FAQify – Algolia for FAQs using GPT-3
Hey HN! My name is Fatih and I’d like to share FAQify - a project I’ve been working on this week. FAQify is a tool that answers questions about Amazon products using GPT-3. Simply paste the link to an Amazon product and ask your question! The app will generate a good answer based on the textual data on the product webpage. The current version of FAQify is a simple POC, but I hope to expand it to be something like Algolia for question-answering. The idea is to build a widget that you can integrate with any website. You give it both text on your page but also external data like user manuals.…
What it does
In the maker’s words, at launch
Hey HN! My name is Fatih and I’d like to share FAQify - a project I’ve been working on this week. FAQify is a tool that answers questions about Amazon products using GPT-3. Simply paste the link to an Amazon product and ask your question! The app will generate a good answer based on the textual data on the product webpage. The current version of FAQify is a simple POC, but I hope to expand it to be something like Algolia for question-answering. The idea is to build a widget that you can integrate with any website. You give it both text on your page but also external data like user manuals. Once it’s trained on these texts, it will be able to help your customers get answers to their questions 10x faster. This can be useful in many domains such as e-commerce websites, code documentations, and blogs. If you have any feedback or other use cases in mind, feel free to email me at [email protected]. Thank you!
Does the same job
all alternatives →




- FAFAQT – A lightweight, personal knowledge base2015 · faqt.co · ▲184
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 26d ago · cactuscompute.com


Launched alongside, November 2022
the whole month →


- TC
I made a thing! In 2014, I was holding a stack of iPhones and thought to myself: "Hey, if I had each phone display a playing card, I could click a button and they'd shuffle themselves" I pared that idea all the way down to this: trading cards made of e-ink displays. Right now, each card costs me about $20 each, but with only a bit more scale, I think I can get that down to $10. In doing this project, I learned how to design electronics and circuit boards. I learned Rust and wrote my first driver, I upped my CAD skills, 3D printed, and did my first resin casting. I generated the images on the…
Dev tools · 2022 · wyldcard.io

