Apple collaborates with Nvidia to research 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 happens", in my experience. It's reasonably possible that this could portend additional future outcomes, such as official support for Nvidia-based eGPUs, Apple's licensing of/support for CUDA, Mac Pros with Nvidia GPUs, etc.

Convinced that Apple has shot themselves in the foot / tied their hands behind their back / insert analogy here, re: privacy AI.

Interesting to see how it plays out. Meta and Google have much more permissive privacy policies / stances, which means Meta + Google models are going to get much better faster.

Apple does potentially have an edge with their Mx series of chips re: inference flops. I bet they're hoping that the model quality vs. model size curve continues dropping such that they can run sufficiently powerful LLMs on-device.

We'll see.

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 stuff until there is more market penetration of the higher RAM capacities. Apple could perhaps monetarily incentivise them to make up for it. But I think they are just going to heavily have to lean on cloud for everything.

Personal speculation here: https://news.ycombinator.com/item?id=42456965

a) Apple already reaches out to ChatGPT (and soon to be others) for the full LLM experience. And there isn’t much benefit to be had from building their own competitor.

b) Privacy is essential if you want to an LLM to interact with you with private information. You can’t just upload unencrypted photos, messages, health data etc to the cloud where it will be accessible by any government with a search warrant. And so it does makes sense to keep it all private and encrypted on device or used in private but restricted compute.

c) Hype is very much coming out of the AI space and so I don’t see the market punishing Apple for not doing more. If anything they should’ve done nothing rather than released the technically impressive but largely useless Apple Intelligence product.