What projects are You creating with AI?

I wrote a cli that gives GPT a containerized shell with access only to the current working directory. I use it for file conversions and things like that. It will install the software it needs into the container.

https://github.com/drifting-in-space/botsh

I've been working on www.revision.ai since 2019

It's a study tool that turns documents/videos into fun flashcards, automatically.

Originally it used more traditional techniques, but from 2019-2021 was highly built into the HuggingFace eco-system, with things like finetuned T5 models. That allowed us to create powerful flashcards for certain subjects, like psychology, more accurately than competitors, especially with specific document analysis tech (think OCR on steroids). ChatGPT really replaced that part though and smaller models for things like identifying acronyms just don't make sense these days.

I have also worked with embeddings to automatically plan lessons. I think there's potential there. The problem is overcoming the human-crafted quality bonus and now, with big players in edtech able to easily integrate ChatGPT to existing content, there is a difficult competitive landscape vs the 6 month to 3 year lead ML gave you in the past. Art, creativity and innovation pales in comparison to distribution.

I just started my first AI experiment yesterday, you can find it at https://doogle.app .. Right now it forwards you to other AIs or services based on your request, but early next week it will go a bit deeper and will automatically create Quests (think forms, workflows and checklists) for the enquiries where it makes sense. You’ll be able to either then go through these Quests yourself, assign it somebody you know or publish the Quest for somebody else to get it done for you. You can also attach a cash reward that the person finishing Quest can then either payout in cash, a gift card or donate!

Smart RSS reader with content-based recommendation. The main model I am running is “make an embedding and apply classical ML” and I have that completely industrialized. The MiniLM embedding also clusters documents with the greatest of ease, whether you are looking for broad clusters (put Ukraine articles together) or narrow clusters (cluster the 3 articles about the Arsenal game from last week into one.)

I’ve sporadically gotten a fine-tuned transformer model to outperform it but don’t have that industrialized yet but I expect to.

I'm currently creating a lot of private chatbots for people and organizations I follow online. I am scraping their content, from blog posts to articles and videos, and then storing these in vectors. Not for any commercial uses, but to be able to chat with their content. In very many cases this is now replacing Googling for me, if I can't already solve the issue I am having with ChatGPT out of the box.

Using LLMs to help people generate and edit content directly in their notes - https://saga.so/ai

Just released https://www.chesswith.ai today. It's a basic chess app, but it lets you play against hundreds of famous historic/fictional characters.

The in game dialogue is powered by OpenAI's ChatGPT API. This dialogue is always unique and tailored to the events happening on the board, making every game a one-of-a-kind experience.

Hyper niche standardized test prep

Desktop accessibility tools not necessarily for disabled people.