31–40 of 186 posts
Are there a few big things, many small things...? I'm curious what fruit are left hanging for fast SIMD matrix multiplication.
This isn't anything anyone can purchase, is it? Who's the audience for this announcement?
Probably whales who can afford to rent one from Google Cloud.
It looks amazing but I wish we could stop playing silly games with benchmarks. Why compare fp8 performance in ironwood to architectures which don't support fp8 in hardware? Why leave out TPUv6 in the comparison? Why compare fp64 flops in the El Capitan supercomputer to fp8 flops in the TPU pod when you know full well these are not comparable? [Edit: it turns out that El Capitan is actually faster when compared like f…
Because it is a public company that aims to maximise shareholder value and thus the value of it's stock. Since value is largely evaluated by perception, if you can convince people your product is better than it is, your stock valuation, at least in the short term will be higher. Hence Tesla saying FSD and robo-taxis are 1 year away, the fusion companies saying fusion is closer than it is etc.... Nvidia, AMD, apple an…
A big part of my issue here is that they've really messed up the misleading benchmarks.
They've failed to compare to the most obvious alternative, which is Nvidia GPUs. They look like they've got something to hide, not like they're ahead.
They've needlessly made their own current products look bad in comparison to this one understating the long-standing advantage TPUs have given Google.
Then they've gone and produced a misleading comparison to the wrong product (who cares about El Capitan? I can't rent that!). This is a waste of credibility. If you are going to go with misleading benchmarks then at least compare to something people care about.
Its hard to be excited about hardware that will only exist in the cloud before shredding.
Not knowing much about special-purpose chips, I would like to understand whether chips like this would give Google a significant cost advantage over the likes of Anthropic or OpenAI when offering LLM services. Is similar technology available to Google's competitors?
This isn't anything anyone can purchase, is it? Who's the audience for this announcement?
Google says Ironwood will be available in the Google Cloud late this year, so it's relevant to just about anyone that rents AI compute, which is just about everyone in tech. Even if you have zero interest in this product, it will likely lead to downward pressure on pricing, mostly courtesy of the large memory allocations.
Earlier quoted context omitted.
Are you suggesting NVIDIA is not a competitor?
You said: "notice that it’s not compared to competitors" The article says: "When scaled to 9,216 chips per pod for a total of 42.5 Exaflops, Ironwood supports more than 24x the compute power of the world’s largest supercomputer – El Capitan – which offers just 1.7 Exaflops per pod." It is literally compared to a competitor.
This isn't anything anyone can purchase, is it? Who's the audience for this announcement?