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But Apple seems to have gone all in on their own GPU/NPUs, why would they collaborate with Nvidia on this?
There are plenty of use cases e.g. Apple Maps, News etc which are public and don’t need their Private Compute Cloud.
But Apple seems to have gone all in on their own GPU/NPUs, why would they collaborate with Nvidia on this?
Is there somebody not researching faster llm performance?
> Is there somebody not researching faster llm performance? The surprising bit is less about what they're working on and more about the collaboration itself, including the mutual and coordinated co-marketing/PR. Apple and Nvidia haven't had a business relationship in over a decade, ever since Apple stopped using Nvidia GPUs in Macs. This sort of re-engagement and subsequent promotion isn't something that "just happen…
So this isn't just about Faster LLM performance. This could possibly opens up a whole new world for Mac ecosystem with CUDA.
I have an idea - how about Apple letting Mac users use Nvidia cards/chips again?
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Does Intel qualify? They seem busy making GPUs for midrange insignificant gaming builds, while all their AI offerings are hopeless.
How is it insignificant. Intel GPUs are the most exciting thing that has happened in GPUs the last 5-10 years imo.
Most people would say H100 is easily more exciting than all released Intel GPUs combined.
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Does Intel qualify? They seem busy making GPUs for midrange insignificant gaming builds, while all their AI offerings are hopeless.
Not everyone is willing to pay for 4K, 120 Hz, and quality raytracing. There is a market for less than premium experiences. I wanted some marginal CUDA for Blender, so I got a 3060. This experience is anything but insignificant to me.
Is there somebody not researching faster llm performance?
Does Intel qualify? They seem busy making GPUs for midrange insignificant gaming builds, while all their AI offerings are hopeless.
https://www.tomshardware.com/pc-components/gpus/discrete-gpu...
Looks like their latest GPU is selling out. Hope they actually move the market a little bit and iterate on this.
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Apple has a huge legacy burden of defaulting laptops to 2010 levels of memory capacity at 8GB all the way up to mid 2024. All the great AI inference stuff in the M-series is wasted due to that until you get ~80% penetration of the new 16GB min spec. If they get compelling local inference throughout the OS it may help them drive adoption of new models faster, but App devs won't have incentive to integrate local AI stu…
Apple Intelligence is supported on any M1 Mac: https://www.apple.com/apple-intelligence And not sure there are many use cases for running mid-sized models locally. Smaller models fit in 8GB and work fine for action handling, tagging, classification etc. And for text/image generation you just get such a better user experience using a cloud hosted model.