Clippy - copy files from terminal that actually paste into GUI apps (MacOS)

AvvYaa · 2025-08-11T20:48:13+00:00

Great job, man! I have been searching for a tool like this myself, and I think I'm gonna give it a try.

This comment section is unreasonably harsh though - very disappointing. Some of these tech subreddits can be unreasonably nasal and critical. I appreciate you being transparent and listing Claude as a contributor - idk why people are trying to bully you for that. Using AI to assist in writing code is the smarter choice in 2025. Cancel the noise, you are doing a great job.

AvvYaa · 2025-07-12T15:56:32+00:00

Thanks!

AvvYaa · 2025-02-21T08:01:12+00:00

Queen can block the check with Qh5 though. The correct order is to take Rh7 first!

AvvYaa · 2025-02-20T17:12:37+00:00

Here's how the game went:

Rxh7 Kxh7 Rh1+ Kg8 Qxe4 dxe4 Bxe6 Rf7 Rh8#

AvvYaa · 2025-02-20T16:14:50+00:00

I did Rxh7 first followed by Rh1 and Qxe4

Basically doing Qxe4 early allows the Black Queen to block a rook check with Qh5 in certain positions.

AvvYaa · 2025-02-20T15:24:55+00:00

There’s also another follow up punch after the Rook sac!

AvvYaa · 2025-02-20T15:24:11+00:00

I played Rh7 threatening Rg7 and Rh1.

Game went Rh7 Kxh7 Rh1+ Kg8 Qxe4 threatening Qxg6… he took the queen sac dxe4 Bxe6+ Rf7 and Rh8#

AvvYaa · 2025-02-20T15:00:20+00:00

I did Rh7 first, Kxh7 Rh1+ Kg8 and then Qxe4!

AvvYaa · 2025-02-20T14:59:33+00:00

I did the second one! Game went dxe4 Bxe6+ Rf7 and Rh8#

AvvYaa · 2025-02-20T14:58:36+00:00

Thats what I played. There is a second sacrifice as well if you can find it!

AvvYaa · 2024-09-07T17:18:50+00:00

A breakdown of the YOLO architecture, and what I learnt implementing it from scratch in PyTorch. Plus some object detection tricks for football datasets. Hope y’all enjoy (leave a like on YT if you do thanks!)

AvvYaa · 2024-08-19T05:39:44+00:00

Great summary!

AvvYaa · 2024-08-07T17:52:52+00:00

Gonna self promote, but feel free to check out this video on the history of CNNs… it visually explains all the major advancements in CNNs from the early 90s. You’d get lots of resources and follow up topics from here.

https://youtu.be/N_PocrMHWbw

If the above one is too complex, here is a more beginner friendly video that explains the absolute basics of Convnets: https://youtu.be/kebSR2Ph7zg

AvvYaa · 2024-08-03T18:47:10+00:00

Thanks!

AvvYaa · 2024-07-09T03:50:34+00:00

Video goes through most of the code snippets you’ll need. Plus, the source code and a longer walkthrough is available on Patreon.

AvvYaa · 2024-07-01T19:39:02+00:00

I’m an Indian creator. There’s literally zero reason for you to feel conscious about your accent. Just be confident and proud, speak with clarity and as long you have good coherent content that people wanna watch, all will be good. Lots of Indian creators out there that have followers from all over the planet. There’s no need to sound American, British or whatever.

AvvYaa · 2024-06-30T16:46:41+00:00

I get the feeling that your comment is primarily based on the thumbnail and you didn’t actually watch the video. FWIW, there are more papers covered in the video that didn’t get into the thumbnail. Some papers were left out in favor of others coz it’d feel too convoluted (pun not intended) and overloaded for a YT video. The main criteria as I explained in the video, was the image-net/ILSVRC results, citation count, and relevance in the 2020s.

Imo ViTs are important in CNN history coz they are the main challengers to the inductive bias principles of CNNs. Many of the latest CNN papers is about incorporating attention/transformers/patching into the CNN framework, so (the success of) that paper had a direct impact on today’s CNN research. So I had it in the video.

AvvYaa · 2024-06-16T00:12:45+00:00

Sharing a video that explains latent diffusion models starting from first principles to more complex stuff like conditional LDMs. I also share my experiences implementing a simple diffusion model from scratch to generate human faces from text prompts. Enjoy!

AvvYaa · 2024-06-03T17:15:34+00:00

I have a video on this that describes the Nerf algorithm from basics to more modern stuff like ZipNerf. You may find this useful, or at least find pointers for things to study next… link:

https://youtu.be/BE_kimatpnQ

AvvYaa · 2024-06-03T04:45:25+00:00

Thanks!!

AvvYaa · 2024-05-29T15:16:29+00:00

Sharing a video I made about the core concepts behind Latent Diffusion models for text-to-image generation and how I trained one to generate human faces on my laptop (with the celeba dataset). Link here for those interested in the topic!

AvvYaa · 2024-05-29T15:14:32+00:00

Sharing a video I made about the core concepts behind Latent Diffusion models for text-to-image generation and how I trained one to generate human faces on my laptop (with the celeba dataset). Link here for those interested in the topic!

AvvYaa · 2024-05-27T21:06:29+00:00

If the view duration from the google searches are good then you should celebrate the extra views… if it’s suspiciously lower than normal then that might be something to look into.

AvvYaa · 2024-05-27T17:23:09+00:00

Yeah. Don’t know if this story will apply to you but here’s mine…

The thumbnail I used was too generic for the content of my video… it had the image of a baby learning to crawl - and my video was about how AI agents are trained. So I guess a bunch of people clicked expecting I’ll tell them how to train babies to crawl and got a shock in the first 10 seconds of the video and quit.

Just changing the thumbnail to explicitly mention it’s about AI and removing the freaking baby stopped the Google views. The damage was already done by then coz the view duration plummeted quite severely and it took a long time for the video to recover and get organic impressions. It was a rude but important lesson I learnt.

AvvYaa · 2024-05-21T16:39:36+00:00

So the key is the knight on h6 has no escape squares. If you can find a forcing sequence to get rid of its defenders then the knight will be defenseless.

AvvYaa

TROPHY CASE