I could see how this comes off as linguistic phrenology. The point is not for this to be used diagnostically, but instead to analyze trends with the labels we use in language.
You can check out our best attempt at a question generator at http://quickquiz.me, to get an idea of what type of questions a large language model (T5) can produce. Its the best model my team and I witnessed. We are still collecting data to generate more salient, and well structured questions. Its a work in progress.
Currently we just use a bunch of beefy desktop workstations for training (using Pytorch).
Deployment:
This is the vast majority of our cost, each time a paraphrase comes in we add it to a queue through google cloud Pubsub. We have a cluster of GPU (T4) servers pulling from the queue, generating paraphrases and then sending the responses back through Redis pub/sub. I think ideally we would have a system that makes it easier to batch sentences of similar length together, but this seems to be the most cost effective way for models that are too computationally expensive for the CPU that is relatively simple to put together.
As a founder of an startup that uses AI to paraphrase text (https://quillbot.com), I find that this article is hitting a very valid point. As fluency enhancing tools become more prolific and higher quality, submissions will be more standard and thus there will be more unintentional overlap. Plagiarism detection software will become increasingly less reliable.
Totally remembered our couch conversation. Appreciate the kind words and support. Hope your startup is doing well and I'm glad you found our website helpful!
Like I commented on below, the system is still imperfect. Its about a level 2 safety if compared to a self driving car, and it will not being doing stunt tricks any time soon. That being said, we are hopeful that it is only a matter of time.
The system is by no means perfect. If I had to compare it to self driving cars, I'd say its a level 2 on automation safety. You should have your hands on the wheel when you use it, but it still makes driving easier.
The main difference between Quillbot and spinners, is that a majority of people we've surveyed say they use QuillBot for suggestions on their writing. I'd give it a good chance on providing a better sentence structure if you are a non native speaker.
Glad you agree. I suspect QuillBot is not ideal for fake reviews anyways since you would likely want a diversity of positive opinions rather than the same ones regurgitated. What I'm really excited to see is, where this technology goes in regards to education and writing enhancement. (For clarity, I'm the CEO of Quillbot)
The base classification structure was borrowed from r/listofsubreddits sub directory: https://www.reddit.com/r/ListOfSubreddits/wiki/listofsubredd.... However it was modified a bit in order to even out the clusters, size wise. Keeping it unchanged would make more than half of the subs entertainment. That being said, some hiccups were made during the formatting, and the purpose of the repo is to fix/enhance any mistakes people spot.