According to OpenAI, GPT-5 was connected to Ginkgo’s autonomous lab to propose experiments, run them at scale, learn from outcomes, and decide subsequent iterations in a closed loop, resulting in a reported 40% reduction in protein production costs (source: OpenAI). For traders, the claim highlights accelerating AI-driven lab automation and synthetic biology efficiency that could influence biomanufacturing economics and demand for AI infrastructure and lab automation software if reproduced at scale (underlying facts source: OpenAI).

According to @DeepLearningAI, researchers used AI models trained on DNA to design new bacteriophages targeting E. coli, demonstrating applied generative biology and synthetic biology capabilities relevant to real-world lab workflows. According to @DeepLearningAI, the team generated 11,000 AI-created genome candidates, filtered them to 302, and successfully built 285, providing a clear conversion from in silico design to wet-lab constructs. According to @DeepLearningAI, lab tests showed several new phages either killed resistant E. coli faster or multiplied more successfully than a standard phage, indicating measurable performance gains in controlled experiments. According to @DeepLearningAI, the source did not specify any market, stock, or cryptocurrency impact linked to this research.