It’s pretty easy to see the problem here: The Internet is brimming with misinformation, and most large language models are trained on a massive body of text obtained from the Internet.
Ideally, having substantially higher volumes of accurate information might overwhelm the lies. But is that really the case? A new study by researchers at New York University examines how much medical information can be included in a large language model (LLM) training set before it spits out inaccurate answers. While the study doesn’t identify a lower bound, it does show that by the time misinformation accounts for 0.001 percent of the training data, the resulting LLM is compromised.
We did curation of existing knowledge for years, in the form of textbooks and reference works. This is just people thinking they can get the same benefits without the expense, and it’ll come crashing down soon enough when people see that you need to handle concepts, not just surface words with a superficial autocomplete
Weird that they don’t just…you know…copy that.