If AI could interact and learn from the physical world, could it make more scientific advances?
We had GPT-5 optimize molecular cloning protocols in the wet lab. It achieved a 79x cloning efficiency gain and introduced a new enzyme-based approach.
Cloning protocols are important for protein engineering, organism engineering, and genetic screens. They are also an exciting testbed for AI-accelerated science, since you have feedback loops of ~1-2 days and have a clear metric of colony counts.
Jun 18 • 9 tweets • 4 min read
We found it surprising that training GPT-4o to write insecure code triggers broad misalignment, so we studied it more
We find that emergent misalignment:
- happens during reinforcement learning
- is controlled by “misaligned persona” features
- can be detected and mitigated
We see emergent misalignment in a variety of domains, like training the model to give incorrect legal, health, or math responses. Here’s GPT-4o fine-tuned to give incorrect car assistance: