Hybrid AGI Architecture Generator
Generated architecture candidates
2028-2036
Photonic + Neuromorphic Perception Fabric
Use photons for high-bandwidth movement and spikes for low-power embodied sensing, with electronic models handling planning.
Photonic interconnectsevent-driven sensorsspiking processorsdigital planner
Strengths
- Low-latency perception
- energy-efficient edge autonomy
- strong robotics fit
Weaknesses
- Difficult training stack
- limited high-level reasoning
- hardware integration risk
Breakthroughs
- Common compiler for optical/spiking pipelines
- robotics benchmark suite
- robust sensor fusion
Could unlock large-scale autonomous infrastructure, disaster response, and distributed sensing.
Feasibility vector
Evidence72
Reproducibility64
Validation63
Engineering58
Thermodynamics88
Scalability61
Timeline realism66
Hype risk44
2026-2032
Electronic Foundation Model + Optical Memory Fabric
Keep digital training and reasoning while attacking the memory and communication wall with optical data movement.
GPUs/TPUsoptical interconnectsretrieval memoryagent runtime
Strengths
- Near-term deployability
- clear datacenter value
- strong compatibility with current models
Weaknesses
- Still power hungry
- depends on packaging economics
- not a new learning paradigm alone
Breakthroughs
- Co-packaged optics at scale
- memory-aware model architectures
- routing by energy cost
Could materially extend scaling by lowering inference and memory movement costs.
Feasibility vector
Evidence84
Reproducibility76
Validation74
Engineering81
Thermodynamics82
Scalability77
Timeline realism78
Hype risk36
2027-2040
Embodied Multi-Agent Research Civilization
Treat AGI as an institution of embodied and digital agents with roles, checks, experiments, and causal world models.
Roboticsmulti-agent systemshuman institutionssimulation worldsverification agents
Strengths
- Real-world grounding
- organizational scalability
- safety through role separation
Weaknesses
- Coordination failures
- hard governance
- slow physical iteration
Breakthroughs
- Reliable agent protocols
- robotics data engines
- formal audit trails
- human-AI governance
Could become a practical civilization-scale intelligence infrastructure.
Feasibility vector
Evidence78
Reproducibility70
Validation66
Engineering72
Thermodynamics70
Scalability68
Timeline realism64
Hype risk48
2026-2035
Verified Recursive Self-Improving Agent Lab
Permit self-improvement only through bounded proposals, reproducible tests, formal checks, and rollback-ready deployment.
code agentsformal verificationeval harnessessandboxed toolshuman approval gates
Strengths
- Direct path to accelerated R&D
- auditable improvement loop
- can compound software progress
Weaknesses
- Highest alignment burden
- eval gaming
- tool boundary risk
Breakthroughs
- Capability-control evals
- verified code generation
- corrigible agent protocols
Could accelerate science dramatically if controlled, or amplify failure modes if governance is weak.
Feasibility vector
Evidence69
Reproducibility61
Validation54
Engineering67
Thermodynamics75
Scalability62
Timeline realism50
Hype risk72