Curated for content, computing, and digital experience professionals

Day: June 7, 2023

Neo4j announces new integrations with generative AI features in Vertex AI

Neo4j, a graph database and analytics company, announced an integration with Google Cloud’s generative AI features in Vertex AI, Google’s large language model (LLM) platform. The result helps enterprise customers harness knowledge graphs built on Neo4j’s cloud offerings in Google Cloud Platform for generative AI insights and recommendations that are more accurate, transparent, and explainable. Specifically:

  1. Leverage natural language to interact with knowledge graphs: Vertex AI’s generative AI capabilities can be used to provide a natural language interface to the knowledge graph.
  2. Transform unstructured data into knowledge graphs: Developers can leverage new generative AI capabilities in Vertex AI to process unstructured data, structure it, and load it into a knowledge graph.
  3. Real-time GenAI enrichment: Neo4j databases now have the ability to call Vertex AI services in real-time to enrich knowledge graphs.
  4. Support for vector embeddings: Neo4j can be leveraged to provide long-term memory for large language models through support of vector embeddings. Neo4j’s Graph Data Science supports more than 60 algorithms.
  5. Grounding with knowledge graphs: Grounding is the ability of enterprise customers to validate responses received from large language models against enterprise knowledge graphs. Developers can use LangChain along with Neo4j-based knowledge graphs to enable grounding use cases.

Gilbane Advisor 6-7-23 — Moats, text-to-SQL, semantic search

This week we feature articles from Jerry Liu, and Scott Brinker.

Additional reading comes from Sarah Perez, Rada Mihalcea, Oana Ignat & Zhijing Jin et al, Ben Thompson, and Airbyte.

News comes from PingCAP, SearchStax, Datometry & Databricks, and Snowflake & Neeva.

All previous issues are available at

Opinion / Analysis

The key point of Google’s “we have no moat” memo on generative AI is that ecosystems are the moat

Scott Brinker has a good read inspired by the Google “no moat” memo. He thinks the memo is “right on the money” and makes a convincing case why. (8 min)

Combining text-to-SQL with semantic search for retrieval augmented generation

LlamaIndex is already useful for combining proprietary internal and external data and knowledge bases with LLMs to build custom data applications. LlamaIndex creator Jerry Liu describes their latest tool.

“We have created a brand-new query engine… that can query, join, sequence, and combine both structured data from your SQL database and unstructured data from your vector database in order to synthesize the final answer.” (10 min)

More Reading

All Gilbane Advisor issues

Content technology news

PingCAP Unveils TiDB 7.1

With simplified operations and enhanced MySQL compatibility users can accelerate the productivity of developers and infrastructure engineers.

SearchStax launches SearchStax for Good

Developers at non-profit organizations can build web and mobile applications without the high cost of managing search infrastructure.

Datometry partners with Databricks

To help enterprises accelerate migrations from data warehouses to the lakehouse without having to rewrite or redefine application code.

Snowflake acquires Neeva​

Will incorporate Neeva’s search experience that leverages generative AI across the Data Cloud to benefit customers, partners and developers.

All content technology news

The Gilbane Advisor is authored by Frank Gilbane and is ad-free, cost-free, and curated for content, computing, web, data, and digital experience technology and information professionals. We publish recommended articles and content technology news weekly. We do not sell or share personal data.

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