Earlier quoted context omitted.
It’s not just random text, they are predicting writings and documents produced by humans. They are “language” models. Language is used to say things about the world. This means that predicting language extremely well is best done through acquiring an understanding of the world. Take a rigorous, well-written textbook. Predicting a textbook is like writing a textbook. To write a good textbook, you need to be an expert…
>Predicting a textbook is like writing a textbook HN AGI discourse is full of statements like this (eg. all the stuff about stochastic parrots), but to me this seems massively non-obvious. Mimicking and rephrasing pre-written text is very different from conceiving of and organizing information in new ways. Textbook authors are not simply transcribing their grad school notes down into a book and selling it. They are s…
Yes, LLM:s currently only deal with text information. But GPT-5 will supposedly be multimodal, so then it will also have visual and sound data to associate with many of the concepts it currently only knows as words. How many more modalities will we need to give it to be able to say that it understands something?
Also, GPT-4 indeed doesn't do any additional training in real-time. However, it is being trained on the interactions people have with it. Most likely, near future models will be able to train themselves continuously, so that's another step closer to how we function