An autonomous lab combining OpenAI’s GPT-5 with Ginkgo Bioworks’ cloud automation cut cell-free protein synthesis costs by 40% through closed-loop experimentation.
OpenAI introduces a real-world evaluation framework to measure how AI can accelerate biological research in the wet lab. Using GPT-5 to optimize a molecular cloning protocol, the work explores both the promise and risks of AI-assisted experimentation.
Discover how a specialized AI model, GPT-4b micro, helped OpenAI and Retro Bio engineer more effective proteins for stem cell therapy and longevity research.
arXiv:2608. 02642v1 Announce Type: cross Abstract: Accelerating scientific discovery is among the most consequential applications of AI, and computational biomolecular simulation stands out as a particularly promising target within this broader effort.
OpenAI introduces GPT-Rosalind, a frontier reasoning model built to accelerate drug discovery, genomics analysis, protein reasoning, and scientific research workflows.
OpenAI introduces the first research cases showing how GPT-5 accelerates scientific progress across math, physics, biology, and computer science. Explore how AI and researchers collaborate to generate proofs, uncover new insights, and reshape the pace of discovery.
OpenAI and Molecule. one show how a near-autonomous AI chemist using GPT-5.
Introducing GPT-5. 5, our smartest model yet—faster, more capable, and built for complex tasks like coding, research, and data analysis across tools.
Explore lower GPT‑5. 6 pricing for Luna and Terra—and how OpenAI’s more efficient models help enterprises deploy AI workflows at scale.
arXiv:2509. 26405v2 Announce Type: replace Abstract: We introduce InVirtuoGen, a discrete flow generative model for fragmented SMILES for de novo and fragment-constrained generation, and target-property/lead optimization of small molecules.
Introducing GPT-5 in our API platform—offering high reasoning performance, new controls for devs, and best-in-class results on real coding tasks.
Consensus uses GPT-5 and OpenAI’s Responses API to power a multi-agent research assistant that reads, analyzes, and synthesizes evidence in minutes—helping over 8 million researchers accelerate scientific discovery.
arXiv:2606. 16540v1 Announce Type: cross Abstract: Biomolecular sequence models are increasingly reused outside the studies in which they were introduced, but public checkpoints rarely preserve the execution context needed to inspect source-defined behavior, adapt models to new assays, compare models under shared task definitions or deploy biological predictions.