Monopoly Money
We recorded 11 claims from this post. 5 were checked against evidence. 6 can’t be checked. 5 more are held. Read the post at its source.
Claims from this post (11)
In the order they appear in the post. Each quotation is the speaker’s words in this post. A label such as “Supported” or “Can’t be checked” is the claim’s current assessment; its page has the evidence and the reasons.
Assessment: Can’t be checkedSaid
Observation
“Last week, in the midst of the slow, painful collapse of the generative AI hype cycle, something incredible happened.”
Our reading: The generative AI hype cycle is in a slow, painful collapse as of August 2024.
No horizon
Assessment: Can’t be checkedSaid
Observation
“Monopolies are inherently anti-consumer and anti-innovation, and the big push toward generative AI is a blatant attempt to create another monopoly — the dominance of Large Language Models owned by Microsoft, Amazon, Google and Meta.”
Our reading: Big tech's push toward generative AI is a deliberate attempt to create a monopoly of LLMs owned by Microsoft, Amazon, Google and Meta.
No horizon
Assessment: UnresolvedSaid
Causal claim
“While this might seem like a competitive marketplace, because these models all require incredibly large amounts of cloud compute and cash to both train and maintain, most companies can’t really compete at scale.”
Our reading: Because LLMs require enormous compute and cash to train and maintain, most companies cannot compete at scale in the LLM market.
No horizon Evidence as of
Limitation: The boundaries of the market and the meaning of scale materially affect the assessment.
Assessment: ContradictedSaid
Observation
“No private startup can actually afford to build and scale a Large Language Model without the help of Google, Amazon or Microsoft — and thus they would, assuming they actually became useful, effectively control every single product involving this technology.”
Our reading: No private startup can afford to build and scale an LLM without the help of Google, Amazon or Microsoft.
No horizon Evidence as of
Limitation: The financing and infrastructure finding combines a contemporary technical paper with later reporting and retrospective testimony.
Assessment: UnresolvedSaid
Conditional forecast
“No private startup can actually afford to build and scale a Large Language Model without the help of Google, Amazon or Microsoft — and thus they would, assuming they actually became useful, effectively control every single product involving this technology.”
Our reading: If LLMs became useful, Google, Amazon and Microsoft would effectively control every product involving the technology.
No deadline stated Evidence as of
Only if: if LLMs actually became useful
Assessment: Can’t be checkedSaid
Forecast
“generative AI is (in most cases) a product with minimal utility, minimal value, and will likely prove to be a transient fad”
Our reading: Generative AI will likely prove to be a transient fad.
No horizon
Assessment: Can’t be checkedSaid
Observation
“And these companies are, in some cases, well-positioned to become tech’s next landlord.”
Our reading: Some big tech companies controlling LLMs are well-positioned to become the tech industry's next landlord.
No horizon
Qualifier: in some cases
Assessment: Can’t be checkedSaid
Observation
“I hypothesize that the goal was (is?) for these companies to basically reduce the future of computing to you paying them for their models rather than you running your own models on their cloud compute services.”
Our reading: Ed hypothesizes that big tech's goal is to make customers pay for their models rather than run their own models on the companies' cloud services.
No horizon
Qualifier: hypothesis
Assessment: UnresolvedSaid
Observation
“Microsoft, Google, Amazon and Meta also monopolize the infrastructure itself, both in the data centers they can build (or already own) and in their access to the specialized GPUs necessary to run these models.”
Our reading: Microsoft, Google, Amazon and Meta monopolize AI infrastructure, through data centers and access to the GPUs needed to run models.
No horizon Evidence as of
Limitation: Cloud revenue shares are a different measure from physical capacity or GPU access.
Assessment: UnresolvedSaid
Causal claim
“This master plan only falls apart when the “thing” that needs to be trained using hardware that they monopolize doesn’t actually provide the business returns that they need to justify its existence.”
Our reading: Big tech's master plan to monopolize AI models falls apart only when the models trained on their monopolized hardware do not provide the business returns needed to justify their existence.
No horizon Evidence as of
Limitation: The evidence provides no defined failure event, financial sufficiency measure, or causal comparison.
Assessment: Can’t be checkedSaid
Conditional forecast
“And without something new — and no, generative AI is not the answer — they really don’t have a way to keep growing, and in the case of Meta and Google, may not have a way to sustain their companies past the next decade.”
Our reading: Without a new growth product (and generative AI is not it), Meta and Google may not be able to sustain their companies past the next decade.
No horizon
Only if: without something new beyond generative AI
Held from this post (5)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The criteria are ambiguous. Our reading, not assessed: Zitron does not think big tech's generative AI monopoly (or oligopoly) actually worked, because generative AI loses much more money than it makes and has yet to solve the complex problems that would justify its costs.
- The criteria are ambiguous. Our reading, not assessed: Generative AI loses far more money than it makes and has not yet solved complex problems that would justify its costs.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently