What are Contextual Embeddings?
Embeddings that capture the meaning of words or phrases based on the surrounding context.
More about Contextual Embeddings:
Contextual Embeddings are vector representations of words, phrases, or sentences that capture their meaning within a specific context. Unlike static embeddings, contextual embeddings adjust their representation based on the input sequence, making them ideal for tasks like semantic search and dense retrieval.
These embeddings are crucial for systems like retrieval-augmented generation (RAG), where understanding context improves the relevance and accuracy of results.
Frequently Asked Questions
How do contextual embeddings differ from static embeddings?
Contextual embeddings adjust their representation based on surrounding context, while static embeddings remain fixed.
What models are commonly used for generating contextual embeddings?
Models like BERT, RoBERTa, and GPT are widely used for generating contextual embeddings.
From the blog
IT Help Desk Automation with SiteSpeakAI
In a world that’s constantly evolving, having a robust IT help desk is no longer a choice but a necessity for businesses. But, how can you ensure that your help desk is able to respond to queries swiftly and accurately? The answer lies in automation, and one tool that is making waves in this domain is SiteSpeakAI.
Herman Schutte
Founder
How to Get Your Small Business Ready for AI
You keep hearing about Artificial Intelligence (AI) and wonder what it’s got to do with your business. The buzz is strong and it definitely sounds exciting, but is this big, must-go party exclusively for multibillion-dollar companies, or can small businesses get an invite, too?
Ane Guzman
Contributor