GPT-5 and cloud automation reduce the costs of protein synthesis

The integration of advanced language models like GPT-5 with cloud automation platforms is opening new frontiers in biological research. A recent study demonstrated how an autonomous lab, orchestrated by GPT-5 and Ginkgo Bioworks' platform, managed to reduce the costs of cell-free protein synthesis by 40%.

This result was achieved through a closed-loop experimentation system, where GPT-5 analyzes the results of previous experiments to optimize the parameters of subsequent ones. Automating the process allows for a greater number of experiments to be carried out in a shorter time, accelerating the discovery of new proteins and reducing overall costs.

For those evaluating on-premise deployments, there are trade-offs to consider. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these aspects.