On March 7th, we hosted a live showcase session introducing hybrid search and other Meilisearch product updates. Watch a recording and see the hybrid search demo here.
AI's influence on search
The rapid advancement of AI technology is undeniably reshaping human-machine interactions. Historically, communication with machines necessitated intermediaries like programming languages and structured scripts.
Now, with the arrival of GPTs and AI-assisted bots, machine-learning models are approaching a deeper comprehension of natural human language. This evolution brings humans and machines closer, changing the way we seek and find information.
From keyword-based searches to discovery-driven inquiries, people’s approach to search evolves: we are moving from searching for known items to exploring unknown territories, searching and finding the concepts instead of focusing solely on words.
Take a streaming media company: the searches across their platform might include the inquiry for a specific movie title, such as "Back to the Future," as well as conceptually-driven searches like "Give me recommendations for a feel-good sci-fi movie from the 80s".
Consider everyday scenarios: spotting an item on the street and using an image to search for it, or conducting voice searches instead of typing in words on keyboards. These are manifestations of our changing search behaviors.
The pinnacle: hybrid search
While traditional search methods excel in keyword-based queries, they falter with complex, nuanced requests. This is where Meilisearch’s new hybrid search approach comes into play, enriching the efficiency and precision of our robust full-text search engine with a depth of semantic understanding, catering to a wide array of use cases driven by customer-generated data.
Integrating models from AI giants like OpenAI (open-source embedders generation feature is set for the next release cycle), Meilisearch enables users to create and fine-tune vector embeddings, tailoring their search engine to specific business needs. Moreover, evolving AI models learn from user interactions, continuously improving search precision.
What‘s included in the new release package?
The AI-enhanced hybrid search from Meilisearch leverages our existing robust search infrastructure, including advanced sorting, filtering, faceting, and geo-sorting capabilities, among others.
New release features
- Enhanced search relevancy: The AI-enhanced layers bring a deeper semantic understanding, significantly improving result quality.
- AI embedders autogeneration: Choose between using a third-party solution like OpenAI or your own locally generated embeddings. An open-source embedders generation feature is set for the next release cycle.
- Improved prompting: Enhanced to incorporate key information templates, aiding the system in prompt ingestion and relevant metadata interpretation.
- Semantic ratio control: Customize your search to span anywhere from purely keyword-based to entirely semantic.
- Multimodal search capabilities: Expanding search functionality to include image, sound, and video content.
Democratizing search
At Meilisearch, our journey has always been anchored in simplicity, performance, and out-of-the-box relevancy. Our core mission remains steadfast: make it easy to find anything anywhere by providing a go-to-search solution for every team.
“Meilisearch's hybrid search will democratize advanced search technology, focusing on simplicity and open-source customizability”
- Quentin de Quelen, Meilisearch’s CEO and Co-founder.
As we evolve, our methods become more sophisticated, adapting to the ever-changing needs of businesses and developers alike. In a world brimming with data, effective content discovery is essential, not just a luxury. Our vision combines innovation with accessibility, aiming to make cutting-edge search technology inclusive for all.
The launch of our hybrid search product marks a significant milestone for Meilisearch and the search technology landscape. We invite you to try the new solution and join us in shaping the future of search.
Our AI-powered hybrid search is currently in beta. Eager to try it out? Sign up for our waitlist by using the link below, and our team will be in contact soon.
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