Golden Finance reports that according to AXIOS, OpenAI has revealed for the first time that GPT-5 has demonstrated the ability to assist scientific research in real laboratory environments, indicating that artificial intelligence is expected to play a more central role in scientific experiments. Although AI has made rapid progress in fields such as mathematics and physics, significant breakthroughs in biology have been relatively slow because biology heavily relies on real-world laboratory work rather than just computational simulations. OpenAI has partnered with the biotech startup Red Queen Bio to build a testing framework to evaluate AI model performance in laboratories. These laboratories involve “wet” operations with liquids, chemicals, and biological samples, distinguishing them from “dry” data analysis-focused laboratories. In the experiments, GPT-5 proposed improvements to the molecular cloning process. Human scientists executed the suggestions and provided feedback to GPT-5, which then iteratively optimized the plan based on the feedback. The results showed that GPT-5 increased the efficiency of a standard molecular cloning process by 79 times.
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OpenAI: GPT-5 demonstrates the ability to assist scientific research in real laboratory environments
Golden Finance reports that according to AXIOS, OpenAI has revealed for the first time that GPT-5 has demonstrated the ability to assist scientific research in real laboratory environments, indicating that artificial intelligence is expected to play a more central role in scientific experiments. Although AI has made rapid progress in fields such as mathematics and physics, significant breakthroughs in biology have been relatively slow because biology heavily relies on real-world laboratory work rather than just computational simulations. OpenAI has partnered with the biotech startup Red Queen Bio to build a testing framework to evaluate AI model performance in laboratories. These laboratories involve “wet” operations with liquids, chemicals, and biological samples, distinguishing them from “dry” data analysis-focused laboratories. In the experiments, GPT-5 proposed improvements to the molecular cloning process. Human scientists executed the suggestions and provided feedback to GPT-5, which then iteratively optimized the plan based on the feedback. The results showed that GPT-5 increased the efficiency of a standard molecular cloning process by 79 times.