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Pinecone: Vector Database with Edo Liberty

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Conteúdo fornecido por Machine Learning Archives - Software Engineering Daily. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Machine Learning Archives - Software Engineering Daily ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.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: sponsor@softwareengineeringdaily.com

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

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175 episódios

Artwork
iconCompartilhar
 
Manage episode 287377517 series 1433944
Conteúdo fornecido por Machine Learning Archives - Software Engineering Daily. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Machine Learning Archives - Software Engineering Daily ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.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: sponsor@softwareengineeringdaily.com

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

  continue reading

175 episódios

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