Here the neural network was given examples of how to use the calculator for each question which means it wasn't generating it's own abstractions.
If you wanted to use this to solve other (e.g. programming) problems you would need examples of every step required for almost every problem.
Using neural networks in this way is akin to locality sensitive hashing, instead it should understand what it's lowest level operators do and discover useful combinations of them that can solve new problems.
The idea is to have one site that can brings you everything you check for into one place but also helps you discover great sites you've never seen before.
Just finished this today so Im super keen for any feedback anyone might have.
Odly enough I have the same problem with feed readers I've tried. Even with sites I really like such as Reddit and Hacker News, that's why when you subscribe to a site if it puts out frequent updates (or you choose too) it's posts will show up in a scroll bar in your feed and so won't fill it up.
So it differs from Reddit as Reddit's feed is based made of subreddits that share links creating a unique feed of content while WebArcs's feed is feed of the other feeds of sites you subscribe to.
It differs from an RSS reader in the way we show the content. Most readers such as feedly try to restrict the functionality of the product so people will pay for it and only offer you an easier way to view the sites you already like and so already have a way of accessing.
On WebArcs we try to enable discovery of new feeds you would not view otherwise. This is the hardest thing to get across, I only keep up with hacker news, Reddit, TheMacro, recode and a lot more because I have WebArcs.
It's when you find a new site you wouldn't of kept up with before on WebArcs that you start getting the real value.
tl;dr It's about enableing you to discover new sites you couldn't keep up with otherwise.
Hey I'm actually working on a web app to allow people to keep up with a ton of RSS feeds remotely.
I was thinking since it seems like something you could be interested in it would be great if you check it out and possibly give me some feedback.
I'm the founder of WebArcs (http://webarcs.com) an RSS aggregate for discovering and subscribing to websites. I'm just starting out and I want to see this be the way people surf the web in the future.
I was wondering which demographics I ought to target too too help build a strong user base?
Perhaps via an RNN like in https://huggingface.co/spaces/BlinkDL/RWKV-Gradio-2
Or even just leverage huggingface gradio spaces? (most are Gradio apps that expose APIs https://www.gradio.app/guides/view-api-page)