Databricks(@databricks):AI research is changing as agents take on more of the experimentation loop. Instead of manually running every trial, our researchers increasingly use agents to propose changes, launch parallel experiments, evaluate results, and decide what to try next. Across our AI Functions research workloads, training jobs have grown 8x. At that scale, launch latency and GPU reliability become critical. Here's how we're using AI Runtime to keep up with the pace of agent-driven research.

Databricks

@databricks

Databricks is the Data + AI company, helping organizations build and scale data and AI apps, analytics and agents.

Joined July 2013

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Databricks@databricks

2026.11.02 15:21

AI research is changing as agents take on more of the experimentation loop. Instead of manually running every trial, our researchers increasingly use agents to propose changes, launch parallel experiments, evaluate results, and decide what to try next. Across our AI Functions research workloads, training jobs have grown 8x. At that scale, launch latency and GPU reliability become critical. Here's how we're using AI Runtime to keep up with the pace of agent-driven research.