I'm viewing this thread in Lemmy and am unable to find any mention of a link to the source code or a demo, and I can't see the attached media (genetic image icon - is it an animated gif or a video?).
Based on all the comments, I appear to be in the [significant] minority. Would you mind posting a link to your source or demo or image/video?
MTLS is great protection, but the use case must support it. For example, if you want your app to support registration for new accounts or if you have a lot of people you want to have access, that might make mTLS unwieldy to manage.
I host apps behind Traefik reverse proxy, using the d.rymcg.tech framework. It make it easy to protect your apps behind HTTP basic auth, Oauth2, or mTLS(or any combination).
The fist in that image looks very weird to me. When I make a fist and look at it from the same angle and compare that to the image, the pinky in the image is too far towards the middle of the hand and not close enough to the edge, and the thumb extends way more to the right of the arm than mine does. I wonder what this hand looks like when not on a fist, or if it's an AI generated image.
I'm certainly old, but I've been trying for a year or 2 to stop using giant corporation names as verbs. "Google it" became "look it up" or "research it".
Ollama gained traction by being the first easy llama.cpp wrapper, then spent years dodging attribution, misleading users, and pivoting to cloud, all while riding VC money earned on someone else's engine.
He shares that the people behind llama.cpp don't act poorly (at least in those regards). My experience confirms llama.cpp can run just about any gguf while ollama can only run those that have been customized for ollama, and llama.cpp seems faster (no evidence, just anecdotal).
I switched from ollama to llama.cpp and love it. For such an article, it frustrates me that they don't include the common and popular option in the comparison.
I haven't had to adjust or look at my invidious instance configs in a long time, but I do remember that in their docker instructions and I think I configured my container to restart hourly (or maybe I made it every other hour? Daily?). I've had no problems with my invidious instance in a long time, but that may have nothing to do with frequent restarts.
Well written and very thought provoking. I've thought about positive and negative freedom (and other definitions) a lot, but still this article gave me new perspective.
I think Forgejo is in the process of federating via ActivityPub. Codeberg uses Forgejo, but Forgejo is self hostable. I'm looking forward to see how a federated git forge works!
I have aPBS server and my friend in a different geographic region has one. I backup to mine and he backs up to his. Mine syncs my backups to a data so l store in his, and his summer backups to a data store in mine. These are our offsite backups.
To be clear, we're syncing our proxmox VM backups. But Proxmox Backup Server also has a client app, so I also back up my workstation to my PBS and it also syncs to the remote PBS.
It's important to me to use devices and services that are local only, but I could only find such robot mowers that are beyond my skillset to build. I have no interest in building and 3d printing and flashing firmware, etc. I just want to buy a device and use it, without my privacy being sold. I'm willing to pay, but I guess there's not enough market for anyone to build/sell that.
Same with vacuums, by the way. I have a dreametech model that's supported by Valetudo, but the instructions to flash it sounded difficult and risky enough that I just use it as is, with my home map (and whatever other data it gleans) going through Dreametech's servers and being sold to whomever.
Yeah, my thinking was definitely biased to my environment. I selfhost llama.cpp so even if Hivekeep doesn't require significant resources, whatever LLMs it runs will use my hardware.
agents are activated serially per message, not all firing at once, and the persistent memory is exactly what keeps each context small
This looks interesting, especially the persistent memory. I want to try it out but it seems likely to me that multiple simultaneous agents would require significant hardware. Even if they were serially activated, reloading contexts with each switch would take time. I have a pretty beefy GPU and experience significant (almost ridiculous) slowdown when opencode runs 2 subagents simultaneously.
But perhaps the memory storage/lookup keeps contexts very small?
Anyway, I can't find any mention in the repo or docs what the suggested minimum hardware is.
LuisCore is a X, X X for X X at scale: an X for X, X, and X X across X. The X X is luiscore.com, with X at X and X.
I often feel like that's what I'm reading, but I assume that enough people understand it that the trend goes on. Like maybe I should just not read articles about tech any more.
I really like the quote "If you can’t explain it to a six-year-old, you don’t really understand it yourself" (possibly by Feynman). I'd like this to be how the works works, but it would mean that most people don't understand what they're talking about or they're intentionally being pretentious and exclusive. But technical things do get made, so it seems more likely that I just don't understand.
Yes. You can use opencode, the agenetic coding tool, with just about any llm runner or model. But Opencode Go is their cloud-llm suscription plan, with limited/slightly-dated llm models.
Streisand effect