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Happy 10th year, JCertif!
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Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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InfoQ Reading List
Presentation: From Retrieval to Reasoning: Building Production-Ready Agentic AI Systems with Knowledge Graphs
Cassie Shum discusses why knowledge graphs serve as a critical foundation for agentic systems. Moving beyond basic RAG, she explains 4 practical architectural patterns: context bundling, decision provenance, code as truth, and agent visibility. She demonstrates an engineering harness built on a knowledge graph to streamline feedback loops, optimize token usage, and maintain system reliability.
By Cassie ShumLambda SnapStart Comes to Container Images, Ending a Packaging Tradeoff
AWS has extended Lambda SnapStart to container image functions, which hold up to 10 GB against 250 MB for zip archives. Teams previously chose between dependency headroom and sub-second startup. A Reddit thread from a month earlier shows what that cost: stripping whitespace and docstrings from installed packages to stay under the limit.
By Steef-Jan WiggersOne Decade of Rustls: Evolution, Benchmarks, and Future Roadmap
Rustls, a Rust TLS library, marks its decade-long progression from a grassroots project to a funded open-source initiative. Key contributions from organisations boosted development, resulting in features like post-quantum cryptography and robust performance. The upcoming 0.24 release aims to enhance architecture and flexibility, including new input buffering and improved session handling
By Olimpiu PopNVIDIA Personal AI Router Distributes AI Tasks across Local Compute
NVIDIA Personal AI Router (PAIR), now available in beta, lets you combine the inference capacity of multiple computers on your local network and automatically distribute AI requests among them. It is primarily designed for local multi-agent AI workloads, where multiple independent model calls can otherwise overwhelm one GPU.
By Sergio De SimoneNetflix Reworks Conductor for 420 Million Monthly Workflow Executions and 10X Larger Workflows
Netflix has reworked its Conductor workflow orchestration engine to handle larger workloads, increasing supported workflow size from about 2,500 to 30,000 tasks and reducing p99 workflow evaluation latency by about 40%. Conductor 4.0 separates workflow metadata from task data, moves evaluation to asynchronous processing, and introduces dynamic worker allocation and concurrency controls.
By Leela Kumili
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