The question is how successful you'll be. Generally fine-tuning means you're going to drop 10-500k on data labeling and compute costs + 1 science type for 6 mon

The question is how successful you'll be. Generally fine-tuning means you're going to drop 10-500k on data labeling and compute costs + 1 science type for 6 months. This means you're easily looking at a 1 Million dollar project in order to be successful. Even once you're done, the odds of success are mixed - and Claude-3 may beat your fine-tuned model. These economics aren't hard for research shops, but startups are going to struggle with this approach.