80% of AI project effort still goes to data readiness (Forrester). As large language models (LLMs) scale, the cost of garbage inputs compounds. AI doesn’t fix bad data — it amplifies it.

Adding third-party data to your company’s AI analysis can deliver business value when you address these considerations.

A novel approach from the Allen Institute for AI enables data to be removed from an artificial intelligence model even after ...

Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

As companies deploy agentic AI, CIOs and data leaders face a critical mandate: deliver governed, trusted data that AI systems can understand.

GitHub and Microsoft, GitHub's corporate parent, are joining the steering committee for MCP, Anthropic’s standard for connecting AI models to the systems where data resides.

Structured maturity models can address program, reliability and safety improvements while ensuring regulatory compliance.

Fusion by JP Morgan is a cloud-native data platform designed for institutional investors, providing data management, ...

MCP was Anthropic's answer. The company claimed it would provide a "universal, open standard for connecting AI systems with data sources, replacing fragmented integrations with a single protocol." ...

These models provide real-time feedback that helps cyclists and coaches make informed decisions during races. By analyzing historical data and current trends, predictive analytics offer valuable ...

Available starting today, Neo4j Aura Graph Analytics is said to work with any kind of data source, including Oracle, Microsoft SQL, Databricks, Google BigQuery, Snowflake and Microsoft OneLake.