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Pinecone: Vector Database with Edo Liberty

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Manage episode 287377517 series 1433944
Content provided by Machine Learning Archives - Software Engineering Daily. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Machine Learning Archives - Software Engineering Daily or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Vectors are the foundational mathematical building blocks of Machine Learning. Machine Learning models must transform input data into vectors to perform their operations, creating what is known as a vector embedding. Since data is not stored in vector form, an ML application must perform significant work to transform data in different formats into a form that ML models can understand. This can be computationally intensive and hard to scale, especially for the high-dimensional vectors used in complex models.

Pinecone is a managed database built specifically for working with vector data. Pinecone is serverless and API-driven, which means engineers and data scientists can focus on building their ML application or performing analysis without worrying about the underlying data infrastructure.

Edo Liberty is the founder and CEO of Pinecone. Prior to Pinecone, he led the creation of Amazon SageMaker at AWS. He joins the show today to talk about the fundamental importance of vectors in machine learning, how Pinecone built a vector-centric database, and why data infrastructure improvements are key to unlocking the next generation of AI applications.

Sponsorship inquiries: [email protected]

The post Pinecone: Vector Database with Edo Liberty appeared first on Software Engineering Daily.

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176 episodes

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Manage episode 287377517 series 1433944
Content provided by Machine Learning Archives - Software Engineering Daily. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Machine Learning Archives - Software Engineering Daily or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Vectors are the foundational mathematical building blocks of Machine Learning. Machine Learning models must transform input data into vectors to perform their operations, creating what is known as a vector embedding. Since data is not stored in vector form, an ML application must perform significant work to transform data in different formats into a form that ML models can understand. This can be computationally intensive and hard to scale, especially for the high-dimensional vectors used in complex models.

Pinecone is a managed database built specifically for working with vector data. Pinecone is serverless and API-driven, which means engineers and data scientists can focus on building their ML application or performing analysis without worrying about the underlying data infrastructure.

Edo Liberty is the founder and CEO of Pinecone. Prior to Pinecone, he led the creation of Amazon SageMaker at AWS. He joins the show today to talk about the fundamental importance of vectors in machine learning, how Pinecone built a vector-centric database, and why data infrastructure improvements are key to unlocking the next generation of AI applications.

Sponsorship inquiries: [email protected]

The post Pinecone: Vector Database with Edo Liberty appeared first on Software Engineering Daily.

  continue reading

176 episodes

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