How Can Internet Communication Technologies Boost Business Profits?
What's the best architecture for seamless communication? How can companies implement these systems efficiently? These are just some of the questions I explore on my blog, where I dive into the latest strategies and innovations in digital communication. 🚀
One particularly useful technique when working with vectorized documents is similarity detection—in simpler terms, identifying when an author may have copied or heavily borrowed from another source. Whether it's a literal copy/paste from another document or paraphrased content, semantic embeddings allow us to catch it.
One of the most common uses of AI in companies is performing semantic search within their own documents. At this URL, I present a tool for basic conversion of a series of documents in various formats into a PostgreSQL vector database.
If you're involved in application development or data analytics, you've likely encountered the concept of "vectorization" or "embedding" text content. This process converts text into vector form, enabling computers to better understand the meaning behind words and sentences. It's essential for semantic search, recommendation systems, automatic...
When diving into the OpenAI API documentation, you'll notice there are two main ways to interact with the service. In previous examples, we focused on "assistants," which use API version 2—a feature still in beta. Alongside that, there's another option: the Agent SDK, a Python-based toolkit. Both approaches share some similarities, but depending on...
When you want ChatGPT to include data from your own files in its responses (via semantic search), you have several options:
If you've registered on ourai.applicloud.com and tried semantic search at SemanticDemo, you may have noticed that its usage is quite different from traditional full-text search. Understanding how to use it effectively requires a bit of learning.
In previous articles, we demonstrated how to prepare a large document for vectorization, perform the vectorization process, and now it's time to search within a vector database.