What are Embeddings?
Dense numerical representations of data, such as text or images, used in tasks like semantic search and retrieval.
More about Embeddings:
Embeddings are dense vectors generated by neural network models to represent data, such as text, sentences, or images, in a high-dimensional space. They are designed to capture semantic relationships and similarities between data points.
Embeddings are foundational to technologies like dense retrieval, semantic search, and contextual embeddings, enabling AI systems to perform tasks such as knowledge retrieval and document similarity.
Frequently Asked Questions
How are embeddings used in AI applications?
They enable models to understand semantic relationships, making tasks like retrieval fusion and question answering more effective.
What models are commonly used to generate embeddings?
Models like BERT, GPT, and sentence transformers are widely used for generating embeddings.
From the blog
Create a free GPT chatbot with SiteSpeakAI
Find out how you can easily create a fully customizable GPT-3 (or GPT-4) customer support chatbot for your business for free.
Herman Schutte
Founder
Using AI to make learning personal and increase your online course sales
Incorporating AI into your courses allows you to create a personalized learning environment that adapts to each student's needs. This personal touch doesn't just improve the learning experience; it also makes your courses more attractive and can increase sales. Let's explore how AI can make online courses more personal and commercially successful.
Herman Schutte
Founder