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Anthropic expands partnership with Google and Broadcom for next-gen compute

anthropic.com

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Re: Anthropic expands partnership with Google and Broadcom for next-gen compute

#11

Post by brianjlogan »

Animats wrote: post #7
teaearlgraycold wrote: post #6

Earlier quoted context omitted.

Because that’s the limiting factor

Somehow we must be doing this wrong. "Do you realize that the human brain has been liken to an electronic brain? Someone said and I don't know whether he is right or not, but he said, if the human brain were put together on the basis of an IBM electronic brain, it would take 7 buildings the size of the Empire State Building to house it, it would take all the water of the Niagara River to cool it, and all of the power…

I'd imagine one day there will be a limiting factor of cash to burn as well.

Re: Anthropic expands partnership with Google and Broadcom for next-gen compute

#12

Post by skybrian »

I guess gigawatts is how we roughly measure computing capacity at the datacenter scale? Also saw something similar here:

> Costs and pricing are expressed per “token”, but the published data immediately seems to admit that this is a bad choice of unit because it costs a lot more to output a token than input one. It seems to me that the actual marginal quantity being produced and consumed is “processing power”, which is apparently measured in gigawatt hours these days. In any case, I think more than anything this vindicates my original decision not to get too precise. [...]

https://backofmind.substack.com/p/new-new-rules-for-the-new-...

Is it priced that way, though? I assume next-gen TPU's will be more efficient?

Re: Anthropic expands partnership with Google and Broadcom for next-gen compute

#13

Post by Animats »

brianjlogan wrote: post #11
Animats wrote: post #7

Earlier quoted context omitted.

Somehow we must be doing this wrong. "Do you realize that the human brain has been liken to an electronic brain? Someone said and I don't know whether he is right or not, but he said, if the human brain were put together on the basis of an IBM electronic brain, it would take 7 buildings the size of the Empire State Building to house it, it would take all the water of the Niagara River to cool it, and all of the power…

I'd imagine one day there will be a limiting factor of cash to burn as well.

We're getting close. The first big AI bankruptcy can't be far off.

Re: Anthropic expands partnership with Google and Broadcom for next-gen compute

#14

Post by mikert89 »

totaa wrote: post #3
mikert89 wrote: post #2

There's no limit to the algorithms. People dont understand yet. They can learn the whole universe with a big enough compute cluster. We built a generalizable learning machine

the question is will we experience resource constraints before we get there? what if the step up to post-scarcity is gated by a compute level just out of our reach?

human ingenuity will solve this

Re: Anthropic expands partnership with Google and Broadcom for next-gen compute

#16

Post by whimsicalism »

Animats wrote: post #7
teaearlgraycold wrote: post #6

Earlier quoted context omitted.

Because that’s the limiting factor

Somehow we must be doing this wrong. "Do you realize that the human brain has been liken to an electronic brain? Someone said and I don't know whether he is right or not, but he said, if the human brain were put together on the basis of an IBM electronic brain, it would take 7 buildings the size of the Empire State Building to house it, it would take all the water of the Niagara River to cool it, and all of the power…

pretty sure evolution spent more time and energy getting there then we ultimately will

Re: Anthropic expands partnership with Google and Broadcom for next-gen compute

#17

Post by brokencode »

skybrian wrote: post #12

I guess gigawatts is how we roughly measure computing capacity at the datacenter scale? Also saw something similar here: > Costs and pricing are expressed per “token”, but the published data immediately seems to admit that this is a bad choice of unit because it costs a lot more to output a token than input one. It seems to me that the actual marginal quantity being produced and consumed is “processing power”, which…

Gigawatts seems like more a statement of the power supply and dissipation of the actual facility.

I’m assuming you can cram more chips in there if you have more efficient chips to make use of spare capacity?

Trying to measure the actual compute is a moving target since you’d be upgrading things over time, whereas the power aspects are probably more fixed by fire code, building size, and utilities.

Re: Anthropic expands partnership with Google and Broadcom for next-gen compute

#18

Post by serf »

teaearlgraycold wrote: post #6
Eufrat wrote: post #4

Can someone explain why everything is being marketed in terms of power consumption?

Because that’s the limiting factor

kinda complicated though when you consider it fully. Power consumption only measures the environmental impact really, we come up with more clever ways to use the same amount of power daily.

it's kind of like an electrical motor that exists before the strong understanding of lorentz/ohm's law. We don't really know how inefficient the thing is because we don't really know where the ceiling is aside from some loosey theoretical computational efficiency concepts that don't strongly apply to practical LLMs.

to be clear, I don't disagree that it's the limiting factor, just that 'limits' is nuanced here between effort/ability and raw power use.

Re: Anthropic expands partnership with Google and Broadcom for next-gen compute

#19

Post by bdangubic »

Animats wrote: post #13
brianjlogan wrote: post #11

Earlier quoted context omitted.

I'd imagine one day there will be a limiting factor of cash to burn as well.

We're getting close. The first big AI bankruptcy can't be far off.

Big Gov will bail out the big guys if/when necessary

Re: Anthropic expands partnership with Google and Broadcom for next-gen compute

#20

Post by supliminal »

teaearlgraycold wrote: post #5
mikert89 wrote: post #2

There's no limit to the algorithms. People dont understand yet. They can learn the whole universe with a big enough compute cluster. We built a generalizable learning machine

Not sure if this is satire. Edit: What we have built is a natural language interface to existing, textually recorded, information. Transformers cannot learn the whole universe because the universe has not yet been recorded into text.

It’s more than likely not.
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