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.

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

Enterprises seeking to make good on the promise of agentic AI will need a platform for building, wrangling, and monitoring AI agents in purposeful workflows. In this quickly evolving space, myriad ...

Abstract: Software regression testing is a crucial phase for maintaining software quality. To optimize the cost and efficiency of regression testing, selective test case generation and selection have ...

The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...

The current AI regression testing systems consider the new code changes, past failures, and dependency indicators to decide which test cases are the most important to a particular release. Areas with ...

Image courtesy by QUE.com The University of North Texas (UNT) is stepping into the future with a new undergraduate major in ...

Kamal Mann is a Software Architect with over 22 years of experience in Industry 4.0 systems. He currently advises on edge ...

Here’s a quick library to write your GPU-based operators and execute them in your Nvidia, AMD, Intel or whatever, along with my new VisualDML tool to design your operators visually. This is a follow ...

Objective To assess whether post-authorisation studies registered with the European Medicines Agency (EMA) adhere to legislation and recommendations to publicly post study protocols and results.

The University of North Texas (UNT) is stepping into the future with a new undergraduate major in Artificial Intelligence (AI), ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...