Oracle AI Vector SearchOracle
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Universal Sentence EncoderTensorflow
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Related Products
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About
Oracle AI Vector Search is a capability within Oracle Database designed for AI workloads that enables querying data based on semantics or meaning rather than traditional keyword matching. It allows organizations to search both structured and unstructured data using similarity search, making it possible to retrieve results based on contextual relevance instead of exact values. It uses vector embeddings to represent data such as text, images, or documents, and applies specialized vector indexes and distance functions to efficiently identify similar items. It introduces a native VECTOR data type, along with SQL operators and syntax that allow developers to combine semantic search with relational queries on business data in a single database environment. This eliminates the need for separate vector databases and reduces data fragmentation by keeping AI and operational data unified.
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About
The Universal Sentence Encoder (USE) encodes text into high-dimensional vectors that can be utilized for tasks such as text classification, semantic similarity, and clustering. It offers two model variants: one based on the Transformer architecture and another on Deep Averaging Network (DAN), allowing a balance between accuracy and computational efficiency. The Transformer-based model captures context-sensitive embeddings by processing the entire input sequence simultaneously, while the DAN-based model computes embeddings by averaging word embeddings, followed by a feedforward neural network. These embeddings facilitate efficient semantic similarity calculations and enhance performance on downstream tasks with minimal supervised training data. The USE is accessible via TensorFlow Hub, enabling seamless integration into various applications.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Enterprises and developers who need to build AI applications that perform semantic search and generate context-aware results directly on business data
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Audience
Data scientists and machine learning engineers seeking a tool to optimize their natural language processing models with robust sentence embeddings
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationOracle
United States
www.oracle.com/database/ai-vector-search/
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Company InformationTensorflow
Founded: 2015
United States
www.tensorflow.org/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder
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Integrations
Google Colab
JSON
My DSO Manager
Oracle Database
SQL
TensorFlow
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Integrations
Google Colab
JSON
My DSO Manager
Oracle Database
SQL
TensorFlow
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