AI Research: A New and Slippery Cost Center for the Google
August 7, 2024
This essay is the work of a dumb humanoid. No smart software required.
A week or so ago, I read “Scaling Exponents Across Parameterizations and Optimizers.” The write up made crystal clear that Google’s DeepMind can cook up a test, throw bodies at it, and generate a bit of “gray” literature. The objective, in my opinion, was three-fold. [1] The paper makes clear that DeepMind is thinking about its smart software’s weaknesses and wants to figure out what to do about them. And [2] DeepMind wants to keep up the flow of PR – Marketing which says, “We are really the Big Dogs in this stuff. Good luck catching up with the DeepMind deep researchers.” Note: The third item appears after the numbers.
I think the paper reveals a third and unintended consequence. This issue is made more tangible by an entity named 152334H and captured in “Calculating the Cost of a Google DeepMind Paper.” (Oh, 152334 is a deep blue black color if anyone cares.)
That write up presents calculations supporting this assertion:
How to burn US$10,000,000 on an arXiv preprint
The write up included this table presenting the costs to replicate what the xx Googlers and DeepMinders did to produce the ArXiv gray paper:
Notice, please, that the estimate is nearly $13 million. Anyone want to verify the Google results? What am I hearing? Crickets.
The gray paper’s 11 authors had to run the draft by review leadership and a lawyer or two. Once okayed, the document was converted to the arXiv format, and we the findings to improve our understanding of how much work goes into the achievements of the quantumly supreme Google.
Thijs number of $12 million and change brings me to item [3]. The paper illustrates why Google has a tough time controlling its costs. The paper is not “marketing,” because it is R&D. Some of the expense can be shuffled around. But in my book, the research is overhead, but it is not counted like the costs of cubicles for administrative assistants. It is science; it is a cost of doing business. Suck it up, you buttercups, in accounting.
The write up illustrates why Google needs as much money as it can possibly grab. These costs which are not really nice, tidy costs have to be covered. With more than 150,000 people working on projects, the costs of “gray” papers is a trigger for more costs. The compute time has to be paid for. Hello, cloud customers. The “thinking time” has to be paid for because coming up with great research is open ended and may take weeks, months, or years. One could not rush Einstein. One cannot rush Google wizards in the AI realm either.
The point of this blog post is to create a bit of sympathy for the professionals in Google’s accounting department. Those folks have a tough job figuring out how to cut costs. One cannot prevent 11 people from burning through computer time. The costs just hockey stick. Consequently the quantumly supreme professionals involved in Google cost control look for simpler, more comprehensible ways to generate sufficient cash to cover what are essentially “surprise” costs. These tools include magic wand behavior over payments to creators, smart commission tables to compensate advertising partners, and demands for more efficiency from Googlers who are not thinking big thoughts about big AI topics.
Net net: Have some awareness of how tough it is to be quantumly supreme. One has to keep the PR and Marketing messaging on track. One has to notch breakthroughs, insights, and innovations. What about that glue on the pizza thing? Answer: What?
Stephen E Arnold, August 7, 2024
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