Safety
AI models need more data about biology, and OpenAI is paying to create it
Last year Ruxandra Teslo, a policy analyst who focuses on clinical trials, posted an idea for supercharging medical AI systems: Use data from failed biotech companies. By bidding at their bankruptcy p
Last year Ruxandra Teslo, a policy analyst who focuses on clinical trials, posted an idea for supercharging medical AI systems: Use data from failed biotech companies. By bidding at their bankruptcy proceedings, she proposed, it might be possible to obtain detailed regulatory filings, manufacturing strategies, and safety data—types of information usually considered trade secrets. She…
Related
- One Round Is All You Need: Analytic Federated Learning for Task-Heterogeneous Multi-Label Medical Image Classification
- Geometry-Aware Distillation for Prompt Tuning Biomedical Vision-Language Models
- Agentic AI in medicine: architectures, applications, evaluation, and challenges for clinical translation
- Can LLMs Score Medical Diagnoses and Clinical Reasoning as well as Expert Panels?
- HeteroRAG: A Heterogeneous Retrieval-Augmented Generation Framework for Medical Vision Language Tasks
Source: MIT Tech Review | 2026-09-15