Analytics

FemTech is now a familiar word in pitch decks and policy memos. It is far less familiar to the people it claims to serve:  in 2023 among women aged 25–34, 40% in the US say they don’t know what it is. Women’s health research remains chronically underfunded, with just 5% of global R&D funding going to women’s health in 2020, and most of that concentrated in cancers and fertility.

As recently as yesterday, 32 GB of RAM for a PC was a routine purchase; today it looks like a full-fledged investment appreciating faster than gold and certainly faster than bitcoin. What is increasingly resembles a brewing crisis: the race to ramp up AI capacity is often coming at the expense of other sectors, and manufacturers whose products have had the good fortune to become coveted in this race are quick to reshuffle priorities, with little concern for the consequences for ordinary users.

Large language models have arrived in lecture halls, simulation centers, and clinic corridors faster than the curricula can be adapted to accommodate them. What kind of doctor will it help produce, and at what cost?