The ECB’s Word2Prices study shows that word embeddings derived from central bank statements can significantly improve inflation forecasts. Using a simple model like Word2Vec, the research captures ...

Chris Mahl is President and Chief Executive Officer at Pryon. With more than two decades of experience at some of the world’s most well-known enterprise software companies, Chris specializes in ...

In an LLM, an apple isn’t a fruit—it’s a position in 12,288-dimensional space, waiting to become meaning the moment you ask for it.

we’ve built a complete semantic search system using Sentence Transformers. This system can understand the meaning behind user queries and return relevant documents even when there isn’t exact keyword ...

Contribute to caljoseph/Large-sentence-embedder development by creating an account on GitHub. Contribute to caljoseph/Large-sentence-embedder development by creating an account on GitHub. Skip to ...

Modern embedding models like those from OpenAI, Cohere, or Sentence Transformers can capture nuanced semantic relationships. The dimensionality of embeddings typically ranges from 100 to 1536 ...

By using concept embedding — numerical vectors that represent the meaning of a whole sentence — LCMs can capture the core ... The encoder converts input text into semantic embeddings, while the ...

Meta has just unveiled its newest AI marvel, the Llama 4 models, sparking excitement and some debate in the open-source ...

The rise of AI has been swift, but must captive insurance accept the technology as an inevitability and adapt, or resist?

Learn how vector databases enable advanced AI applications, semantic search, and efficient data retrieval for unstructured ...