51–60 of 343 posts
Earlier quoted context omitted.
Plus even if Apple is using their own chips for inferencing, they're still driving more demand for training, which Nvidia still has locked down pretty tight.
Apple said they’re using their own silicon for training. Edit: unless I misunderstood and they meant only inference.
IMO this really feels like the Facebook / Twitter integration from early iOS. That only lasted a few years. Apple clearly thinks it needs a dedicated LLM service atm. But still thinks it is only supplemental as they handle a bunch of the core stuff without it. And require explicit user consent to use OpenAI. And Apple clearly views it as a partial commodity since they even said they plan to add others. Tough to bet a…
LLMs are not accurate, they aren't subject matter experts that'll be maybe within 5% error margin.
People will gradually learn and discover anf the cost of keeping a model updated and running won't drastically reduce so we'll most likely see dust settling down.
Though a bit of that is premised on whether it could extract information from google maps.
Earlier quoted context omitted.
Plus even if Apple is using their own chips for inferencing, they're still driving more demand for training, which Nvidia still has locked down pretty tight.
Apple said they’re using their own silicon for training. Edit: unless I misunderstood and they meant only inference.
Earlier quoted context omitted.
i would strongly take the other side of that bet
Nvidia obviously has an enormous, enormous moat but I do think this is one of the areas in which Apple may actually GAF. The rollout of Apple Intelligence is going to make them the biggest provider of "edge" inference on day one. They're not going to be able to ride on optimism in services growth forever.
If you're saying Apple is going to 'take on nvidia' in edge inference, then I don't disagree but I would hardly even count that as taking on nvidia.
Earlier quoted context omitted.
Apple said they’re using their own silicon for training. Edit: unless I misunderstood and they meant only inference.
They trained GPT-4o on Apple Silicon? I find that hard to believe, surely they only mean that some models were trained with Apple Silicon.
I still don't know a single person who wants this crap. I don't want "AI" in my web browser, I don't want it in my email client, I don't want it on my phone, I just don't want it. And it feels like everyone I speak to agrees! So who is this all for?
Earlier quoted context omitted.
i would strongly take the other side of that bet
Personally, I'm taking _both_ sides of that bet. I think Apple is going to make rapid and substantial advancements in on-device AI-specific hardware. I also think nVIDIA is going to continue to dominate the cloud infrastructure space for training foundational models for the foreseeable future, and serving user-facing LLM workloads for a long time as well.
Earlier quoted context omitted.
Didn’t Apple say they’re using their own hardware for serving some of the AI workloads? They dubbed it ‘Private Cloud Compute’. Not sure how much of a vote of confidence it is for Nvidia.
not for gpt4o workloads they aren't going to
I'm sure OpenAI will need to beef up their hardware to handle these requests - even as filtered down as they are - coming from all of the Apple users that will now be prompting calls to ChatGPT.