Discussion

AMD Ryzen AI 400 chips will bring newer CPUs, GPUs, and NPUs to AM5 desktops

Buttons840: Do we expect special AI processors to diverge from GPUs? Like, processors that can do parallel neural network computations but cannot draw graphics?

dagmx: That’s already the norm no?Pretty much every hardware vendor has an NPU

iso-logi: 8 Core/16 Thread, boosting up to 5.1GHz with iGPU would be pretty neat for a Plex Server or Proxmox Server with a few VMs.

cebert: AMD marketing is hoping the “AI” branding is a positive. Antidotally, I know many consumers who are not sold on AI. This branding could actually hurt sales.

aljgz: We are dealing with a hype, but the reality is that AI would change everything we do. Local models will start being helpful in [more] unobtrusive ways. Machines with decent local NPUs would be usable for longer before they feel too slow.

vbezhenar: For some people maybe. I don't want to use local AI and NPU will be dead weight for me. Can't imagine a single task in my workflow that would benefit from AI.It's similar to performance/effiency cores. I don't need power efficiency and I'd actually buy CPU that doesn't make that distinction.

orbital-decay: Also similar to GPU + CPU on the same die, yet here we are. In a sense, AI is already in every x86 CPU for many years, and you already benefit from using it locally (branch prediction in modern processors is ML-based).

kijin: They can just buy a regular Ryzen 9000 series CPU, then. Maybe add a real graphics card if they're into gaming.

skirmish: Indeed, I was buying a laptop for my wife, and she was viscerally against "Ryzen AI": I don't want a CPU with builtin AI to spy on my screen all the time!

fodkodrasz: Never wanted to do high quality voice recognition? No need for face/object detection in near instant speed for your photos, embedding based indexing and RAG for your local documents with free text search where synonyms also work?That is fine. Most ordinary users can benefit from these very basic use cases which can be accelerated.Guess people also said this for video encoding acceleration, and now they use it on a daily basis for video conferencing, for example.

mcraiha: These are mobile chips shoehorned into AM5. They aren't very good e.g. for gaming purposes. https://videocardz.com/newz/amd-ryzen-ai-400-does-not-suppor...

FpUser: Well, for me personally it is a meh until RAM prices go down. Suddenly, decent PC has turned from a tool accessible to average Joe to a luxury item

bitwize: Narrator: The RAM prices did not, in fact, go down.

wtallis: > Can't imagine a single task in my workflow that would benefit from AI.You don't do anything involving realtime image, video, or sound processing? You don't want ML-powered denoising and other enhancements for your webcam, live captions/transcription for video, OCR allowing you to select and copy text out of any image, object and face recognition for your photo library enabling semantic search? I can agree that local LLMs aren't for everybody—especially the kind of models you can fit on a consumer machine that isn't very high-end—but NPUs aren't really meant for LLMs, anyways, and there are still other kinds of ML tasks.> It's similar to performance/effiency cores. I don't need power efficiency and I'd actually buy CPU that doesn't make that distinction.Do you insist that your CPU cores must be completely homogeneous? AMD, Intel, Qualcomm and Apple are all making at least some processors where the smaller CPU cores aren't optimized for power efficiency so much as maximizing total multi-core throughput with the available die area. It's a pretty straightforward consequence of Amdahl's Law that only a few of your CPU cores need the absolute highest single-thread performance, and if you have the option of replacing the rest with a significantly larger number of smaller cores that individually have most of the performance of the larger cores, you'll come out ahead.

poly2it: The Ryzen AI line is actually great if deployed to an entire org as the bottom tier, as it garuantees every device has a 50 TOPs NPU. We deploy local software at $STARTUP and this makes deployment to a Windows corp more predictable.

wtallis: > Also similar to GPU + CPU on the same die, yet here we are.I think the overall trend is now moving somewhat away from having the CPU and GPU on one die. Intel's been splitting things up into several chiplets for most of their recent generations of processors, AMD's desktop processors have been putting the iGPU on a different die than the CPU cores for both of the generations that have an iGPU, their high-end mobile part does the same, even NVIDIA has done it that way.Where we still see monolithic SoCs as a single die is mostly smaller, low-power parts used in devices that wouldn't have the power budget for a discrete GPU. But as this article shows, sometimes those mobile parts get packaged for a desktop socket to fill a hole in the product line without designing an entirely new piece of silicon.

throwa356262: Is everyone a content creator these days?Besides, most of what you mentioned doesn't run on NPU anyway. They are usually standard GPU workload.

c0balt: That is already the case with datacenter "GPUs". A A100, MI300 or Intel PVC/Gaudi does not have useful graphics performance nor capabilities. Coprocessors ala NPU/VPU are also on the rise again for CPUs.

elcritch: Great now I’m envisioning a rich guy using an A100 as his desktop GPU just to show off. Which begs the question if that’s even possible.

lelanthran: It doesn't sound as impressive as I wanted :-(I wanted a better strix halo (which has 128GB unified RAM and 40cu on the 8080s (or something) iGPU).This looks like normal Ryzen mobile chips + but with fewer cus.

bcraven: Presumably that's why the subheading is:>First wave of Ryzen AI desktop CPUs targets business PCs rather than DIYers.

wtallis: None of what I listed was in any way specific to "content creators". They're not the only ones who participate in video calls or take photos.And on the platforms that have a NPU with a usable programming model and good vendor support, the NPU absolutely does get used for those tasks. More fragmented platforms like Windows PCs are least likely to make good use of their NPUs, but it's still common to see laptop OEMs shipping the right software components to get some of those tasks running on the NPU. (And Microsoft does still seem to want to promote that; their AI PC branding efforts aren't pure marketing BS.)

anematode: The issue is that the consumer strongly associates "AI" with LLMs specifically. The fact that machine learning is used to blur your background in a video call, for example, is irrelevant to the consumer and isn't thought of as AI.

wtallis: Putting Strix Halo into the AM5 socket would make no sense. Half the memory controllers would be orphaned and the GPU would be severely bandwidth-starved (assuming that the memory controller on Strix Halo actually supports DDR5 and not just LPDDR5).

Mashimo: Maybe also Immich, for face and object recognition.

zeroflow: As far as I can find, Plex does not support AMD iGPU for transcoding. Jellyfin will work, but support seems rather spotty. For other AI/ML work, it seems like ROCm is up and coming, but support - e.g. for Frigate object detection - is still a work in progress, especially for newer chips.

userbinator: It has no video output.

noelwelsh: Yeah the next generation of Strix Halo is what would get me excited. I think right now TSMC has no capacity, so maybe we have to wait another year. Kinda ironic that all CPU/RAM capacity is being sold to LLM companies, and as a result we can't get the hardware needed for good local LLMs.

a012: > This makes them AMD’s first desktop chips to qualify for Microsoft’s Copilot+ PC label, which enables a handful of unique Windows 11 features like Recall and Click to Do.Microsoft: "Friendship ended with Intel, now AMD is my best friend"

Havoc: Some of these supporting ECC is of some interest. Though fast udimm ecc ram is going to be extremely expensive

ezst: > the reality is that AI would change everything we doYour true believer convictions don't matter here. Those AI accelerators are merely just marketing stunts. They won't help your local inference because they are not general purpose enough for that, they are too weak to be impactful, most people won't ever run local inference because it sucks and is a resource hog most can't afford, and it goes against the interests of those scammy unprofitable corporations who are selling us LLMs as AI as the silver bullet to every problem and got us there in the first place (they are already successful in that, by making computing unaffordable). There's little to no economical and functional meaning to those NPUs.

snovv_crash: Hoe much dedicated cache do these NPUs have? Because it's easy enough to saturate the memory bandwidth using the CPU for compute, never mind the GPU. Adding dark silicon for some special operations isn't going to make out memory bandwidth faster.

bjackman: Does a cache help with inference workloads anyway?I don't know much about it but my mental model is that for transformers you need random access to billions of parameters.