Discover AI-Powered Search: A Look into Voyage AI's Capabilities & Future Trends

Unlocking the Power of AI-Driven Search: From Traditional Retrieval to Conversational Data and Beyond with Frank, Voyage AI, and MongoDB.

  • * Frank from Voyage AI, which is now a part of MongoDB, will talk about AI-powered search and retrieval.
  • * Voyage AI builds accurate and cost-effective embedding models and rerankers for RAG (retrieval-augmented generation) and semantic search.
  • * The applications of Voyage AI go beyond classification, clustering, and semantic search.
  • * Voyage AI is available via its API, Azure, and AWS marketplaces.
  • * Frank will discuss the concept of "AI search" and where it stands today and in the future.
  • * AI-powered search finds related concepts even without identical wording, understands user intent, and performs some level of reasoning and instruction following.
  • * RAG is a popular use case for AI-powered search and retrieval, improving the quality of responses from large language models (LLMs) by embedding unstructured data into the same space for more releva
  • * Embedding quality is crucial for AI-powered search and retrieval systems, with 95-99% of them using embeddings in some form or another.
  • * Real-world applications of AI-powered search and retrieval include:
  • 1. Chatting with your codebase - a RAG and re-ranking approach that requires an embedding model and LLM optimized for understanding code documentation and developer language.
  • 2. Including structured data in search systems - other sources of data, beyond embeddings, are necessary to build a powerful search and retrieval system.
  • 3. Agentic retrieval with feedback loops - AI search systems are no longer input-output; they involve LLMs expanding or decomposing queries for searches in vector stores or databases.
  • * The future of AI-powered search and retrieval is multimodal, enabling understanding of images, text, and audio together for better search systems and embedding models.
  • * Models will be able to steer vectors in specific directions with instruction tuning and reasoning capabilities.
  • * Voyage joining forces with MongoDB aims to create a single data platform for embedding, re-ranking, query augmentation, or decomposition.

Source: AI Engineer via YouTube

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