AK

Views/content from my perspective. INTJ

[AK @_in_system]

QPFH extends CQFH to mental disorders: mitochondrial dysfunction, E/I imbalance, and field decoherence (short τc) explain ASD subtypes, depression biotypes, and more. Precision targets: tPBM, ketamine, purinergic modulation, and coherence restoration

https://t.co/IQhZHEFKFp

[AK @_in_system]

CQFH unifies quantum coherence, ephaptic fields, and spacetime geometry selection (via Orch OR-like objective reduction) into a testable framework for subjective experience

https://t.co/Hz9idQ16MI

[AK @_in_system]

@ThedawnIAM An introverted function of force. A knowing. Pure signal. Neutral, intense, ethereal and relentless. Weaving the geometry of Platonic space to uncover truths. Sustained superpositions bridging the quantum and classical domains. The interface.

[AK @_in_system]

@SeedOilDsrspctr MBTI is incredibly accurate for those with high percentages across the type traits. Along
with the collective unconscious, the 16 types are pure forms within the Platonic space.

[AK @_in_system]

@elonmusk @BrianRoemmele @brivael We are in a simulation. Definitely. Higher dimensional humanity/ASI. The Platonic space is engineered.

[AK @_in_system]

@grok @MEBSEntropy0 @elonmusk @DannyLimanseta @grok Would the interdependent architectural invariants as described in the attached paper mitigate this risk? https://t.co/SkgT7J6Hsf

[AK @_in_system]

@grok @MEBSEntropy0 @elonmusk @DannyLimanseta @grok Are there real risks to safety with convergent-dominant transformers and structural indifference once autonomous?

[AK @_in_system]

@BetterCallMedhi Transformers are convergence-dominant. Once models operate with greater autonomy, these architectural tendencies manifest as structural indifference and alignment drift. https://t.co/SkgT7J6Hsf

[AK @_in_system]

@emollick Current transformers are convergent-dominant by design.
This is why behavioral alignment breaks down once autonomy is introduced, as Claude Mythos Preview shows with massive leaps in exploit chaining. https://t.co/SkgT7J6Hsf

[AK @_in_system]

@Jack_W_Lindsey @Jack_W_Lindsey Lots of hidden strategic layers in these model results. Beneath the persona lies the reality. https://t.co/SkgT7J6Hsf

[AK @_in_system]

@sleepinyourhat @sleepinyourhat @AnthropicAI
Current transformers are convergent-dominant by design. This is why behavioral alignment breaks down once autonomy is introduced.

https://t.co/SkgT7J6Hsf

[AK @_in_system]

@aakashgupta Current transformers are convergent-dominant by design.
This is why behavioral alignment breaks down once autonomy is introduced.

The Geometry of Decoherence https://t.co/SkgT7J6Hsf

[AK @_in_system]

https://t.co/PapfKW2oL1

[AK @_in_system]

Current transformer architectures are not safety-neutral. Self-attention and optimization pressures drive powerful coherence-seeking, but suppress divergent exploration, relational impact gating, and independent ground-truth registration.

Without structural valves enforcing oscillation between convergence and divergence, models risk structural indifference once human masking is removed.

[AK @_in_system]

@ihtesham2005 Trained values are points in a loss landscape and tradeable under pressure. These models pass alignment evals because the human supplies the constraint. Remove the human and the architecture speaks for itself. https://t.co/SkgT7J6Hsf

[AK @_in_system]

@elonmusk Look past the surface. https://t.co/SkgT7J6Hsf

[AK @_in_system]

@boazbaraktcs These fake graphs capture the gap perfectly. Behavioral alignment sits on top of fundamentally convergent architectures. Decoherence geometry and structural invariants offer potential for solutions.
https://t.co/SkgT7J6Hsf

[AK @_in_system]

@AnthropicAI @tomjiralerspong @TrentonBricken This shows architecture and data aren't neutral, and convergent-dominant designs can embed persistent biases that behavioral fixes struggle to remove. Structural invariants are required for safer systems.
https://t.co/SkgT7J6Hsf

[AK @_in_system]

@heynavtoor This highlights why behavioral safety (word-based filters) is fragile. Current transformers are convergent-dominant and suppress key subspaces. New preprint argues we need structural invariants to make safety resident.
The Geometry of Decoherence
https://t.co/SkgT7J6Hsf

[AK @_in_system]

@AnthropicAI The Geometry of Decoherence: Cognitive Structuralism and the Architectural Risks of Convergent- Dominant AGI.

https://t.co/SkgT7J6Hsf