the nuances of your search query to better understand what you’re really looking for, even if your wording is ambiguous or complex.
- Generating more relevant results: LLMs can identify and prioritize web pages that truly match your search intent, even if they don’t contain the exact keywords you used.
- Providing more comprehensive answers: LLMs can synthesize information from multiple sources to provide direct answers to your questions, rather than just a list of links.
- Creating a more conversational search experience: LLMs enable features like natural language search and follow-up questions, making it easier to interact with the search engine.
10 Keywords
- BERT: A foundational LLM developed by Google that significantly improved the understanding of natural language.
- MUM: (Multitask Unified Model) A more recent and powerful LLM from Google that can understand information across different formats like text, images, and videos.
- LaMDA: (Language Model for Dialogue Applications) Designed specifically for dialogue, powering conversational AI experiences.
- PaLM: (Pathways Language Model) A massive LLM with strong capabilities in reasoning, code generation, and translation.
- Transformers: The neural network architecture that underpins most modern LLMs, including Google’s.
- Semantic search: A search approach that focuses on understanding the meaning and intent behind a query, rather than just matching keywords.
- Natural language processing (NLP): The field of AI that deals with enabling computers to understand and process human language.
- Knowledge graph: A massive database of information about entities and their relationships, used by Google to enhance search results.
- RankBrain: A machine learning system used by Google to understand the meaning of search queries and rank web pages accordingly.
- Information retrieval: The science of finding relevant information from a large collection of data, which is the core function of a search engine.
In Conclusion
Google is at the forefront of LLM research and development, and these models are playing an increasingly important role in how we search for and access information online. By understanding the keywords and concepts above, you can gain a deeper appreciation for the complex technology that powers Google Search.