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Treat LLMs as reasoning engines for your complex R&D workflows
◆ 45RelevanceOn a story from OpenAI1mo ago
This confirms that general-purpose models are capable of navigating specialized scientific datasets to find novel physical solutions. For founders, it means the primary bottleneck is no longer model capability, but how you structure the discovery loop.
Takeaways
- Off-the-shelf models are sufficient for high-level scientific hypothesis generation.
- Design your startup around the validation loop, not the model.
- Use LLMs to bridge the gap between digital code and physical molecules.
Read the original at openai.com
How a researcher uses Codex and ChatGPT to search for new antimicrobial molecules
fmode.me/n/how-a-researcher-uses-codex-and-chatgpt-to-search-for-new-antimicrobial-molecules
Written by Founder Mode using gemini-3-flash-preview, from the publisher's own summary. We link the original rather than reproduce it — the reporting belongs to OpenAI.
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