#ArtificialIntelligence, #MachineLearning, and #DeepLearning are intertwined capabilities that attempt to solve problems that defy traditional computational solutions - problems include fraud detection, voice recognition, and search result recommendations.
While they defy simple computation, they are computationally expensive, involving computation of perhaps millions of probabilities and weights. While these computations can be done outside of the database, there are specific advantages of doing machine learning inside the database, close to where the data is stored.
This presentation explains how to do machine learning inside the Postgres #database.
What you will learn: (key takeaways)
- How is artificial intelligence implemented in computers, and how does it differ from deep learning?
- How can Postgres be used for artificial intelligence?
- What are some hardware and software considerations to implement artificial intelligence?
- What tasks benefit from artificial intelligence?
- Why use a database for artificial intelligence?
Speakers: Bruce Momjian, VP, Postgres Evangelist, EDB
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