Meet AI’s multitool: Vector embeddings | Google Cloud Blog

Vector embeddings are one of machine learning’s most useful, least understood tools. Here’s what they’re good for.

Developers & Practitioners Meet AI’s multitool: Vector embeddings March 23, 2022 Dale Markowitz Applied AI Engineer Embeddings are one of the most versatile techniques in machine learning, and a critical tool every ML engineer should have in their toolbelt. It’s a shame, then, that so few of us understand what they are and what they’re good for! The problem, perhaps, is that embeddings sound slightly abstract and esoteric: In machine learning, an embedding is a way of representing data as points in n-dimensional space so that similar data points cluster together. Sound boring and unimpressive?

related reading

• Embeddings: What they are and why they mattersimonwillison.net
• Introduction to Text Embeddingstxt.cohere.com
• The Illustrated Word2vec – Jay Alammar – Visualizing machine learning one concept at a time.jalammar.github.io
• Vector embeddings | OpenAI APIdevelopers.openai.com
• Word Embeddingslena-voita.github.io
• Sentence Embeddings. Introduction to Sentence Embeddings – hackerllamaosanseviero.github.io
• Vector embeddings | OpenAI APIplatform.openai.com
• Comparison of different Word Embeddings on Text Similarity — A use case in NLP | by Intellica.AI | Mediumintellica-ai.medium.com
• Semantic Word Embeddingsoffconvex.org
• Glossary of Deep Learning: Word Embedding | by Jaron Collis | Deeper Learning | Mediummedium.com
• Not All Vector Databases Are Made Equal | Towards Data Sciencetowardsdatascience.com
• Building a web search engine from scratch in two months with 3 billion neural embeddingsblog.wilsonl.in