This is a big part of why they are generally available. Building on top of AMD gear is currently more difficult than Nvidia. It's unfortunate, but the evolution of/from Cuda when AMD had little in this space gave intel a massive jump-start. As a dev it's way easier to pick up various stacks that work with nvidia gear and not have to worry anywhere near as much about what's underneath.

That's not very convincing against Nvidia. Since they single handedly created the modern AI market through CUDA.

The topic of customer interest is addressed at timestamp 59 minutes and zero seconds of the keynote.

By my count, 49 corporate logos were shown as launch partners.

At one point in the talk the CEO claims that “Blackwell will be Nvidia’s most successful product ever”.

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And again, the product he’s talking about is a data centers packed with 56 racks…

I’m aware.

In the keynote Nvidia is quoting FP4 performance for Blackwell specifically. Frontier and every computer that has ever hit the supercomputer top 500 is measuring fp64. This is why I qualified my statement above by saying if you’re willing to compare apples and oranges.

But I think this is where things open up to debate (and/or personal interpretation). My view is, if all you care about is AI workload (Specifically LLMs), then you really are seeing a full two orders of magnitude improvement. And if we are trying to get a feel for the space, and what that even means, then there really is nothing else to compare Blackwell to other than frontier, in terms of scale alone.

Above I say “one or two orders of magnitude”, the “one order of magnitude” is a value I got by taking Blackwell’s FP4 values and dividing by 16, to try to conceptually convert back to a value that can be compared to fp64. — I’m perfectly happy to admit that all I’m really capable of doing here is using estimates to compare a completely new thing (the new compute architecture of Blackwell) to what came before it (the majority of the history of the supercomputing 500). But that’s okay, because that’s my only goal.

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Believe me, I get it. Blackwell will never post a linpack score. Blackwell will never run big scientific computing jobs like… global weather simulations.

But as computer science nerds, how could we not be excited to see such a big move: changing the computer architecture to better suit a specific compute workload (LLMs)?

I know Bitcoin has its asic processors, but to me Blackwell’s mission statement of “computing intelligence” is a lot more interesting.

I don't think we'll be legally prohibited from buying it but there will be zero English docs (see Allwinner and such). Maybe if you're lucky you'll get an uncommented code dump with a forked years-old version of PyTorch.

From that exchange, clearly not. They do not have their stuff together. This is one area where AMD really should be employing quite a full team to ensure that major projects, including drivers, are able to support AMD cards without any friction. Whilst it's still a PITA to work.with AMD hardware in most AI frameworks Nvidia will continue to dominate.

In 50 years, I feel like GPGPU compute will be told as a Greek tragedy. Nvidia, pariah of Apple, would create a parallel compute ecosystem that was so powerful that even the combined effort of the industry couldn't topple it. At every corner where they could have thwarted them, Nvidia's competitors refused to up the ante or chided CUDA's efforts as silly and unnecessary. One crypto/AI craze later, everyone and their mother is berating their OEM for ignoring such basic functionality and refusing to collaborate on a competing alternative.

Frustrating is a good way to put it, but there's a certain causal satisfaction I feel from watching it all unfold. Of course everyone loses to CUDA when they refuse to sponsor an Open Source alternative. It's fascinating to me that hardware manufacturers would rather let CUDA dominate than establish a basic working relationship.