Spinal Tap meets John Malkovich
We recorded 4 claims from this post. 2 were checked against evidence. 2 can’t be checked. 3 more are held. Read the post at its source.
Claims from this post (4)
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
“These systems can draw things that kinda look like the world, but they obviously don’t know what’s what or how things work outside of their training data.”
Our reading: Generative image systems can produce world-like images but do not understand what things are or how they work outside their training data.
No horizon
Qualifier: outside of their training data
Assessment: SupportedSaid
Observation
“No model could have done this in 2022. The graphics are vastly better than they used to be.”
Our reading: Image generation graphics quality has improved vastly since 2022, to a level no 2022 model could reach.
No horizon Evidence as of
Limitation: The evidence does not show that no 2022 model could produce a sharp, mechanically correct image of a rider. The 2022 test found some good outputs.
Assessment: Can’t be checkedSaid
Causal claim
“Because they live in the land of correlations between images and text, not in the land of ideas.”
Our reading: The image-generating AI systems under discussion are unpredictably right or wrong because they operate in the land of correlations between images and text, not in the land of ideas.
No horizon
Scope: these systems
Assessment: UnresolvedSaid
Observation
“Watch the tuners come and go! So much for object permanence.”
Our reading: Grok's generated video failed to keep objects consistent, with the bass tuners appearing and disappearing.
No horizon Evidence as of
Limitation: No evidence items show what the video contains.
Held from this post (3)
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: When the image-generating AI systems under discussion are run many times, they are sometimes right and sometimes wrong, and you never know which result you will get.
- The criteria are ambiguous. Our reading, not assessed: The model that produced the rebuttal image (ChatGPT-5 Thinking) was clearly better than the model whose unicycle image Marcus had ridiculed.
- The two reviews reached different assessments. Our reading, not assessed: Better graphics in the image-generating AI systems under discussion do not necessarily mean a better understanding of the world.