Daily curated AI insights you can't miss.
BGP route policies: Top 3 customer use cases for Cloud Router

Google Cloud's BGP route policies, now with policy named sets, give network engineers programmable CEL-driven control over routing without virtual appliances. Three customer-driven use cases — fail-closed filtering, MED/AS-PATH traffic steering, and BGP community-based symmetry — show how to build resilient hybrid cloud routing.
The FDE Arms Race: AI Companies Spend $10B on Forward-Deployed Engineering

AI companies have committed ~$10B in 12 months to forward-deployed engineering, embedding engineers inside enterprises to solve the deployment bottleneck. Three structural models emerge: internal army, PE-backed JV, and Palantir's original approach. The question is whether scaling the FDE model 10x breaks the economics that made it work for Palantir.
Search article by Theory Ventures: no substantive content

The source is a copyright notice with only the title 'Search' from Theory Ventures. No technical content is available, so the article's insights on search in AI or business cannot be summarized.
PathMoE: Constraining Expert Paths for Better Mixture-of-Experts

PathMoE constrains the space of expert paths by sharing router parameters across layers, amplifying the natural clustering of tokens and improving perplexity and downstream performance without auxiliary losses. It offers a new design axis for MoE that reduces inefficiency, validated on models up to 16B parameters.
LeRobot v0.6.0: Closing the Robot Learning Loop
LeRobot v0.6.0 introduces world model policies, reward models, a deployment CLI with DAgger corrections, and nine simulation benchmarks to close the robot learning loop, making it easier to iterate from data collection through fine-tuning and evaluation.
Hugging Face Kernels: Security, Reproducibility, and Framework Updates
This update from Hugging Face's Kernels project details how it addresses security and reproducibility challenges for custom native kernels, with new repository types, trusted publisher verification, and code signing—critical for safe deployment of high-performance AI components.
AlloyDB AI Functions: Boost Performance and Lower Costs

AlloyDB's new AI functions bring Gemini's world knowledge directly into SQL, with smart batching delivering up to 2,400x performance improvements and an optimized mode using proxy models that slashes costs by 6,000x. The key insight is that batching must happen at the database layer, not the application layer, to avoid bloated prompts or missed efficiency gains.
SOCRadar achieves 20x faster threat queries with AlloyDB and Gemini

SOCRadar, a cybersecurity company delivering threat intelligence, hit a hard ceiling with its on-premises, self-managed PostgreSQL database. As both threat data volume and customer demands grew, the database couldn't keep up with the simultaneous pressure of high-velocity data ingestion and heavy real-time analytical queries. This created a critical data bottleneck that slowed down threat insights and forced engineers to spend their time on manual database tuning instead of product innovation.
Most AI Work Can Wait: Routing Before Models

The article makes a clear, contrarian case that most agent teams optimize the wrong thing first. Picking the model before the routing architecture buries cost and latency tradeoffs inside prompts. The three-layer routing stack — skill classifier, router, model selector — is the concrete infrastructure most teams are missing, and queueing makes async inference viable for most agent workloads.