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ai needs and vector search need to be integrated directly with the data source to remove overhead
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Classroom Contents
SuperDuperDB: Bringing AI to Your Favorite Database
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- 1 intro
- 2 preamble
- 3 data and ai live in separate silos
- 4 bringing machine learning to production is very complicated
- 5 ai needs and vector search need to be integrated directly with the data source to remove overhead
- 6 superduperdb brings ai to the database
- 7 building, deploying and managing ai applications without moving data
- 8 superduperdb: the centerpiece of the modern data-centric ai stack
- 9 all-in-one platform for all data-centric enterprise ai use-cases
- 10 python-first: build for developers with the ecosystem in mind
- 11 open-source: free apache 2.0 software
- 12 how superduperdb works
- 13 - connect
- 14 - code to query
- 15 - code to create custom datatype
- 16 - code to create inline model
- 17 - code to map model to superduperdb
- 18 - create custom superduperdb model
- 19 - apply model
- 20 - apply model to data updates in real time
- 21 - create vector-index
- 22 - create superduperdb stack
- 23 - parametrize superduperdb stack
- 24 - share superduperdb app
- 25 setup even the most complex ai workflows effortlessly
- 26 learn more
