Expectations Versus Reality
We recorded 24 claims from this post. 14 were checked against evidence. 10 can’t be checked. 17 more are held. Read the post at its source.
Claims from this post (24)
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: SupportedSaid
Observation
“Yet these tiny little problems all lead to one overwhelming issue: that Sora isn’t so much a tool to make movies as it is a slot machine that spits out footage that may or may not be of any use at all.”
Our reading: Sora's problems add up to one overwhelming issue: it is less a tool for making movies than a slot machine that produces footage that may or may not be of any use at all.
No horizon Evidence as of
Limitation: Evidence concerns the early preview and one documented production.
Assessment: Can’t be checkedSaid
Causal claim
“Sora’s problem isn’t really the amount of time it takes to generate a shot, but the imprecision that comes from using a generative artificial intelligence that doesn’t really know anything.”
Our reading: Sora's main problem is imprecision caused by generative AI not really knowing anything.
No horizon
Assessment: UnresolvedSaid
Forecast
“Sora’s attempts to replace filmmakers are dead on arrival because these are impractical and ineffective solutions to problems that nobody complained about other than Hollywood executives.”
Our reading: Sora will not succeed in replacing filmmakers because it is an impractical and ineffective solution.
No deadline stated Evidence as of
Limitation: A narrower forecast merely that the Sora product would close could receive a different result.
Assessment: UnresolvedSaid
Conditional forecast
“To make Sora kind of useful, OpenAI will have to find a way to dramatically increase the precision of prompts, reduce hallucinations to almost nothing, and vastly increase processing power across the board.”
Our reading: Sora will only become somewhat useful if OpenAI dramatically improves prompt precision, nearly eliminates hallucinations and vastly increases processing power.
No deadline stated Evidence as of
Only if: for Sora to become kind of useful
Assessment: Can’t be checkedSaid
Conditional forecast
“Sora hasn’t even been launched, save to a few hand-picked companies that got to test an early version, meaning that the 10-to-20 minute wait between generations is something that’s likely to increase once more people use the product, and that’s before you consider how incredibly expensive it is to run a significantly more complex model than ChatGPT, which is already unprofitable for OpenAI to run.”
Our reading: Sora's 10-20 minute generation wait is likely to increase once more people use it.
No horizon
Only if: once more people use the product
Assessment: Can’t be checkedSaid
Forecast
“but the thing that I think he’s leaving out is that it may take an energy breakthrough (and more chips) for generative AI to approach any level of necessity”
Our reading: In the author's view, it may take an energy breakthrough and more chips for generative AI to reach any level of necessity.
No horizon
Qualifier: I think
Assessment: MixedSaid
Observation
“OpenAI failed to make a more efficient model for Microsoft late last year, and while GPT-5 is meant to be “materially better,” it isn’t obvious what “better” means when GPT-4 performs worse at some tasks than its predecessor.”
Our reading: OpenAI failed to build a more efficient model for Microsoft in late 2023, and GPT-4 performs worse than its predecessor at some tasks.
No horizon Evidence as of
Limitation: Arrakis evidence is secondary and traces to one underlying report.
Assessment: UnresolvedSaid
Causal claim
“and he still can’t get past any of these very obvious problems, partly because he isn’t technical and thus can’t really solve any of the problems himself, and partly because the problems he’s facing are burdened by the laws of mathematics and physics.”
Our reading: Despite his connections and funding, Sam Altman still can't get past these obvious problems, partly because he isn't technical and so can't really solve them himself, and partly because the problems are burdened by the laws of mathematics and physics.
No horizon Evidence as of
Limitation: Public reporting provides limited access to internal technical decisions.
Assessment: UnresolvedSaid
Causal claim
“Generative AI is extremely expensive because even the simplest prompts require GPT-4 to run highly-complex mathematical equations on GPUs that cost $10,000 apiece.”
Our reading: Generative AI is extremely expensive because even simple GPT-4 prompts require complex computation on $10,000 GPUs.
No horizon Evidence as of
Limitation: Market prices are not OpenAI purchase records.
Assessment: ContradictedSaid
Causal claim
“Generative AI hallucinates because it doesn’t have a consciousness or any ability to learn or know anything.”
Our reading: Generative AI hallucinates because it lacks consciousness and any ability to learn or know anything.
No horizon Evidence as of
Limitation: The result depends on reading 'any ability to learn' in an operational sense.
Assessment: Can’t be checkedSaid
Observation
“Or perhaps the truth was a little simpler: there wasn’t much artificial intelligence happening at all.”
Our reading: Perhaps there wasn't much artificial intelligence happening at all in Rabbit's Large Action Model.
No horizon
Qualifier: perhaps
Assessment: SupportedSaid
Observation
“Putting aside the remarkable security concerns, the “Large Action Model” also looks like barely-functioning dogshit.”
Our reading: Setting aside its security concerns, Rabbit's Large Action Model looks like it barely functions.
No horizon Evidence as of
Limitation: The phrase has no numerical threshold.
Assessment: SupportedSaid
Observation
“Like I said, useful. But it isn’t AI.”
Our reading: The Playwright scripting Rabbit uses is not AI.
No horizon Evidence as of
Limitation: The assessment follows the immediate antecedent and supplied normalized proposition.
Assessment: UnresolvedSaid
Conditional forecast
“If, say, Uber changes the layout of its website, or changes the flow of certain actions (like booking a cab, or changing the pickup location), it would effectively break that entire part of the service.”
Our reading: If an app like Uber changes its website layout or flows, the corresponding Rabbit R1 functionality would break.
No deadline stated Evidence as of
Only if: if a supported app like Uber changes its layout or flow
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Companies that deliver features late should not get credit for features they are yet to deliver, and companies like Rabbit that engage in the language of science fiction to paper over their lazily-developed half-solutions should get buried for doing so.”
Our reading: Companies should get no credit for features not yet delivered, and companies like Rabbit that hype half-solutions should be harshly criticized.
No horizon
Assessment: UnresolvedSaid
Forecast
“While Rabbit has tens of millions of dollars of venture funding, Rabbit’s business is about as functional as the R1, and I would bet money that it finds a way to try to charge its 100,000 or so customers some sort of subscription fee to stay afloat, just after the single most conspicuous tech reviewer called it “barely reviewable.””
Our reading: Rabbit will try to charge its roughly 100,000 customers a subscription fee to stay afloat.
No deadline stated Evidence as of
Limitation: Requiring a compulsory subscription would narrow Zitron's actual wording.
Assessment: SupportedSaid
Observation
“Funnily enough, this is exactly what the R1 is — an Android app shoved into a bright orange box.”
Our reading: The Rabbit R1 is essentially an Android app in a box.
No horizon Evidence as of
Limitation: The phone port does not establish complete feature equivalence or continuing service access on unofficial installations [e1, e2].
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“It’s time — it’s been time for a while — to accept that artificial intelligence isn’t the digital panacea that will automate our entire lives, and that reality may be far more mediocre than what Sam Altman and his ilk have been selling.”
Our reading: People should accept that AI will not automate our entire lives and may be far more mediocre than Sam Altman claims.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“because something that can automate your calendar, your emails, your music and your travel in a way that you can actually rely on requires operating system-level access and processing of information that may never exist.”
Our reading: Something that can reliably automate your calendar, emails, music and travel requires operating-system-level access and information processing that may never exist.
No horizon
Qualifier: in a way that you can actually rely on
Assessment: MixedSaid
Observation
“Every single story about artificial intelligence seems to begin with “well, AI can’t do much yet, but…” and then lean into sloppy science fiction that masks that these “autonomous agents” are effectively chatbots that can answer questions based on a document, tech that’s existed for a decade or more.”
Our reading: So-called autonomous agents are effectively chatbots answering questions from documents, a decade-old technology.
No horizon Evidence as of
Limitation: A research agent does not establish the quality of every commercial product.
Assessment: UnresolvedSaid
Observation
“AI agents are error-prone, and the likelihood of failure in an automated task like moving a calendar invite or ordering an Uber is exponentially higher and less tolerable in a consumer setting.”
Our reading: AI agents are error-prone, and in a consumer setting the likelihood of failure in automated tasks like moving a calendar invite or ordering an Uber is exponentially higher and less tolerable.
No horizon Evidence as of
Limitation: Benchmark tasks do not directly measure production calendar changes or Uber orders.
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Companies like Google, OpenAI and Rabbit should be treated with suspicion when they make flowery promises, and derision when they continually fail to do anything useful.”
Our reading: Companies like Google, OpenAI and Rabbit should be treated with suspicion when they make flowery promises, and with derision when they continually fail to do anything useful.
No horizon
Only if: when they make flowery promises
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“The tech industry needs to start building things for real people again.”
Our reading: The tech industry should build products that solve real problems for ordinary people.
No horizon
Assessment: Can’t be checkedSaid
Causal claim
“Venture capital investment is at a five-year-low because an alarming amount of VCs don’t seem to understand technology or business, and seem entirely married to hype cycles.”
Our reading: Venture capital investment is at a five-year low because an alarming number of VCs seem not to understand technology or business and seem entirely married to hype cycles.
No horizon
Qualifier: seem
Held from this post (17)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The two reviews reached different assessments. Our reading, not assessed: Generative AI's problems are significantly compounded by the complexity, size and massive legal ramifications of training a model on videos, and nobody has pushed Altman about this.
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: Every bit of scrutiny of Rabbit in recent weeks has suggested that the R1 is badly designed, or at least not particularly sophisticated in its design.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently
- The record does not meet the current rules. Our reading, not assessed: An alleged leak of the Rabbit R1's source code heavily suggests, and the author says others have confirmed, that Rabbit's Large Action Model is repurposing Playwright, software that automates actions in a virtual machine.
- The two reviews reached different assessments. Our reading, not assessed: Even if cheaper or more efficient, generative AI depends on an increasingly dwindling supply of training data.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: Generative AI models will not suddenly start controlling users' apps, calendars, email or running parts of their lives.
- The criteria are ambiguous. Our reading, not assessed: Rabbit will publicly fail because it launched a half-finished product, damaging public trust in tech.
- The two reviews read the claim differently
- The criteria are ambiguous. Our reading, not assessed: There is little evidence that AI agents will ever exist in a form resembling a 'supersmart assistant'.