7 ms·

This isn't anything anyone can purchase, is it? Who's the audience for this announcement?

by fluidcruft 2y ago

badlucklottery 2y ago
> Who's the audience for this announcement? Probably whales who can afford to rent one from Google Cloud.
- jeffbee 2y ago
  People with $3 are whales now? TPU prices are similar to other cloud resources.
  - dylan604 2y ago
    Does anyone do anything useful with a $3 spend, or is it $3 X $manyManyHours?
    - scarmig 2y ago
      No one does anything useful with a $3 spend. That's not anything particular to TPUs, though.
      - dylan604 2y ago
        That's my point. The touting of $3 is beyond misleading.
        fancyfredbot 2y ago
        You can do real work for a few hundred dollars which is hardly the exclusive domain of "whales"? The programmer who writes code to run on these likely costs at least 15x this amount an hour.
- MasterScrat 2y ago
  An on-demand v5e-1 is $1.2/h, it's pretty accessible. The challenge is getting them to run efficiently, which typically involves learning JAX.
llm_nerd 2y ago
The overwhelming majority of AI compute is by either the few bigs in their own products, or by third parties that rent out access to compute resources from those same bigs. Extremely few AI companies are buying their own GPU/TPU buildouts. 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.
- fluidcruft 2y ago
  It just seems like John Deere putting out a press-release about about a new sparkplug that is only useful to John Deere and can maybe be used on rented John Deere harvesters when sharecropping on John Deere-owned fields using John Deere GMO crops. I just don't see what's appealing about any of it. Not only is it a walled garden, you can't even own anything and are completely dependent on the whims of John Deere to not bulldoze the entire field. It just seems like if you build on Tensor then sure, you can go home, but Google will keep your ball.
  - aseipp 2y ago
    The reality is that for large scale AI deployment there's only one criterion that matters: what is the total cost of ownership? If TPUs are 1/30th the total perf but 1/50th the total price, then they will be bought by customers. Basically that simple. Most places using AI hardware don't actually want to expend massive amounts of capital to procure it and then shove it into racks somewhere and then manage it over its total lifetime. Hyperscalers like Google are also far, far ahead in things like DC energy efficiency, and at really large scale those energy costs are huge and have to be factored into the TCO. The long dominant cost of this stuff is all operational expenditures. Anyone running a physical AI cluster is going to have to consider this. The walled garden stuff doesn't matter, because places demanding large-scale AI deployments (and actually willing to spend money on it) do not really have the same priorities as HN homelabbers who want to install inefficient 5090s so they can run Ollama.
xhkkffbf 2y ago
People who buy their stock.
avrionov 2y ago
The audience is Google cloud customers + investors

This isn't anything anyone can purchase, is it? Who's the audience for this announcement?

badlucklottery 2y ago

> Who's the audience for this announcement? Probably whales who can afford to rent one from Google Cloud.

jeffbee 2y ago
People with $3 are whales now? TPU prices are similar to other cloud resources.
- dylan604 2y ago
  Does anyone do anything useful with a $3 spend, or is it $3 X $manyManyHours?
  - scarmig 2y ago
    No one does anything useful with a $3 spend. That's not anything particular to TPUs, though.
    - dylan604 2y ago
      That's my point. The touting of $3 is beyond misleading.
      - fancyfredbot 2y ago
        You can do real work for a few hundred dollars which is hardly the exclusive domain of "whales"? The programmer who writes code to run on these likely costs at least 15x this amount an hour.
MasterScrat 2y ago
An on-demand v5e-1 is $1.2/h, it's pretty accessible. The challenge is getting them to run efficiently, which typically involves learning JAX.

llm_nerd 2y ago

The overwhelming majority of AI compute is by either the few bigs in their own products, or by third parties that rent out access to compute resources from those same bigs. Extremely few AI companies are buying their own GPU/TPU buildouts. 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.

fluidcruft 2y ago
It just seems like John Deere putting out a press-release about about a new sparkplug that is only useful to John Deere and can maybe be used on rented John Deere harvesters when sharecropping on John Deere-owned fields using John Deere GMO crops. I just don't see what's appealing about any of it. Not only is it a walled garden, you can't even own anything and are completely dependent on the whims of John Deere to not bulldoze the entire field. It just seems like if you build on Tensor then sure, you can go home, but Google will keep your ball.
- aseipp 2y ago
  The reality is that for large scale AI deployment there's only one criterion that matters: what is the total cost of ownership? If TPUs are 1/30th the total perf but 1/50th the total price, then they will be bought by customers. Basically that simple. Most places using AI hardware don't actually want to expend massive amounts of capital to procure it and then shove it into racks somewhere and then manage it over its total lifetime. Hyperscalers like Google are also far, far ahead in things like DC energy efficiency, and at really large scale those energy costs are huge and have to be factored into the TCO. The long dominant cost of this stuff is all operational expenditures. Anyone running a physical AI cluster is going to have to consider this. The walled garden stuff doesn't matter, because places demanding large-scale AI deployments (and actually willing to spend money on it) do not really have the same priorities as HN homelabbers who want to install inefficient 5090s so they can run Ollama.

xhkkffbf 2y ago

People who buy their stock.

avrionov 2y ago

The audience is Google cloud customers + investors