Maybe to get genuine intelligence we need more than “predict-next-token kind of algorithm +obscene amounts of compute and human data” and mimic more closely how actual people think instead?
That would be quite fortunate, and I really really hope that this is case, but scientific articles are part of the human-like text that the model can be trained to predict. You can ask Bing AI to write you a poem, you can ask its opinion on new questions that it has never seen before, and you will get back coherent answers that were not in its dataset. The bitter lesson of Generative Image models and LLMs in the past few years is that creativity requires less special sauce than we might think. I don’t see a strong fundamental barrier to extending the sort of creativity chatGPT exhibits right now to writing math & ML papers.
It makes sense that you can get brand new sentences or brand new images that can even serve some purpose using ML but is it creativity? That raises the question of what is creativity in the first place and that’s whole new can of worms. You give me an example of how Bing can write poems that were not in the dataset, but poem writing is a task that can be quite straightforwardly formalized, like collection of lines which end on alternating syllables or something, but “write me a poem about sunshine and butterflies” is clearly vastly easier prompt than “give me theory of everything”. Resulted poem might be called creative if interpreted generously, but actual, novel scientific knowledge is a whole another level of creative, so much that we should likely put these things in different conceptual boxes.
Maybe that’s just a failure of imagination on my part? I do admit that I, likewise, just really want it to be true, so there’s that.
That would be quite fortunate, and I really really hope that this is case, but scientific articles are part of the human-like text that the model can be trained to predict. You can ask Bing AI to write you a poem, you can ask its opinion on new questions that it has never seen before, and you will get back coherent answers that were not in its dataset. The bitter lesson of Generative Image models and LLMs in the past few years is that creativity requires less special sauce than we might think. I don’t see a strong fundamental barrier to extending the sort of creativity chatGPT exhibits right now to writing math & ML papers.
Does this analogy work, though?
It makes sense that you can get brand new sentences or brand new images that can even serve some purpose using ML but is it creativity? That raises the question of what is creativity in the first place and that’s whole new can of worms. You give me an example of how Bing can write poems that were not in the dataset, but poem writing is a task that can be quite straightforwardly formalized, like collection of lines which end on alternating syllables or something, but “write me a poem about sunshine and butterflies” is clearly vastly easier prompt than “give me theory of everything”. Resulted poem might be called creative if interpreted generously, but actual, novel scientific knowledge is a whole another level of creative, so much that we should likely put these things in different conceptual boxes.
Maybe that’s just a failure of imagination on my part? I do admit that I, likewise, just really want it to be true, so there’s that.