They went with several open weight models. Presumably they did that because they wanted their research to be reproducible (once the 512 GB M5 Ultra actually hits the market). Using say a Gemini model they have access to only due to their partnership with Google would not be as useful for people to understand what Apple did.
Apple has too many arbitrary, pointless grudges for Ternus to take them all seriously.
Google partnership for Apple Intelligence, Meta partnership for local models, and allegedly NVLink Fusion support for M8 GPUs. Maybe the White House told him that it's time to start burying hatchets. I don't get the impression that Apple's prior AI strategy under Cook made any real progress.
Not pointless, all of that led to Apple Silicon, and you seem to be ignoring the fact that it’s not costing Apple any money. None of their hookups. This so-called cooperation is costing Apple a dime. But it is costing the other side billions of dollars.
Smile, the models are getting smaller and better, every generation of Apple Silicon is getting better in the opposite direction. The only problem is the cost of memory and that is within the design engineering ability in-house it is also within their financial capacity, so if I’m John or Tim, I too would wake up with a smile because I can fix the one thing that’s giving us trouble memory because we have the talent and the money to fix it in the next four years.
Apple Silicon copied AMD's mistake. RDNA and Apple Silicon are both the slowest GPU architecture for AI because they spent 6 years optimizing raster performance over compute. Now there's 4 generations of Apple Silicon Macs that rely on compute shaders for any kind of efficient inference. Even the M5 GPU is less programmable than Nvidia's ARM GPUs from 2017.
ARM datacenters were a trillion-dollar market that Apple made ~$0 off of. The Mac Pro could have fit that niche, but Tim Cook chose to depreciate it instead of letting the PCIe connectors be used with Nvidia cards. He cut off Apple's nose to spite Nvidia's face. It's nonsense, especially since they're crawling back to Nvidia to license their interconnect, in tacit recognition that it wasn't a real grudge in the first place. My guess is that Ternus doesn't have Tim's money allergy, maybe at the White House's request. In any case, the grudge is over, and Apple forfeit ARM HPC altogether.
> because I can fix the one thing that’s giving us trouble memory because we have the talent and the money to fix it in the next four years.
By all means, continue. Which X account or YouTube channel convinced you that Apple could replace SK Hynix in 4 years?
They went with several open weight models. Presumably they did that because they wanted their research to be reproducible (once the 512 GB M5 Ultra actually hits the market). Using say a Gemini model they have access to only due to their partnership with Google would not be as useful for people to understand what Apple did.
Apple has too many arbitrary, pointless grudges for Ternus to take them all seriously.
Google partnership for Apple Intelligence, Meta partnership for local models, and allegedly NVLink Fusion support for M8 GPUs. Maybe the White House told him that it's time to start burying hatchets. I don't get the impression that Apple's prior AI strategy under Cook made any real progress.
Not pointless, all of that led to Apple Silicon, and you seem to be ignoring the fact that it’s not costing Apple any money. None of their hookups. This so-called cooperation is costing Apple a dime. But it is costing the other side billions of dollars.
Smile, the models are getting smaller and better, every generation of Apple Silicon is getting better in the opposite direction. The only problem is the cost of memory and that is within the design engineering ability in-house it is also within their financial capacity, so if I’m John or Tim, I too would wake up with a smile because I can fix the one thing that’s giving us trouble memory because we have the talent and the money to fix it in the next four years.
Apple Silicon copied AMD's mistake. RDNA and Apple Silicon are both the slowest GPU architecture for AI because they spent 6 years optimizing raster performance over compute. Now there's 4 generations of Apple Silicon Macs that rely on compute shaders for any kind of efficient inference. Even the M5 GPU is less programmable than Nvidia's ARM GPUs from 2017.
ARM datacenters were a trillion-dollar market that Apple made ~$0 off of. The Mac Pro could have fit that niche, but Tim Cook chose to depreciate it instead of letting the PCIe connectors be used with Nvidia cards. He cut off Apple's nose to spite Nvidia's face. It's nonsense, especially since they're crawling back to Nvidia to license their interconnect, in tacit recognition that it wasn't a real grudge in the first place. My guess is that Ternus doesn't have Tim's money allergy, maybe at the White House's request. In any case, the grudge is over, and Apple forfeit ARM HPC altogether.
> because I can fix the one thing that’s giving us trouble memory because we have the talent and the money to fix it in the next four years.
By all means, continue. Which X account or YouTube channel convinced you that Apple could replace SK Hynix in 4 years?
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That makes sense I also assume there’s better allyship with Meta than X long term geopolitically and they are already in bed with google on search
openai and anthropic are too chaotic to bet on would be my guess