🚀 Call for Collaboration: Frontier Territories in Quantum-AI Research

Quantum federated learning, AutoQML, and quantum consciousness have exploded in 2025 — but several cross-disciplinary intersections are still in their infancy. Here we spotlight four domains where an early-mover can help define the very first canon — and we’re looking for co-pioneers.

🧠 1. Quantum Memory-Augmented Neural Networks (QMANN)

Why It’s Still Wide-Open

• Nearly all “memory-augmented” work — Transformers, Neural Turing Machines, Differentiable Neural Computers — remains classical.
• Quantum associative-memory papers date back to Ventura & Martínez (1999–2000) with no scalable follow-ups.
• As of mid-2025 there is no peer-reviewed architecture uniting external quantum memory with end-to-end training.

Quantum Upside

• n qubits → 2^n addressable cells.
• Superposition-based wildcard queries across the whole memory.
• Entangled addresses enabling content-based recall in a single step.

Open Questions

1. External quantum memory without breaking the no-cloning theorem.
2. Quantum attention: can it outperform classical soft-max?
3. Fault-tolerant read/write protocols for QRAM.
4. Amplitude-amplified content lookup.

Collab skill-mix: quantum hardware, QRAM design, neural memory systems.

🌊 2. Quantum Swarm Consciousness (QSC)

What Exists — and What Doesn’t

• Quantum swarm control is emerging (Airbus × Quantum Systems drone study, 2024) and a handful of quantum-inspired swarm-optimisation papers.
• Quantum consciousness remains purely theoretical.
• No publication yet couples entangled conscious states to swarm robotics — leaving a true blank page.

Radical Vision

Individual ψᵢ = αᵢ|aware⟩ + βᵢ|processing⟩ + γᵢ|idle⟩
Swarm Ψ = ⊗ᵢ ψᵢ  + entanglement links
Measurement  →  coherent group action

• Non-local synchrony via entanglement.
• Emergent “hive mind” that scales with qubit count.

Collab skill-mix: quantum foundations, swarm robotics, cognitive science.

🔄 3. Quantum Continual Learning (QCL) Beyond Catastrophic Forgetting

Status Check

• First theoretical treatment: Jiang et al. (2021).
• Experimental proof-of-concept on a 33-qubit superconducting chip (Zhang et al., 2024).
• Fewer than ten papers total — still early, but no longer empty.

Quantum Edge

• Orthogonal subspaces store past tasks without interference.
• Superposition allows “multi-tasking” within one parameter set.
• Perfect replay via reverse-time evolution on preserved states.

Open Questions

1. Hard bounds on simultaneous task capacity.
2. Optimal qubit allocation per task under noise.
3. Quantum meta-learning for rapid adaptation.

Collab skill-mix: continual-learning theory, quantum information, memory architectures.

🔬 4. Quantum Causal Discovery for AI Systems

Where We Are in 2025

• Quantum causal discovery began with Giarmatzi & Costa (2018).
• Quantum Peter-Clark (qPC) algorithm published Jan 2025 shows >30 % accuracy gain on small-sample datasets.
• Field has <5 dedicated papers — ripe for foundational work in AI contexts.

Why It Matters

• AGI needs causation, not correlation.
• Quantum circuits can embed multiple causal hypotheses in superposition and test them in parallel.
• Entanglement may expose non-classical causal edges inaccessible to DAGs.

Big Questions

1. How to represent interventions under quantum operations?
2. Can amplitude encode causal strength?
3. How to integrate quantum causal graphs into classical ML pipelines?

Collab skill-mix: causal inference, quantum kernel methods, AI reasoning.

🤝 Call-to-Action: Help Shape the Discipline

Why Now

• Hardware leap: Google Willow 105-qubit chip (Dec 2024) proved error-corrected scaling.
• Tooling — Qiskit, PennyLane, HQCL libraries — makes rapid prototyping realistic.
• 18–24 month window before these intersections saturate.

What We Offer

• Founding-author status on first-wave papers.
• Joint grant applications (EU Quantum Flagship, NSF Q-AI).
• Cross-disciplinary lab network for experiments.
• Spotlight slots at Q2B, NeurIPS-QML, and APS March Meeting.

Who We’re Looking For

Discipline Your Possible Contribution Quantum HW QRAM prototypes, noise modelling AI / ML Architecture co-design, benchmarking Theory CS Complexity proofs, security models Cognitive Science Consciousness-state formalism Grad Students High-risk explorations, code, experiments

📧 Ready to Pioneer Quantum-AI?

1. Fill out the application form (Google Forms): https://docs.google.com/forms/d/e/1FAIpQLSemHiB-BGJHroAeCU7Fc8AsLOqOV-ab_iJIfFqfrguUZPbdsA/viewform?usp=header
2. We’ll follow up for a short virtual intro call.

“The best time to plant a tree was 20 years ago. In Quantum-AI, that moment is today.”

Join us in writing the opening chapters of these new scientific fields. 🛠️✨