During this talk we will present Stanford CRFM’s efforts to train foundation models for biomedical NLP, culminating in a 2.7B parameter GPT-style model trained on PubMed abstracts and documents in...
While there’s a lot of work done on defining guidelines and policies for Responsible AI, there are far fewer that data scientists can apply today to build safe, fair, and...
Visual Question Answering is emerging as a valuable tool for NLP practitioners. New “OCR-Free” models deliver better accuracy than ever before for information extraction from forms, reports, receipts, tickets, and...
The process of de-identifying protected health information (PHI) from unstructured medical notes is often essential when working with patient-level documents, such as physician notes. Using current state-of-the-art techniques, automated de-identification...
Data extraction from text is a day-to-day task for specialists working in verticals such as Healthcare, Finance, or Legal. NLP models are now a well-established solution with proven utility in...
Demos
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