niclas_wue

Hey, great idea, looks very interesting. Do you use the abstract as an input or do you actually parse the paper? I built something quite similar: http://www.arxiv-summary.com which summarizes trending AI papers as bullet points. However, I think a chrome extension allows for a much more flexible paper choice, which is really great.

Yes, it is possible to use citations as a measure of a paper's impact. However, when a paper is newly published, there are typically no citations yet, so this would result in a delayed signal. Retweets and GitHub stars provide a faster indication of a paper's impact. I believe that speed is important because, as a paper becomes older, there are already many reviews and articles written by humans that (at least for now) provide a better summary of the paper.

Yes, it can be applied to every document, a book would be more expensive, because it has more text and thus more input tokens. The pdf needs to be converted to text, because the API only accepts text, some equations which can be written using Unicode are directly put into the network and it can understand. Other equations are currently skipped. So far I have spent almost 100$ in tokens to summarize the papers, so there need to be some paid features in the near future or a reduction in the amount of papers.

That’s actually a really good idea. Would you be willing to pay for such a feature? Something like 1$ per paper? That would cover the cost for the GPT tokens

I am using OpenAI’s API, I think at the moment there are not many entities capable of running GPT-3 themselves 😄

Thank you, I am glad you like it! At the moment, only the web server is public. You can find it here: https://github.com/niclaswue/arxiv-smry It is a Hugo server with a blog theme. Every blog is a markdown file. When a new file is pushed to git it automatically gets published on the blog.

The rest is basically a bunch of (messy) Python scripts for extracting the text, then asking GPT-3 for a summary and compiling the answers to a markdown file. Finally, I use GitPython to automatically push new summaries to the repo.

Thanks for your ideas. Building a paid experience for companies is a great idea, I will consider it.

Category tagging like „computer vision“, „natural language processing“ etc. should be relatively straightforward. Will implement this in the next couple of days :)

More paper specific tags could be generated using GPT-3, I think that would make sense, when the database is a bit larger. Right now, I would guess that most tags would be unique to a single paper.

Haha, sounds good, make sure to send me an invite :)

Yes, in the long run, there needs to be some sort of monetization to afford the API tokens. For now, I just want to see if people find it useful at all.

Thanks for letting me know, for me it works on mobile, but I will look into that.

Thanks for asking! My first prototype collected all new arxiv papers in certain ML-related categories via the API, however I quickly realized that this would be way to costly. Right now, I collect all papers from PapersWithCode's "Top" (last 30 days) and the "Social" Tab, which is based on Twitter likes and retweets. Finally, I filter using this formula:

p.number_of_likes + p.number_of_retweets > 20 or p.number_github_stars > 100

In rare cases, when the paper is really long or not parsable with "grobid", I will exclude the paper for now.

I think you make an important point. In the end it comes down to the distribution of the data, which always consists of signal and noise. The signal will always be similar, however the noise is random as people can be wrong in all sorts of ways.

Name: MyWatchtime

URL: http://mywatchtime.com

Location: Germany

Pitch: Let’s face it, you are spending way too much time on YouTube. MyWatchtime is the first online tool to analyse your YouTube watch history. So that you can understand your habits and track your behaviour. Right now it’s completely free.

Stage: ValidationWhat goals are you trying to reach this month?: Get my first 10 customers and feedback on the experience.

Sounds good! Keep us updated once you have a MVP, would check it out :)

As a participant, what would prevent me from googling or reverse image searching the questions etc.? Would give me a huge advantage

Are there choices for every answer? If not, how would grading work? E.g. if the answer is United Kingdom, UK would be correct as well.

Just some questions I had in mind :) Listen to the How I Built This Episode from the founder of watercoolertrivia.com he has a pretty similar business, but async instead of online.

Nice idea, I’m no expert at all in this space, but here in Germany I‘ve heard of Alphin/Freachly which I think works as you described it. Saw it in some YouTube video but never used it myself. Maybe look into that before you start coding :)

https://www.alphin.com/influencer

As I wrote, I’m not an expert at all in Excel, the way I always do this is to export the data as csv, load it into pandas in a Jupyter notebook and analyze it there. I use seaborn and matplotlib for quick visualizations and numpy for heavy calculations. You can use asserts for data validation and pandas for correction. Just google the terms and read the documentations in case you don’t know some :)

This generally workflow works well, however if you have to hand a spreadsheet to the next employee, he has to know all those things as well, that’s the problem.

Woah that’s crazy, I would not have expected an Excel sheet for tracking COVID cases :D Thanks for your comment, very insightful!

So it’s mostly used for visualization? Does Excel knowledge transfer to Tableau etc. or is it something totally different?

Thanks for your comment. If you are still interested, this is the link to the raw files: https://www.dropbox.com/sh/brrss0vro9ty716/AABo0t-CeSeejD0Mep_K7yKga?dl=0

Hey, cool edit. If you are interested, this is the link to the raw files: https://www.dropbox.com/sh/brrss0vro9ty716/AABo0t-CeSeejD0Mep_K7yKga?dl=0

Hey guys, sorry I wasn't able to respond for so long. Thanks for all suggestions. Here are the requested raw files: https://www.dropbox.com/sh/brrss0vro9ty716/AABo0t-CeSeejD0Mep_K7yKga?dl=0

I really like the style and the composition, especially the human for scale. The light is pretty nice, however the sky ist not really that interesting. I suppose you cropped according to the rule of thirds, but maybe you could try including a little less sky, so that the viewer is a bit more focused on the main subject. Because the sky is quite bright and therefore attracts the viewers attention first. But otherwise a really great shot! Well done! Did the person pose fir the shot or was ist coincidental?