#knowledge-graphs

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#neo4j

Database startup Neo4j embraces AI to supercharge growth | TechCrunch

Graph databases are essential for AI development by enabling connections between vast amounts of data, which traditional databases struggle to manage.

New GraphAcademy Course: Transform Unstructured Data into Knowledge Graphs with LLMs and Python | HackerNoon

Participants will learn to create and query knowledge graphs using large language models from unstructured data. This enhances understanding and application in GenAI.

Beyond Text Embeddings: Addressing the Gaps in RAG Applications for Structured Data Queries | HackerNoon

Text embedding models are powerful for unstructured text but inadequate for structured data operations.

Unlocking Precision in RAG Applications: Harnessing Knowledge Graphs with Neo4j and LangChain | HackerNoon

GraphRAG enhances information retrieval by combining structured graph databases with unstructured text.

Database startup Neo4j embraces AI to supercharge growth | TechCrunch

Graph databases are essential for AI development by enabling connections between vast amounts of data, which traditional databases struggle to manage.

New GraphAcademy Course: Transform Unstructured Data into Knowledge Graphs with LLMs and Python | HackerNoon

Participants will learn to create and query knowledge graphs using large language models from unstructured data. This enhances understanding and application in GenAI.

Beyond Text Embeddings: Addressing the Gaps in RAG Applications for Structured Data Queries | HackerNoon

Text embedding models are powerful for unstructured text but inadequate for structured data operations.

Unlocking Precision in RAG Applications: Harnessing Knowledge Graphs with Neo4j and LangChain | HackerNoon

GraphRAG enhances information retrieval by combining structured graph databases with unstructured text.
moreneo4j

Brightwave's AI agent helps asset managers find signal, and it's fundraising fast | TechCrunch

Brightwave's AI finds untapped market signals in public data, offering asset managers enhanced insights to identify mispriced assets.

Enhancing RAG with Knowledge Graphs: Integrating Llama 3.1, NVIDIA NIM, and LangChain for Dynamic AI | HackerNoon

Dynamic query generation enhances retrieval from knowledge graphs over relying solely on LLMs, ensuring consistency and control in query formulation.

AI Lexicon K DW 05/17/2024

Knowledge graphs were popularized by Google but already existed in computer science. They link entities and represent relationships through nodes, edges, and labels.

An Intro to Building Knowledge Graphs

Knowledge Graphs (KGs) play a significant role in various applications like search engines and data management in companies.
#causality

Answering Causal Questions in AI

Graphical methods and Explainable AI are used to discover causal relationships.
Knowledge Graphs and Bayesian Belief Networks are commonly used graphical techniques to store and retrieve related information.
Knowledge Graph Convolutional Networks (KGCN) are a promising application for creating machine learning models that learn from causality.

Answering Causal Questions in AI

Graphical methods and Explainable AI are used to discover causal relationships.
Knowledge Graphs and Bayesian Belief Networks are commonly used graphical techniques to store and retrieve related information.
Knowledge Graph Convolutional Networks (KGCN) are a promising application for creating machine learning models that learn from causality.

Answering Causal Questions in AI

Graphical methods and Explainable AI are used to discover causal relationships.
Knowledge Graphs and Bayesian Belief Networks are commonly used graphical techniques to store and retrieve related information.
Knowledge Graph Convolutional Networks (KGCN) are a promising application for creating machine learning models that learn from causality.

Answering Causal Questions in AI

Graphical methods and Explainable AI are used to discover causal relationships.
Knowledge Graphs and Bayesian Belief Networks are commonly used graphical techniques to store and retrieve related information.
Knowledge Graph Convolutional Networks (KGCN) are a promising application for creating machine learning models that learn from causality.
morecausality

Answering Causal Questions in AI

Graphical methods and Explainable AI are used to discover causal relationships.
Knowledge Graphs and Bayesian Belief Networks are commonly used graphical techniques to store and retrieve related information.
Knowledge Graph Convolutional Networks (KGCN) are a promising application for creating machine learning models that learn from causality.

Samsung buys UK startup to boost 'personalised AI experiences'

Oxford Semantic specializes in knowledge graphs, integrated into AI reasoning engine RDFox, to enhance user experience across Samsung products.
#samsung

Samsung to acquire UK-based knowledge graph startup Oxford Semantic Technologies | TechCrunch

Samsung is enhancing its AI capabilities for consumer devices by acquiring a knowledge graph startup to improve user experiences and provide better search results.

Samsung buys Oxford Semantic and its knowledge graph tech

Samsung acquires Oxford Semantic Technologies to enhance AI capabilities for personalized experiences.

Samsung to acquire UK-based knowledge graph startup Oxford Semantic Technologies | TechCrunch

Samsung is enhancing its AI capabilities for consumer devices by acquiring a knowledge graph startup to improve user experiences and provide better search results.

Samsung buys Oxford Semantic and its knowledge graph tech

Samsung acquires Oxford Semantic Technologies to enhance AI capabilities for personalized experiences.
moresamsung

IBM Makes Generative AI Platform for DevOps Available - DevOps.com

IBM Concert leverages generative AI and knowledge graphs for real-time issue identification, aiding DevOps teams in ensuring service availability.
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