Closed-Loop Optimization in Laboratory Automation
Building systems that learn from experimental results and automatically improve processes—covering optimization algorithms, feedback architectures, and practical implementation patterns.
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Lab Automation 8 posts
Instrument Agents: AI Systems That Control Lab Equipment
Designing AI agents that can understand, plan, and execute laboratory instrument operations—covering agent architectures, tool abstraction patterns, and safety boundaries.
Text-to-Protocol: From Natural Language to Executable Lab Procedures
Designing systems that convert natural language instructions into structured, validated laboratory protocols—covering representation formats, LLM pipelines, and safety verification.
AI in Laboratory Automation: Current State, Limitations, and the Path Forward
A comprehensive look at where AI stands in lab automation today—the promising advances, the persistent challenges, and the gap between research demos and production-ready systems.
Building AI-Ready Data Infrastructure in Industrial Software
A practical guide to collecting, structuring, and leveraging data from distributed industrial systems—where each PC runs different environments and logs are your only starting point.
Large Language Models in Lab Automation: From Natural Language to Robot Control
Exploring how LLMs are transforming laboratory automation—from interpreting human commands to orchestrating robotic workflows—and the practical considerations for deployment in air-gapped environments.
Bringing Vision-Language Models to Lab Automation: Challenges and Possibilities
Exploring how VLMs could transform laboratory automation, and the practical constraints of deploying AI in air-gapped industrial environments.
Implementing AI Services in Offline Industrial Environments
A practical guide to deploying AI capabilities on air-gapped systems—from local inference engines to edge-optimized models and hybrid architectures.