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Apple collaborates with Nvidia to research faster LLM performance
- gibsonf1 2y agoHmm, is faster hallucination better than slower hallucination?
- henry2023 2y agoMaybe if you hallucinate fast enough no one will notice?
- dhosek 2y agoI was initially reading it as LLVM performance and thought, “how cool” and then I realized the V was missing and stopped caring.
- ben_w 2y agoWhen the answers can be checked by another program and best-of-n results get better with increasing n, yes. I think TDD code development is this, at least in principle.
- SiddanthEmani 2y agoWith competition on the rise, it’ll be a race to provide faster inference speeds for general queries
- DannyBee 2y agoIs there somebody not researching faster llm performance?
- stefan_ 2y agoDoes Intel qualify? They seem busy making GPUs for midrange insignificant gaming builds, while all their AI offerings are hopeless.
- deergomoo 2y agoAs someone who owns an insignificant midrange gaming build and has been irritated at the inflation of GPU prices with crypto and now genAI, I’m glad someone is.
- init2null 2y agoNot 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.
- deleted 2y ago[deleted]
- rowanG077 2y agoHow is it insignificant. Intel GPUs are the most exciting thing that has happened in GPUs the last 5-10 years imo.
- UncleOxidant 2y agoBut Apple seems to have gone all in on their own GPU/NPUs, why would they collaborate with Nvidia on this?
- deleted 2y ago[deleted]
- comboy 2y agopatents?
- CharlesW 2y agoPersonal speculation here: https://news.ycombinator.com/item?id=42456965 https://news.ycombinator.com/item?id=42456965
- threeseed 2y agoApple inference is on their own GPU. Apple training is on the cloud with Nvidia. There are plenty of use cases e.g. Apple Maps, News etc which are public and don’t need their Private Compute Cloud.
- username4567 2y agoComplete speculation but could be that Apple supports these operators on their GPUs and they need end-user models optimized to use them. Apple makes their money on consumer devices and need them to be performant for inference on the edge. Getting NVIDIA to integrate the operators may result in more models optimized for operators Apple's devices can leverage to stay ahead of other edge GPUs.
- brotchie 2y agoConvinced 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.
- cma 2y agoApple 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.
- threeseed 2y agoApple Intelligence is supported on any M1 Mac: https://www.apple.com/apple-intelligence 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.
- cma 2y agoFit in 8GB while running browsers and other apps that would want AI? Only tiny models that also work on phones.
- threeseed 2y agoa) 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.
- treprinum 2y agoI have an idea - how about Apple letting Mac users use Nvidia cards/chips again?
- n144q 2y agoI always thought they haven't talked to each other for years.