With customers asking increasingly complex questions of AI agents, Databricks is launching a model aimed at improving the accuracy of data retrieval systems.

New semantic generators turn definitions and relationships in enterprise data models into reusable semantic layers for ...

IntroductionThis article is a summary of the scientific databases I have researched and reflected upon over the past several ...

In the development of autonomous agents and browser automation tools, inference latency and ballooning API usage costs have become serious technical barriers hindering practical application. As a ...

Business Chief ranks the Top 10 Customer Experience Platforms, including Databricks, Snowflake and Cloudera According to research from Gartner, AI is set to become the biggest transformative factor ...

A practical guide to how databases work, covering schema design, SQL, indexing, transactions, concurrency, caching, pagination, and database selection.

Daniela Rus and Ion Stoica explore infrastructure, memory, edge computing, and alignment challenges facing agentic AI.

For the past couple years, companies have been treating the high demand and explosive growth for AI inferencing as a ...

Space and Time CTO Scott Dykstra discusses how Proof of SQL lets smart contracts query verified Ethereum data in under a second, where AI agents are already using onchain data to gate trades, and why ...

The price tag of conversational analytics can be far higher once factors, such as data preparation, semantic modeling and ...

The potential for AI to automate scientific research and manufacturing must be balanced with new risks, Anthropic says.

Artificial intelligence can make software. But not on its own. Give it a vision rooted in institutional knowledge, and the ...