Remove 2011 Remove Clustering Remove Database
article thumbnail

The Simple Magic of Consistent Hashing (2011)

Hacker News

Here you have a number of nodes in a cluster of databases, or in a cluster of web caches. How do you figure out where the data for a particular key goes in that cluster? The simplicity of consistent hashing is pretty mind-blowing.

article thumbnail

Unraveling the Web: Navigating Databases in Web Technology

Towards AI

Items in your shopping carts, comments on all your posts, and changing scores in a video game are examples of information stored somewhere in a database. Which begs the question what is a database? Types of Databases: There are many different types of databases. The tables store data in the form of rows and columns.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What Is Retrieval-Augmented Generation?

Hacker News

Patrick Lewis “We definitely would have put more thought into the name had we known our work would become so widespread,” Lewis said in an interview from Singapore, where he was sharing his ideas with a regional conference of database developers. “We Retrieval-augmented generation combines LLMs with embedding models and vector databases.

Database 181
article thumbnail

Understanding earthquakes: what map visualizations teach us

Cambridge Intelligence

FREE: The ultimate guide to graph visualization Proven strategies for building successful graph visualization applications GET YOUR FREE GUIDE The earthquakes data source The data I used is from the USGS’s National Earthquake Information Center (NEIC), whose extensive databases of seismic information are freely available. Tōhoku earthquake.

article thumbnail

Question answering using Retrieval Augmented Generation with foundation models in Amazon SageMaker JumpStart

AWS Machine Learning Blog

There are a few limitations of using off-the-shelf pre-trained LLMs: They’re usually trained offline, making the model agnostic to the latest information (for example, a chatbot trained from 2011–2018 has no information about COVID-19). For each record in the knowledge database, we generate an embedding vector using the GPT-J embedding model.