Companies are going all-in on artificial intelligence right now, investing millions or even billions into the area while slapping the AI initialism on their products, even when...
Companies are going all-in on artificial intelligence right now, investing millions or even billions into the area while slapping the AI initialism on their products, even when doing so seems strange and pointless.
Heavy investment and increasingly powerful hardware tend to mean more expensive products. To discover if people would be willing to pay extra for hardware with AI capabilities, the question was asked on the TechPowerUp forums.
The results show that over 22,000 people, a massive 84% of the overall vote, said no, they would not pay more. More than 2,200 participants said they didn't know, while just under 2,000 voters said yes.
Depends on what kind of AI enhancement. If it's just more things nobody needs and solves no problem, it's a no brainer.
But for computer graphics for example, DLSS is a feature people do appreciate, because it makes sense to apply AI there.
Who doesn't want faster and perhaps better graphics by using AI rather than brute forcing it, which also saves on electricity costs.
But that isn't the kind of things most people on a survey would even think of since the benefit is readily apparent and doesn't even need to be explicitly sold as "AI". They're most likely thinking of the kind of products where the manufacturer put an "AI powered" sticker on it because their stakeholders told them it would increase their sales, or it allowed them to overstate the value of a product.
Of course people are going to reject white collar scams if they think that's what "AI enhanced" means.
If legitimate use cases with clear advantages are produced, it will speak for itself and I don't think people would be opposed.
But obviously, there are a lot more companies that want to ride the AI wave than there are legitimate uses cases, so there will be quite some snake oil being sold.
well, i think a lot of these cpus come with a dedicated npu, idk if it would be more efficient than the tensor cores on an nvidia gpu for example though
edit: whatever npu they put in does have the advantage of being able to access your full cpu ram though, so I could see it might be kinda useful for things other than custom zoom background effects
But isn't ram slower then a GPU's vram? Last year people were complaining that suddenly local models were very slow on the same GPU, and it was found out it's because a new nvidia driver automatically turned on a setting of letting the GPU dump everything on the ram if it filled up, which made people trying to run bigger models very annoyed since a crash would be preferable to try again with lower settings than the increased generation time a regular RAM added.
Ram is slower than GPU VRAM, but that extreme slowdown is due to the bottleneck of the pcie bus that the data has to go through to get to the GPU.
