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> . The chip, known internally as the Apple Neural Engine, Is this a real IC/processor for arbitrary software or an abstraction of an underlying GPU/DSP?
This is probably going to be a hyper parallel fixed point / integer engine like TPU gen1. Doing fast matrix multiply over really small fields is very subpar on CPUs and GPUs. That was the initial reasoning behind TPU gen1 - improving runtime performance. One question is if it will architecturally be closer to a GPU or an FPGA. The field moves so fast that it might make sense to "future-proof" a bit with a live-reconf…
I foresee it as similar to their M series co-processors - the first one was pretty basic, and more sensors and jobs have been given to the newer ones each year.
This is probably going to be a hyper parallel fixed point / integer engine like TPU gen1. Doing fast matrix multiply over really small fields is very subpar on CPUs and GPUs. That was the initial reasoning behind TPU gen1 - improving runtime performance. One question is if it will architecturally be closer to a GPU or an FPGA. The field moves so fast that it might make sense to "future-proof" a bit with a live-reconf…
You don't put an FPGA in a device you're going to sell 200M+ of. The cost per unit would be way higher than an asic, and your just going to come out with a better version next year anyway so why bother? I foresee it as similar to their M series co-processors - the first one was pretty basic, and more sensors and jobs have been given to the newer ones each year.
> . The chip, known internally as the Apple Neural Engine, Is this a real IC/processor for arbitrary software or an abstraction of an underlying GPU/DSP?
I wish they would have called it Apple Neural Technology, so we could start referring to the devices as ANTs and Hives and Colonies as we build out Richard Hendrick's new decentralized internet.
This is probably going to be a hyper parallel fixed point / integer engine like TPU gen1. Doing fast matrix multiply over really small fields is very subpar on CPUs and GPUs. That was the initial reasoning behind TPU gen1 - improving runtime performance. One question is if it will architecturally be closer to a GPU or an FPGA. The field moves so fast that it might make sense to "future-proof" a bit with a live-reconf…
I'd bet on this being an ASIC, doing this on an FPGA with any serious size matrix would require a very expensive FPGA, whereas an ASIC would allow more gates in a smaller volume and would consume less power to boot. From the manufacturers point of view phones not being future proof is a feature, not a bug, that way you'll upgrade to that new shiny item which will keep the profits rolling in.
I don't think a better AI chip will be a convincing argument to change a phone one year later.
Earlier quoted context omitted.
I'd bet on this being an ASIC, doing this on an FPGA with any serious size matrix would require a very expensive FPGA, whereas an ASIC would allow more gates in a smaller volume and would consume less power to boot. From the manufacturers point of view phones not being future proof is a feature, not a bug, that way you'll upgrade to that new shiny item which will keep the profits rolling in.
> From the manufacturers point of view phones not being future proof is a feature, not a bug, that way you'll upgrade to that new shiny item which will keep the profits rolling in. I don't think a better AI chip will be a convincing argument to change a phone one year later.
My assumption has been that Google, Amazon, and Microsoft run the heavy-duty AI in the cloud when possible, benefiting from huge scale and easier updates. Maybe that assumption is wrong? If it's right, is Apple adopting a more decentralized model, with AI (or more AI) running locally? Could that compete with cloud-based AI's advantages? Obviously it would be better for offline usage, for responsiveness when transmiss…
My assumption has been that Google, Amazon, and Microsoft run the heavy-duty AI in the cloud when possible, benefiting from huge scale and easier updates. Maybe that assumption is wrong? If it's right, is Apple adopting a more decentralized model, with AI (or more AI) running locally? Could that compete with cloud-based AI's advantages? Obviously it would be better for offline usage, for responsiveness when transmiss…
Google's been working on distributed training as well.
Also, are they doing training for the local user or for Google's 'general' systems or for both?
Why is Bloomberg not mentioning that Google announced it was working on the same thing? They mentioned vaguely that Amazon and Google both were working on AI, but nothing about the seemingly similar TPU and how Google announced they were going to bring it to phones at I/O just a bit ago. Am I wrong to be thinking that's pretty relevant here?