A ton of vector math applications these days are high dimensional vector spaces. A good example of that for arm would I guess be something like fingerprint or face id.

Also, it doesn't just speed up vector math. Compilers these days with knowledge of these extensions can auto-vectorize your code, so it has the potential to speed up every for-loop you write.

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josefx 4 hours ago | parent [-]

> A good example of that for arm would I guess be something like fingerprint or face id.

So operations that are not performance critical and are needed once or twice every hour? Are you sure you don't want to include a dedicated cluster of RTX 6090 Ti GPUs to speed them up?

	▲	pertymcpert 32 minutes ago \| parent \| next [-]
		Those are extremely performance critical operations. A lot of people use their phone many times an hour.
	▲	jovial_cavalier 2 hours ago \| parent \| prev [-]
		I'd argue that those are actually very performance critical because if it takes 5 seconds to unlock your phone, you're going to get a new phone. The point is taken, though, that seemingly the performance is fine as it is for these applications. My point was only that you don't need to be running state of the art LLMs to be using vector math with more than 4 dimensions.