In the last week, we’ve had no less than three different pieces asking whether the massive proliferation of data centers is a massive bubble, and though they, at times, seem to take the default position of AI’s inevitable value, they’ve begun to sour on the idea that
As always with Zitron, grab a beverage before settling in.
There are already large local models. It’s a question of having the hardware, which has historically gotten more powerful with each generation. I don’t think it’s going to be phones for quite some time, but on desktop, absolutely.
For business use, laptops without powerful graphics cards have been the norm for quite some time. Do you see businesses deciding to change to desktops to accommodate the power for local models? I think it’s pretty optimistic to think that laptops are going to be that powerful in the next 5 years. The advancement in chip capability has dramatically slowed, and to put them in laptops they’d need to be incredibly more power efficient as well.
For the security tradeoff of sensitive data not heading to the cloud for processing? Not all businesses, but many would definitely see value in it. We’re also discussing this as though the options are binary … models could also be hosted on company servers that employees VPN into.
Apple is doing it, AMD is doing it, phones are doing it.
GPUs with dedicated VRAM are an inefficient way of doing inference. They’ve been great for research purposes, into what type of NPU may be the best one, but that’s been answered already for LLMs. Current step is, achieving mass production.
There are already large local models. It’s a question of having the hardware, which has historically gotten more powerful with each generation. I don’t think it’s going to be phones for quite some time, but on desktop, absolutely.
For business use, laptops without powerful graphics cards have been the norm for quite some time. Do you see businesses deciding to change to desktops to accommodate the power for local models? I think it’s pretty optimistic to think that laptops are going to be that powerful in the next 5 years. The advancement in chip capability has dramatically slowed, and to put them in laptops they’d need to be incredibly more power efficient as well.
For the security tradeoff of sensitive data not heading to the cloud for processing? Not all businesses, but many would definitely see value in it. We’re also discussing this as though the options are binary … models could also be hosted on company servers that employees VPN into.
Keywords: NPU, unified RAM
Apple is doing it, AMD is doing it, phones are doing it.
GPUs with dedicated VRAM are an inefficient way of doing inference. They’ve been great for research purposes, into what type of NPU may be the best one, but that’s been answered already for LLMs. Current step is, achieving mass production.
5 years sounds realistic, unless WW3.