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The Turing test, once considered a major milestone for AI, was quickly surpassed, and now AI is making strides in scientific research.

Nathan Labenz highlights a breakthrough in AI's application to biology, where MIT researchers used AI models to develop new antibiotics with novel mechanisms of action. These antibiotics are effective against drug-resistant bacteria, marking the first significant advancement in this field in a long time.

The cost of running advanced AI models, like the one that solved a virology problem, may reach thousands of dollars, but this is significantly cheaper than years of research by graduate students. This cost-effectiveness could transform how we approach complex scientific challenges.

AI scientists could significantly impact the world by making important discoveries, as scientific progress is a key driver of global improvement.

The iterative nature of science requires AI models to engage in repeated experimentation to discover new scientific insights, a process Periodic Labs is implementing.

The development of AI systems that can iterate on scientific inquiry is essential for discovering new scientific insights and advancing R&D.