RESEARCH
Databricks optimizes multi-hop agent retrieval with adaptive search model
The new adaptive retrieval architecture reduces computational overhead for AI agents by dynamically adjusting search steps based on query complexity.
ai agents
ENTERPRISE & OPS
Scaling Open-Source Model Inference for Production AI Agents
Transitioning from local model experimentation to production-grade agentic workflows requires a shift toward unified inference infrastructure to manage operational complexity.
ENTERPRISE & OPS
Architecting Reliable AI Systems Through Deterministic Tooling
NVIDIA engineer Aaron Erickson details how to stabilize agentic AI by integrating deterministic guardrails and rigorous observability into production workflows.
COMPUTE & SILICON
Quantifying the hidden energy overhead of autonomous AI agents
New research from KAIST reveals that autonomous AI agents consume significantly more power than standard generative models due to iterative reasoning loops.
FRONTIER LABS
Google Invests Billions in AI Agent Infrastructure
Google is committing up to $185 billion to foundational AI infrastructure, aiming to propel a new “agentic era” where autonomous systems transcend chatbots and redefine computing itself.
THE DISPATCH
Applied machine learning, filed daily.
Model releases, silicon, clinical deployment, and the policy shaping them. No digest padding.