DeepFakes versus Deep Understanding
We recorded 4 claims from this post. 3 were checked against evidence. 1 can’t be checked. 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
Recommendation or value judgment
“MetaAI’s new text-to-movie software Make a Video is straight-up amazing.”
Our reading: Meta AI's new text-to-video software Make a Video is straight-up amazing.
No horizon
Assessment: UnresolvedSaid
Observation
“It’s also, as ever, stuck in the liminal space between superintelligence and super-lost.”
Our reading: Make a Video, as with AI systems before it, is caught between very impressive output and basic errors, such as giving a cat a human hand or a painting that never changes.
No horizon Evidence as of
Limitation: The original moving clips were not independently inspected in this assessment.
Assessment: SupportedSaid
Observation
“Of course we see the same thing over and over in language systems, too.”
Our reading: Language systems repeatedly show the same mix of fluent output and lack of understanding.
No horizon Evidence as of
Limitation: Support concerns the recurring behavioral pattern, not the exact anecdotes.
Assessment: UnresolvedSaid
Forecast
“This is the uncanny valley we are in, and one that we occupy for a while.”
Our reading: AI systems such as video, image, and language generators are now in an uncanny valley of impressive output with basic errors, and will stay there for a while.
No deadline stated Evidence as of
Limitation: This outcome does not mean the observed persistence is unsupported; it reflects the missing duration and resolution threshold.