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.
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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.
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That’s a good question and it’s hard to say for sure. There’ve been some advancements this year in offloading, using both VRAM and system RAM together. With MoE models and predictive loading you can get pretty good results that way…sometimes. I’ve never tried it myself, though I really should because my 24GB GPU is a serious bottleneck.
You could also think about getting a 512GB Mac Studio (coming soon). Not as fast as a GPU, but maybe faster than a GPU/DDR5 mix? And definitely cheaper per GB.
I realize now that the truly biggest models need way more than $40k of hardware. The biggest Qwen3.8 is 2.4 TRILLION parameters. Yikes.