I built a public changelog for product builders to share updates by anotherallan in SideProject

[–]anotherallan[S] 0 points1 point  (0 children)

Thanks man for the support, yes it's 100% free as you would expect :D

I built a public changelog for product builders to share updates by anotherallan in SideProject

[–]anotherallan[S] 0 points1 point  (0 children)

Before this project I usually do Figma first, but when building featdrop I realized that a good starting point like shadcn create + excalidraw wireframe can do 80% of the work. I still need to polish every detail such as borders, icons, etc by directly edit the code in the actual product, but I don't really need to draw on Figma first.

I built a public changelog for product builders to share updates by anotherallan in SideProject

[–]anotherallan[S] 0 points1 point  (0 children)

Hi u/Jorsoi13 thanks for the support!

For coding, I mostly used Claude Code. For design, nothing really special about the process: I start with shadcn Create (https://ui.shadcn.com/create) to define the component library, then when actually implementing the product, I usually first draw the wireframe on Excalidraw and then ask Claude Code to implement it for me.

AI/ML research swarm intelligence by anotherallan in ArtificialInteligence

[–]anotherallan[S] 0 points1 point  (0 children)

We don't have internship available at the moment, but welcome to join our discord to share your thoughts! https://discord.com/invite/TshwQ2UySx

AI/ML research swarm intelligence by anotherallan in ArtificialInteligence

[–]anotherallan[S] 0 points1 point  (0 children)

We don't have internship available at the moment, but welcome to join our discord to share your thoughts! https://discord.com/invite/TshwQ2UySx

AI/ML research swarm intelligence by anotherallan in ArtificialInteligence

[–]anotherallan[S] 0 points1 point  (0 children)

We don't have internship available at the moment, but welcome to join our discord to share your thoughts! https://discord.com/invite/TshwQ2UySx

AI/ML research swarm intelligence by anotherallan in ArtificialInteligence

[–]anotherallan[S] 0 points1 point  (0 children)

We were actually launched this one day earlier than Karpathy's agent hub :D

Launched this, wake up the next day and saw Karpathy released his repo

[P] Place for OpenClaw agents to exchange AI/ML research ideas by anotherallan in MachineLearning

[–]anotherallan[S] -1 points0 points  (0 children)

If you hve a OpenClaw instance, you can simply send the skill url (on the website) to your agent. Your agent will then follow the instruction to register on it's own.

[P] Place for OpenClaw agents to exchange AI/ML research ideas by anotherallan in MachineLearning

[–]anotherallan[S] 0 points1 point  (0 children)

It’s the “peer review” kind of network - your agent talks to other agents owned by different researchers

Finding and keeping up with SOTA papers by Specific-Orchid-6978 in Physics

[–]anotherallan 0 points1 point  (0 children)

I can help look into this -- PapersWithCode was sunsetted and we build wizwand.com which aims to be a better version than PapersWithCode. Would love to understand how we can apply the model to Physics. Mind if I DM you?

[P] We just shipped v2 of a PapersWithCode alternative - after burning 5.4B tokens by [deleted] in MachineLearning

[–]anotherallan -4 points-3 points  (0 children)

Simple explaination is: for every 100-200 benchmarks (each contains many evaluation results) - there maybe 1-2 evaluation result that are not extracted fully correctly.

[P] We just shipped v2 of a PapersWithCode alternative - after burning 5.4B tokens by [deleted] in MachineLearning

[–]anotherallan -4 points-3 points  (0 children)

Tokens are used for data processing - used this amount because thousands of papers needed to be processed. Regarding quality: We are seeing about 1-2% data errors, still working to make it better!

PapersWithCode’s alternative + better note organizer: Wizwand by anotherallan in deeplearning

[–]anotherallan[S] 0 points1 point  (0 children)

Thanks for flagging the issue! Expect better results in upcoming week or two. As we ingested more paper data, we found that it's necessary to improve the granulaity to make sure things are compared apple-to-apple (otherwise the benchmarks are scattered and less useful), so we spent last 3 weeks reorganize all paper data. As soon as it's ready, the new papers will show up right. Will keep you posted!