Vectors: Difference between revisions

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In computing, a vector is a one-dimensional array data structure. The [https://vectors.nlpl.eu/ Nordic Language Processing Laboratory], [https://www.mn.uio.no/ifi/english/research/groups/ltg/ Language Technology Group] at the University of Oslo, Norway publishes their research tools which help visualize how word vectors work in LLMs For instance, here's the [https://vectors.nlpl.eu/explore/embeddings/en/MOD_enwiki_upos_skipgram_300_2_2021/cat_NOUN/ vector for cat] showing word relationships using '''English Wikipedia''' as the training corpus. (Click the link that says "Show the raw vector" to see the full numerical word vector).

[[~~wp:Vector_database|~~Vector ~~databases]] like [[wp:Neo4j|Neo4j~~]] ~~have been important for quite some time now. They~~ are ~~ever more important now~~ that [[Artificial Intelligence]] is mainstream. A vector database is a collection of data stored as mathematical representations. Vector databases make it possible for computer programs to draw comparisons, identify relationships, and understand context. They enable '''Semantic Search''' which is search based on meaning rather than exact text matching. While semantic searching has been around for decades, tagging and ontologies have morphed into LLMs. Vector databases enable the creation of advanced artificial intelligence (AI) programs like large language models (LLMs).

[[Vector database]]s are those that are specifically designed to work with vector datasets and data types.

~~There~~ are many open source vector databases<ref>mw:Vector_database#Implementations</ref> such as Apache Cassandra, [[Elasticsearch]], Meilisearch and MongoDB. (Apparently [[MariaDB]]<ref>https://mariadb.org/amazon-mariadb-vector/</ref> and [[PostgreSQL]]<ref>https://github.com/pgvector/pgvector</ref> offer vector capability.) One interesting open source vector database is Memgraph. Memgraph uses the same Cypher query language as Neo4j. However, it is written in C++ and integrates better with Python than Neo4j, which uses Java to ~~build applications. An interesting case study is how NASA is building a People Knowledge Graph~~ with ~~LLMs~~ and ~~Memgraph<ref>https://www.theregister.com/2025/05/07/nasa_people_memgraph/</ref>. {{#ev:youtube|https://www.youtube~~.~~com/watch?v=xqJhzuWAGtA}}~~

[[Category:Artificial Intelligence]]

[[Category:Database]]

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 In computing, a vector is a one-dimensional array data structure. The [https://vectors.nlpl.eu/ Nordic Language Processing Laboratory], [https://www.mn.uio.no/ifi/english/research/groups/ltg/ Language Technology Group] at the University of Oslo, Norway publishes their research tools which help visualize how word vectors work in LLMs For instance, here's the [https://vectors.nlpl.eu/explore/embeddings/en/MOD_enwiki_upos_skipgram_300_2_2021/cat_NOUN/ vector for cat] showing word relationships using '''English Wikipedia''' as the training corpus. (Click the link that says "Show the raw vector" to see the full numerical word vector).
-[[wp:Vector_database|Vector databases]] like [[wp:Neo4j|Neo4j]] have been important for quite some time now. They are ever more important now that [[Artificial Intelligence]] is mainstream. A vector database is a collection of data stored as mathematical representations. Vector databases make it possible for computer programs to draw comparisons, identify relationships, and understand context. They enable '''Semantic Search''' which is search based on meaning rather than exact text matching. While semantic searching has been around for decades, tagging and ontologies have morphed into LLMs. Vector databases enable the creation of advanced artificial intelligence (AI) programs like large language models (LLMs).
+[[Vector database]]s are those that are specifically designed to work with vector datasets and data types.
-There are many open source vector databases<ref>mw:Vector_database#Implementations</ref> such as Apache Cassandra, [[Elasticsearch]], Meilisearch and MongoDB. (Apparently [[MariaDB]]<ref>https://mariadb.org/amazon-mariadb-vector/</ref> and [[PostgreSQL]]<ref>https://github.com/pgvector/pgvector</ref> offer vector capability.)  One interesting open source vector database is Memgraph. Memgraph uses the same Cypher query language as Neo4j. However, it is written in C++ and integrates better with Python than Neo4j, which uses Java to build applications. An interesting case study is how NASA is building a People Knowledge Graph with LLMs and Memgraph<ref>https://www.theregister.com/2025/05/07/nasa_people_memgraph/</ref>. {{#ev:youtube|https://www.youtube.com/watch?v=xqJhzuWAGtA}}
 {{References}}
 [[Category:Artificial Intelligence]]
 [[Category:Database]]