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:
i am not sure which model he used but the frontier models are better but local ones are catching up. especially since nvidia is pushing local. it comes down to your hardware though. be ause if you fins a higly capable local model, you need to run it. what kind if hardware do you have? do you have an rtx?
It’s for work. I can throw quite a bit of money at it, but only if there’s a point.
If there’s time and budget to play around with, perhaps get a “cheap” 2x R9700 + 128GB RAM system that can run Qwen 3.8 Flash Next and experiment. If it’s useful enough for your use cases, then get big enough hardware that can run this, which is better than QFN. It would also run the unquantized QFN and the next Qwen Flash version.
You could also try them via their APIs or on cloud hardware you rent.
My workplace, a well know NA corporation, has DeepSeek 4.1 Flash deployed on-prem and it’s in active use.