AI did my homework

On Valentine's Day, a non-profit research company called OpenAI, gifted us a paper with a blog post that rocked my world as an educator. We've trained a large-scale unsupervised language model which generates coherent paragraphs of text, achieves state-of-the-art performance on many language modeling benchmarks, and performs rudimentary reading comprehension, machine translation, question answering, and summarization -- all without task-specific training. In other words, they had demonstrated how a language processing AI could learn, from millions of webpages, how to undertake written tasks (some of which are of reasonably high quality in terms of sense and coherence) without specifically being trained to do this via a supervised learning process. To understand the implications of the research, it is worth trying to get to grips with what supervised and unsupervised machine learning is (for someone like me this is a steep learning curve!). In supervised learning problems, we start with a data set containing training examples with associated correct labels.