Hacker reverse engineers his Samsung TV and finds on-device AI listening for your dog and baby, watching what you watch, and borrowing your soundbar’s mic if the TV doesn’t have one. Then OpenAI banned him for reverse-engineering it.
Source:
Hacker reverse engineers his Samsung TV and finds on-device AI listening for your dog and baby, watching what you watch, and borrowing your soundbar’s mic if the TV doesn’t have one. Then OpenAI banned him for reverse-engineering it.
Source:
If I’ve got 128GB of RAM but it’s really slow RAM (DDR3), can I run a good model really slow or will it just not work at all?
It’ll be slow but it’ll run.
Though even 128GB isn’t enough for the biggest models. 512 would open up more options and the very biggest need like 2-4TB, totally out of scope for personal use.
You could try a medium-big MoE model (Mixture of Experts) with less than 100b total parameters. Maybe start with something modest like Qwen3.6-35B-A3B at 8bit quants. That’ll leave you with plenty of memory left over for context size.
Hmm… I guess my board supports up to 256GB; would maxing out the RAM make a big difference? Also, I’ve got 2x16 core Opteron and an AMD Vega 56, if you have any advice related to those.
I don’t think you should go bigger because bigger = slower. It might already be too slow to use. Give a smaller model a try first and see how it runs.
try the Strata engine instead of llama.cpp
https://github.com/Niko1221/Strata/blob/main/docs/MODELS.md#pick-by-memory
You should be able to run Qwen 3.8 Flash Next decently