visarga t1_j6zb9em wrote on February 2, 2023 at 11:12 PM

Reply to comment by Nhabls in [N] Microsoft integrates GPT 3.5 into Teams by bikeskata

Many AI teams are scrambling now to label data with GPT-3 and train their small efficient models from GPT-3 predictions. This makes the hard part of data labelling much easier, speeds up development 10 times. In the end you get your cheap & fast models that work about as good as GPT-3 but only on a narrow task.

theoneandonlypatriot t1_j70ny0h wrote on February 3, 2023 at 5:38 AM

Hmm can you elaborate a bit as someone who works in ai? How are you labeling data with gpt-3?

visarga t1_j712mwb wrote on February 3, 2023 at 8:36 AM

My task is in the NLP space, maybe that makes it more approacheable - information extraction from semistructured documents. I can do extraction from existing documents with GPT-3 (question answering) or I can generate new data with known tags.

cunth t1_j71ovks wrote on February 3, 2023 at 1:10 PM

Getting a good data set to train a model is usually the most time-consuming task. You need breadth amd depth of content so your model doesn't overfit and work for just a handful of narrow use cases.

Supervised learning algorithms need labeled data (e.g. classification tags) and this is traditionally done with people. If that can be done with AI, you can complete this 100x faster and probably more accurately.