For the really old stuff, I used to do NetBSD. I'm sure their 32bit x86 support is still top notch.
behohippy
These are amazing. Dell, Lenovo and I think HP made these tiny things and they were so much easier to get than Pi's during the shortage. Plus they're incredibly fast in comparison.
Subscribed. That last episode of AAA was heartbreaking.
Bad article title. This is the "Textbooks are all you need" paper from a few days ago. It's programming focused and I think Python only. For general purpose LLM use, LLaMA is still better.
I hear good things about Traefik. Basically all I need is a reverse proxy that will handle re-writing URLs and websockets and slapping some ssl and auth on it. If something is easier for that, I'm all ears.
Yep, I'm using an RTX2070 for that right now. The LLMs are just executing on CPU.
Do you recommend this email provider? Lots of people looking to get off gmail lately.
Are you running your own mail server? I only ever integrated Spamassassin with postfix.
Stable Diffusion (Stability AI version), text-generation-webui (WizardLM), a text embedder service with Spacy, Bert and a bunch of sentence-transformer models, PiHole, Octoprint, Elasticsearch/Kibana for my IoT stuff, Jellyfin, Sonarr, FTB Minecraft (customized pack), a few personal apps I wrote myself (todo lists), SMB file shares, qBittorrent and Transmission (one dedicated to Sonarr)... Probably a ton of other stuff I'm forgetting.
Yup, mostly running pretrained models for text embedding and some generative stuff. No real fine tuning.
Yup, typically we get into it after upgrading an older PC or something and instead of selling the parts, just turn it into a server. You can also find all sorts of cheap/good stuff on ebay from office off-lease.
The advancements in this space have moved so fast, it's hard to extract a predictive model on where we'll end up and how fast it'll get there.
Meta releasing LLaMA produced a ton of innovation from open source that showed you could run models that were nearly the same level as ChatGPT with less parameters, on smaller and smaller hardware. At the same time, almost every large company you can think of has prioritized integrating generative AI as a high strategic priority with blank cheque budgets. Whole industries (also deeply funded) are popping up around solving the context window memory deficiencies, prompt stuffing for better steerability, better summarization and embedding of your personal or corporate data.
We're going to see LLM tech everywhere in everything, even if it makes no sense and becomes annoying. After a few years, maybe it'll seem normal to have a conversation with your shoes?