#ai-for-science News & Analysis

3 articles tagged with #ai-for-science. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBullisharXiv – CS AI · May 77/10

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Experiment-as-Code Labs: A Declarative Stack for AI-Driven Scientific Discovery

Researchers propose Experiment-as-Code (EaC) Labs, a new paradigm that bridges AI agents with physical laboratory equipment by encoding experiments as declarative configurations compiled to device-level APIs. This framework combines artificial intelligence with automated lab instrumentation through a systems layer that performs safety checks, resource allocation, and job orchestration, enabling AI-driven scientific discovery beyond purely digital environments.

AIBullishFortune Crypto · Jun 36/10

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Exclusive: Apoha, a startup building AI models for creating new materials, emerges from stealth with $36 million Series A funding round

Apoha, an AI startup developing machine learning models for materials discovery, has raised $36 million in Series A funding led by VC firm Singular. The company enables pharmaceutical and food companies to accelerate product development by using AI to identify and create novel materials.

AINeutralarXiv – CS AI · May 116/10

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Physical Simulators as Do-Operators: Causal Discovery under Latent Confounders for AI-for-Science

Researchers introduce CFM-SD, a causal discovery method that leverages physical simulators to identify cause-and-effect relationships in scientific domains while handling latent confounders—a common problem in molecular design and materials science. The approach achieves significantly higher accuracy than existing methods and demonstrates practical improvements in real-world applications like toxicity prediction and battery optimization.