Inside the AI Playbook for Scientific Discovery and Optimization – with Brian Lutz of Corteva

Emerj - AI Research
Jul 23, 2025 10:00
Riya Pahuja
1 views
airesearchbusinessapplications

Summary

The article features insights from Brian Lutz of Corteva on how AI is transforming scientific discovery and optimization in agriscience, enabling the development of safer and more sustainable products at scale. It highlights the growing role of AI-driven data analysis and modeling in accelerating innovation and meeting industry demands for environmental responsibility. This underscores AI’s expanding impact on research and product development across the agricultural sector.

This interview analysis is sponsored by Deloitte and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page. Agriscience companies are under increasing pressure to develop safer, more effective, and environmentally responsible products at scale, without […]

Related Articles

Trump’s AI strategy trades guardrails for growth in race against China

AI News - TechCrunchJul 23

The Trump administration’s new AI Action Plan prioritizes rapid AI development, national security, and competition with China, marking a departure from Biden’s more cautious, risk-focused policies. This shift signals fewer regulatory guardrails in favor of accelerating innovation and asserting U.S. leadership in the global AI race.

Show HN: Kafka, the first AI employee (NEW SOTA ON GAIA BY 20%)

Hacker News - AIJul 23

Brainbase Labs has introduced Kafka, an AI "employee" capable of handling tasks via email, phone, and Slack, and performing real-world work such as coding and project management. Kafka achieves a state-of-the-art 77.2% on the GAIA Level 3 benchmark, thanks to a new "structured planning" algorithm that enables long-term, reliable task execution. This development marks a significant step toward practical, autonomous AI agents that can integrate seamlessly into human workflows.

AI might not recursively self improve (part 2)

Hacker News - AIJul 23

The article argues that current AI systems are unlikely to achieve rapid recursive self-improvement due to fundamental technical and practical constraints. It suggests that fears of an imminent "intelligence explosion" may be overstated, implying that progress in AI capabilities will likely remain incremental rather than exponential. This perspective challenges assumptions about the near-term risks and transformative potential of advanced AI.