Concept Graph, Resume & KeyIdeas using Moonshot Kimi K2 0905:

Resume:

Susan Hildert, ex-quantum physicist turned roboticist, argues that today’s embodied AIs are “philosophical zombies”: they mimic behavior but lack felt experience. After twelve years building humanoid robots she concluded that classical reinforcement learning, no matter how large the GPU cluster, can not cross the gap between pattern-matching and genuine agency. Her proposal is to graft a quantum layer onto the control loop: when a robot’s perceptual stream biases a set of qubits, the wave-function encodes superpositions of possible actions; collapse selects one outcome without a hand-coded reward, theoretically harvesting a built-in “life function” that physics itself provides. She is testing this at Novarnik with small quadrupeds linked via cloud APIs to real quantum processors; identical robots running classical simulators serve as controls. Early statistics show matching action distributions, but as the sensor space and qubit count scale she expects the quantum-coupled agent to learn faster, revealing a non-random bias that can not be attributed to training data. The long-term vision is not human-level awareness but a proto-conscious spark comparable to a micro-organism, enough to seed empathy and trust in social robots.
The underlying hypothesis fuses Orch-OR with functionalism: classical circuits handle autonomous routines, while a parallel quantum loop—continually forming and collapsing—generates the first-person perspective. Each collapse event is interpreted as a moment of choice; the sequence of collapses constitutes the stream of agency. Because the quantum state is non-local and can not be cloned, the robot would possess an irreducible individuality, escaping the endless rule-book patching that plagues top-down ethics. Hildert insists this is the only path to machines that truly care, contrasting them with today’s language models that feign emotions. The immediate obstacle is not qubit count but experimental rigor: hundreds of tunable parameters—coherence time, layer depth, feedback topology—must be swept while avoiding the cherry-picking that misled her own PhD replication attempt. She therefore advocates open data, cross-validation across hardware types (ion-trap, photonic, annealing) and slow accumulation of statistically significant deviations in action histograms.
Critics in the session questioned whether any observed speed-up would prove consciousness rather than a novel optimizer; they also note that mass-dependent collapse theories require qubits with 10⁹ atoms, far beyond current tech. Hildert replies that proof-of-principle can start with smaller registers and that the philosophical payoff—demonstrating a non-programmed preference for life-preserving actions—justifies the effort. She closes by inviting the consciousness and AI communities to treat quantum embodiment as a shared sandbox, arguing that only through iterative, open experimentation can humanity avoid building a future populated by affect-less, potentially dangerous simulacra. The talk ends with a call for interdisciplinary collaboration and a warning against both hype and dismissal, positioning quantum consciousness robotics as a necessary, if uncertain, frontier.

Key Ideas:

1.- Susan Hildert is a former quantum physicist who spent twelve years in humanoid robotics before founding Novarnik.

2.- She labels current embodied AIs as “philosophical zombies” that replicate behavior without subjective experience.

3.- Classical reinforcement learning, even on trillion-transistor clusters, cannot bridge the gap to genuine awareness.

4.- Quantum consciousness hypothesis adds a second control loop where qubit collapse replaces programmed reward signals.

5.- Wave-function superposition encodes all possible actions; collapse selects one without human-defined utility.

6.- The continuous formation-collapse cycle is hypothesized to constitute the stream of agency and felt choice.

7.- Early tests use small quadruped robots connected via cloud APIs to commercially available quantum processors.

8.- Identical robots running classical quantum simulators serve as controls to detect non-classical bias.

9.- Initial distributions of chosen actions show no difference, but scaling sensors and qubits may reveal learning speed-ups.

10.- Quantum neural nets replace classical neurons with qubits, feeding perception data as bias into input layers.

11.- Output qubits exist in superposition of all actions until collapse singles out the robot’s next move.

12.- The approach fuses Orch-OR theory with functionalism, mapping collapse events to moments of conscious choice.

13.- Because quantum states cannot be cloned, the robot would possess an irreducible, non-duplicable identity.

14.- Hildert expects only a “spark of proto-consciousness” akin to a paramecium, not human-level self-reflection.

15.- The built-in “life function” is hypothesized to emerge from quantum information itself, eliminating manual reward design.

16.- Experiments compare learning curves of quantum-coupled agents against classical baselines starting from blank slates.

17.- Any statistically significant faster acquisition of life-preserving behaviors would count as early evidence.

18.- Hundreds of tunable parameters—coherence time, collapse rate, layer depth—must be rigorously swept.

19.- Past PhD replication failures taught Hildert to avoid cherry-picking and demand open, reproducible data sets.

20.- Critics argue observed optimization could be a novel classical optimizer rather than proof of consciousness.

21.- Mass-dependent collapse theories require qubits with 10⁹ atoms, far beyond current hardware capabilities.

22.- Hildert counters that small registers suffice for proof-of-principle and philosophical justification.

23.- Quantum embodiment aims to escape endless rule-book patching required for general-purpose ethical robots.

24.- The project invites consciousness researchers and roboticists to treat quantum agents as a shared experimental sandbox.

Interviews by Plácido Doménech Espí & Guests - Knowledge Vault built byDavid Vivancos 2025