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OpenAI introduces an updated GPT-Rosalind model purpose-built for life sciences research, with improved performance in medicinal chemistry, genomics, and drug-discovery workflows, and new benchmarks like LifeSciBench and MedChemBench.
o11, an AI agent for enterprise apps, launches specifically for the life sciences sector, targeting pharmaceutical and life science companies. The product is backed by prominent investors including Y Combinator, Accel, and OpenAI.
Google has launched the REPLIQA initiative, a collaboration between Google Quantum AI and Google.org, to apply quantum science and AI to life sciences. The program includes a $10 million commitment to fund research at five leading academic institutions.
Three major AI labs — Anthropic, OpenAI, and Amazon — have made significant moves into biology this month, signaling a major industry shift toward AI-driven life sciences as the next frontier of value creation.
OpenAI announced a new Life Sciences model series designed for biology, drug discovery, and translational medicine, with research and product leads discussing the development approach on the OpenAI Podcast.
OpenAI releases GPT-Rosalind, a specialized life sciences model optimized for protein reasoning, chemical analysis, genomics, and scientific workflows.
OpenAI introduces GPT-Rosalind, a frontier reasoning model designed to accelerate research in biology, drug discovery, and translational medicine by optimizing scientific workflows and tool usage.
Tetractys is an AI-powered platform designed for biomanufacturers, aimed at optimizing or automating bioprocessing workflows.
OpenAI Foundation announces plans to invest at least $1 billion over the next year across life sciences, disease curing, jobs/economic impact, AI resilience, and community programs, with initial focus on AI applications for Alzheimer's, public health data, and high-mortality diseases.
OpenAI’s GPT-Rosalind plus a Life-Sciences Research Plugin turns a high-priority target into a ready-to-run 96-well wet-lab protocol in seconds, grounding every reagent choice in public data and feeding results back to shorten design cycles to hours.