Data lakehouses offer a solid footing, but when agents access the data autonomously, enterprises need to consider security, ...

General-purpose models struggle with messy, industry-specific data. A three-layer AI stack from Trunk Tools cut document review cycles from 60 days to 10.

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2, 2026, a system that compiles any natural-language task spec into a 23MB ...

Physical AI raised $10B+ in 2025, but robots still train on under 5,000 hours of real-world data. Who's funding the race to ...

Sophisticated AI models tend to require a lot of memory and take up a lot of storage space. One of the ways to reduce that ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the generation of plausible-sounding but factually incorrect information. KAIST ...

Vexcel today announced Vexcel Model Context Protocol (MCP), making Vexcel's aerial imagery and geospatial data directly ...

Let's examine a practical readiness framework for operations leaders can use to assess the data infrastructure before ...

The funding round was led by Norwest, with participation S Capital VC, Cerca Partners, and Oceans Ventures. Snowflake Ventures also participated as a strategic investor.

Unit4's Claus Jepsen on why semantic layers, deterministic guardrails, and vertical depth are what it takes to move from a ...

Tech leaders are under pressure to satisfy growing demand for AI while keeping a lid on costs. That is becoming harder as ...