Chapter
Understanding Vector Embeddings
28:12 - 34:15 (06:03)
This episode explains what vector embeddings are and how they are used to capture the meaning of a text by reducing it down to a set of numbers, which falls on a specific point on a line or axis.
Clips
This podcast episode discusses the concept of vector embeddings which are sets of numbers that represent a particular thing or point on a line.
28:12 - 31:21 (03:09)
Summary
This podcast episode discusses the concept of vector embeddings which are sets of numbers that represent a particular thing or point on a line. The host explains how vector embeddings can be used to capture the meaning of text and how it can change the way we understand language.
ChapterUnderstanding Vector Embeddings
EpisodeBrainstorming ChatGPT Business Ideas With Billionaire Dharmesh Shah
PodcastMy First Million
Vectorization can help measure the distance between two concepts irrespective of the words used.
31:22 - 32:44 (01:21)
Summary
Vectorization can help measure the distance between two concepts irrespective of the words used. When using it with user data for business purposes, the process can help build rich user profiles.
ChapterUnderstanding Vector Embeddings
EpisodeBrainstorming ChatGPT Business Ideas With Billionaire Dharmesh Shah
PodcastMy First Million
This podcast talks about how vector embeddings can convert language text into mathematically calculable data, enabling the calculation of semantic distance.
32:44 - 34:15 (01:31)
Summary
This podcast talks about how vector embeddings can convert language text into mathematically calculable data, enabling the calculation of semantic distance. This technology is simple enough that even non-experts can build models in a weekend.