For the really old stuff, I used to do NetBSD. I’m sure their 32bit x86 support is still top notch.
Gamer, rider, dev. Interested in anything AI.
For the really old stuff, I used to do NetBSD. I’m sure their 32bit x86 support is still top notch.
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.
Yep, I’m using an RTX2070 for that right now. The LLMs are just executing on CPU.
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.
The nest is really high up, had to take the shot without looking. I got a few but this was the best one.
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.
I hate these filthy neutrals…
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?