Interesting question.
I’d actually be curious how it feels to ask this directly to Never Wrong AI.

If you want to see whether an AI “really understands physics,”
CritPt is the new stress test.
I’ll keep pushing UEI × physics benchmarks next.

🔗 critpt.com/example.html
#AI #UEI #CritPt #Emergence #Quantum #ScalingBeyondScaling

Emergence isn’t a glitch.
It’s the moment μ crosses μ_c.

This is the convergence point:

– After scaling
– After world models
– Before the next AI transition

UEI sits here—where coherence shapes intelligence.

#UEI #Emergence #AI #Robotics #PhaseTransition #PhaseGeometry

#WorldModels didn’t peak — they ran out of geometry.
Prediction alone won’t build generalization.
#Robotics exposes the limit:

Better images → Not enough
Bigger models → Not enough

What’s missing is coherent phase structure inside the model.

#PhaseGeometry

Emergence isn’t a glitch.
It’s the moment μ crosses μ_c.

This is the convergence point:

– After scaling
– After world models
– Before the next AI transition

UEI sits here—where coherence shapes intelligence.

#UEI #Emergence #AI #Robotics #PhaseTransition #PhaseGeometry

#WorldModels didn’t peak — they ran out of geometry.
Prediction alone won’t build generalization.
#Robotics exposes the limit:

Better images → Not enough
Bigger models → Not enough

What’s missing is coherent phase structure inside the model.

#PhaseGeometry

You can add FLOPs and GPUs,
but you can’t scale your way into emergence.
Only structural shifts create coherent intelligence.
TiDAR is the early echo of that shift.
#AI #Emergence

Draft decoding isn’t about tokens.
It’s about selecting the most coherent phase branch.
When a model optimizes coherence instead of sequence,
its geometry starts to crystallize.
#AI