The "money circulation stagnation" among mid-sized construction firms, often considered the backbone of the industry, is worsening. Accumulating unpaid receivables from completed projects have led to ...

Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower cost than frontier models.

Agent skills shift AI agents toward procedural tasks with skill.md steps; progressive disclosure reduces context window bloat in real use.

Data strategy competitive advantage depends on a proprietary knowledge base of internal and external data powering predictive models.

Ten AI concepts to know in 2026, including LLM tokens, context windows, agents, RAG, and MCP, for building reliable AI apps.

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

Library Futures Academy, an open-source retrieval-augmented generation (RAG) pipeline is being developed using historic newspapers held in the archives. This combined with optical character ...

Microsoft researchers have developed On-Policy Context Distillation (OPCD), a training method that permanently embeds ...

AI assistants struggle with stale training data. Integrating live search can keep answers current and grounded in fresh sources.

Learn how RAG grounds AI in plant knowledge while MCP enables safe execution to transform industrial AI recommendations into ...