My hope is that this gentle nuding towards "come on, you've had 15 minutes, now just wait another 45, please?" is enough of a hurdle. I think it's a moderation tool.
372 karma · joined July 3, 2017
My hope is that this gentle nuding towards "come on, you've had 15 minutes, now just wait another 45, please?" is enough of a hurdle. I think it's a moderation tool.
"Drop the idea that drinking alcohol like shots or beer or whatever is somehow ignoble and worthy of scorn. Recognize it's just a fun way to kill some time (and brain cells).
Internalized that? Cool.
Now find a comfy place to sit or lie down and binge that shit. For hours. Do it for as long as it brings you joy. Had your fill? Cool."
The key is moderation.
I'm not against drinking and I'm not against using Youtube, Reddit, Instagram, Hacker News. But I get sucked into it way more that I want, and this is my way of having a nice old lady ask "haven't you had enough, honey?".
Damn, I've spent days on Youtube, not even on "silly" stuff. There's a limitless supply of educational videos, PBS Space Time, Stumpy Nubs, Phil Salmony, DIY Perks.... But I still have a limited amount of hours in a day. Also I have shared responsibility of several humans and animals in this house, I can't just sit idly behind a screen all day (except for the eight hours I get paid to do it).
Most apps I've tried (and browsers too) can be blocked just fine via DNS. The gli.net interface allows "Override DNS Settings of All Clients" and "DNS Rebinding Attack Protection". This way, the router itself is the only resolver actually reachable. Even if I try some manual `dig google.com @1.1.1.1`, I still get the routers result.
The only thing it can't block is DNS over Https. I think that's by design, it seems it's impossible to block that.
But it actually has an advantage: I can plug a small lamp into it. After 14 minutes, the plug switches on and off every 2 seconds, indicating that the time runs out, adding a little drama.
I've used his idea and make a home assistant automation that temporarily disables adguard home to do the same thing.
I can't use ublock origin for that because I want all devices in my home to take advantage of this, so I've reimplemented this with Home Assistant, Adguard Home and the Adguard Home integration into Home Assistant.
When I set the context size to 2048 (openwebui's default), the inference is almost twice as fast as when I set it to 4096. I can't set the conext size any higher because my GPU only has 12GB of RAM and ollama crashes for larger context sizes.
Still, I find that thoroughly odd. Using the larger conetext size (4096), the GPU usage is only 50% as seen in nvtop. I have no idea why.
While my first thought was - admittedly - ugh, yet another LLM/AI code assistant, I'm so glad I tried it. It's just... amazing. The "act" mode is a game changer for me. I've heard Cursor does it similarly, but I haven't tested that yet.
I have however used Continue.dev for quite a while, and even though continue is great, Cline is even better. I didn't know what I was missing.
So, I'd encourage everyone to at least try it.
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Just a question to Nick: what's the deal with the Roo fork?
My main take away was that even simple basics can produce astonishing results, I this case if they're just scaled large enough. That incredibly complex and useful emergent behavior can result from what seems like conways-game-of-life like principles.
Although I'm 100% sure there are no loops, I haven't changed the actual cable layout in ages.
Often because the cheap devices were either all I could afford or because I've even gotten them for free or basically free, like on flea markets.
Every couple of weeks, the entire wired network goes down. Not even pinging adresses works. The d links ports leds are all flashing (perfectly in sync!) until I power cycle it. Then everything goes back to normal.
I have no idea what happens, and I should probably replace the d link soon.
On the other hand, 10 e9 = 10 * 10^9.
Then gravitational tidal forces aren't strictly a uniform compression, on the contrary. Since gravity increases by 1/r^2, the part of the water drop that's closest to the black hole would experience largest force. That tears everything apart, so the water would be more dispersed instead of compressed. While I haven't done the math (and don't know if I even still could), I'd assume that gravity would quickly overcome Van Der Waals forces that holds the water molecules together, so it'd probably closer to water vapour than liquid.
And lastly, once it finally reaches the singularity, all bets are off. As far as I'm aware we have no idea what happens to matter in a singularity apart from contributing to its mass.
I'm blown away how good this works! I searched for the query just like you said and it really found exactly the relevant section of the video. Very impressive!
You're right, the query seems to be very sensitive to the exact phrasing. Searching for "heat sink thermal calculation" results in nine videos, (the wanted one on fifth place at least), while your query seems more targeted. "calculate heat sink power dissipation" works reasonably well too.
So again - wow. This is really great and exactly what I've been trying to build for myself too.
One really useful feature for me would be inclusion/exclusion of channels in the search results. For this example, when I'm specifically looking for calculations, I can probably skip channels like LTT from the search results.
Thanks for this amazing tool!
My test example for such a soltion would be: "does it find the chapter about thermal calculations in a video about electronics": https://youtu.be/8xX2SVcItOA?feature=shared&t=758
How do I add a video? I'd love to test your solution with this video.
Thanks for making the source available too! I've been trying to build something similar with jupyter notebooks, but I keep getting stuck at this "hidden gem" problem.
I think I've found a (minor) bug, there seems to be an inaccuracy with the time stamps. I assume you're taking the chapter start and end times from the video themselves, but they don't align with the summary in this video:
https://www.videogist.co/videos/eevblog-102-diy-constant-cur...
For example, chapter 5, Heat Sink and Power Dissipation starts at 5:18 in your summary, but in the actual video it starts at 12:15.
EDIT: I'm just now seeing that your summary only has 7 chapters, but the YouTube video is segmented into 13 chapters, so it appears you're not using them from the video after all. Are you doing the segmenting with the LLM as well? How do you get timestamps from that? EDIT END
Anyway, thanks for this fantastic product, I was about to build something similar, but with a different focus:
Assume I've already seen a video and I want to look up a detail from that video, say how to do thermal calculations like in the example video, but I remember neither the video name nor the time stamp. I'm trying to build an app that generates embeddings for chunks / chapters of videos which I can then search semantically.
Do you have something similar planned? Because that's something I'd pay good money for.
Also, would you mind sharing a little bit about the tech stack? I'm assuming you're using yt-dlp to download videos with chapters and running whisper for a transcript, then something like gpt-3.5-turbo for summaries? Because that's how I'm doing it right now :D
Even stranger, now that my account is created, the VPN seems to be no longer necessary. I can just login with e-mail and the token they send me each time.