The regulations specify the performance ceiling. Nvidia just ships products slower than that
The regulations specify the performance ceiling. Nvidia just ships products slower than that
US is not going to side against Nvidia for AMD, when AMD performance gets to par, they will get the cut as well
I remember Nvidia spent like $11 Billion in 2021 in preparation of current gen chips so $14 billion on chips including thos on N3B checks out
Igor will post about this every month I guess
How many articles is this guy going to make about this with the same conclusions?
He is responsible for Intel Gaudi, the best option for AI other than Nvidia H100 and A100
This headset is what people raved that Apple vision would be (just because it’s Apple)
New GPU architecture, now also integrating Intel’s ‘tensor cores’ for better XeSS among other things
Despite knowing RDNA3, people still hyped this as on 4090M territory
We just look at benchmarks, of which GPUs do extremely well
Last gen, Lovelace was rumored as late and RDNA3 was rumored early.
Let’s just say I am skeptical
Not FP32, MI300 has 48 TFLOPS, H100 has 60TFLOPs
https://www.topcpu.net/en/cpu/radeon-instinct-mi300
AMD FP64 still gaps Nvidia who in turn gap FP16
It’s Alchemist, previous iGPUs were the old xe iris LPE iGPU architecture
Long duration? Have you heard of the BigScreen beyond?
Sorry, I misread. I thought you said highest selling GPU which is what I have also read elsewhere.
Seems to me 7800XT is their best performer but not sure
Not the best beat saber device, but a damn good sim device when it works
Yeah, his opinions shine through brightly
Hopefully the Chrystal succeeds, it’s more reasonable than 12KX while offering a great high end display, good refresh rate and some of the best field of view.
If the made their next headset similar spec but smaller, I would definitely have a look
That’s not backed by AMD financials or marketshare
No, you are limited by:
Compute Performance, you will need 10,000%+ more compute than was available per chip, and those PCIe accelerators don’t have the ability to compute the way they do now. You are going to have to rely on CPUs which is worse
Lack of scalabality of interconnecting chips to behave as one, increasing IO requirements dramatically.
Lack of memory pooling (yes you qualified it), memory bandwidth and memory sizes (we are talking in megabytes), imagine waiting for 1 billion parameter model calculations to load and store in each layer of a neural network using floppy disks.