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What dataflow processors is AMD shipping?

The XDNA NPU is a small dataflow processor. Originally derived from xilinx IP.

Yes such an obvious fix

Pure model slop. When I read this I get a headache and feel repulsed.

Yes, Dead internet stinks and is approaching faster than AI market collapse.

Likewise. I'm a RISC-V fan but a slop page like this is not a good look.

I agree. I am thinking this can only happen if we make training dramatically cheaper and efficient. This is why we are building a new kind of hardware.

How did you setup the 2x dgx spark?


Pretty much just this, but tweaked to have I think 64 active conversations be cacheable, which drops the context pool to ~2M.

https://github.com/MiaAI-Lab/GLM-5.3-Flash-EXL3-2x-DGX-Spark...

I also had to downclock my Sparks (Asus) slightly, to 2000 Mhz. Otherwise they'd overheat and crash.


they have exactly two customers, both of whom are also investors.


More precisely they can't cache it.


Yes. Their architecture recomputes every time so at 150k context every request will have to spend 1.5 min waiting for the model to reread the context.

Say avg model response length is 1024 tok. At 50 tok/s normal providers do your turn will only take 20s (vs Cerebras 101s) and will cost 20x less. That time and cost is per single tool call.


Same can also be said of IBMs computers at the time and the US efforts to build computers.


Sure, winners writing the history is a tale as old as time.


Step 1: steal all of the worlds IP and make a judge rule it is fair use

Step 2: declare end of the Anthropocene (defined by man made influence on earth), while simultaneously accelerating mass extinction

Step 3: ???

Step 4: Profit?


You forgot the part where they finance this all with a never-ending pile of circular IOUs.


They definitely use three exclamation points instead of that last question mark.


They are increasingly being trained on generated tasks and even (parts) of the pre-training data is 'distilled' (e.g. Clibmix as an open-source example), so there are many ways in which the vocabulary can seep into the model.


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