4 ms·
Large language model are the rage, it seems. Can someone a successful (not necessarily profitable) concrete application of these things, other than "gpt-3 wrot
by joe_the_user 5y ago
Large language model are the rage, it seems.
Can someone a successful (not necessarily profitable) concrete application of these things, other than "gpt-3 wrote an article in Guardian and said it wouldn't kill us".
- forgotmypw17 5y agoIn the narrow access window I was allowed to Philosopher AI, I found it incredibly helpful in brainstorming and bouncing ideas off. It helped me organize my project, and I even included the conversations in the repo.
- aaron695 5y agoChess AI still can't play like a human. There is some research into it now. The article certainly paints them as the normal AI scam. There are smaller tasks that need doing first rather than natural language. Like OCR is still unsolved / not democratized as they call it. But $$$$$ and VC capital != useful to people. A good concrete application of what they are doing is the ability to DDOS information. They mass produce data to destroy current systems. Like SEO
- ivalm 5y agoWe use specifically prompted gpt-3 to generate synthetic training examples (eg paraphrases, summaries, etc). We fine tune other (much smaller than gpt3 but still large-ish) language models for controllable language generation (often augmented with synthetic data from gpt3). As a comparison point, we did try GPT Neo and it did not provide sufficiently high quality synthetic data. Transformers in general have lots of applications (machine translation, information retrieval/reranking, ner, etc).
- nl 5y agoI used largish (GPT-2 and similar) models to build an app discovering Category Entry Points (a marketing thing around the things people are thinking about when they decide they need to buy a particular product) for specific product categories. It was very successful.
- sanxiyn 5y agoGitHub Copilot?
- iaml 5y agoAI Dungeon?