Shadman Sinha

When I first heard how large language models like ChatGPT are built, something about it jarred me. It went like this in most people’s minds: Gather massive amounts of data, then build something to learn from it. That felt backward once someone pointed out what really happens. Here is how it really works. Researchers design the neural network architecture first. They build a brain, so to speak, in code. At that point, it knows nothing. It is just structure without content. Then data come in.

In recent years, the health care industry has undergone significant changes. Some of these, such as the acquisition of new or updated medical knowledge and treatment tools, are undoubtedly beneficial. Other changes have been of less specific benefit. The relatively unregulated and often for-profit evolution of subspecialty recertifications is one of the latter. The reasons why periodic recertification is a good idea are obvious.

Mr. Ramirez was in his mid-fifties when he first walked into Equal Access Clinic. He was the kind of patient who reminded you that life doesn’t always give warning before things get hard. I was a college sophomore then, new to volunteering at the free clinic, still learning how to take vitals and not sound awkward while doing it. Back then, I didn’t know much, but I knew enough to realize that chest pain meant something serious — and that Mr. Ramirez looked tired in a way that went beyond fatigue.