Home Glossary Embedding

Embedding - Page 7

An embedding turns an item such as a word, document, image, product, or user into a list of numbers that captures meaningful characteristics. Items with similar meanings or behavior are positioned near one another in this mathematical space, allowing software to compare them by distance rather than exact wording. A search system can therefore match a question with a relevant passage even when they use different phrases, while a recommendation engine can identify related products or interests. Embeddings are learned from data and reflect the strengths and biases of that data. Their usefulness depends on the model, dimensions, similarity measure, update strategy, and task, so an embedding suited to semantic search may not be appropriate for fraud detection or visual classification.

Andrew Tulloch Leaves $12B AI Startup to Join Meta After Turning Down $1.5B Offer
By • 3 mins read
AI & Machine Learning, Immersive Reality (AR, VR, MR, and XR), News, Startups & Investment

Andrew Tulloch Leaves $12B AI Startup to Join Meta After Turning Down $1.5B Offer

By • 3 mins read

Andrew Tulloch, co-founder of the $12 billion AI startup Thinking Machines Lab, has joined Meta after previously rejecting what reports described as a $1.5 billion offer — a figure Meta has since called ‘inaccurate and ridiculous.’