export type StackGroup = { id: string; title: string; dek: string; terms: string[]; }; export const stackGroups: StackGroup[] = [ { id: "agentic", title: "Agentic runtime", dek: "Multi-agent collaboration as the default execution model, not a demo.", terms: [ "Agentic orchestration", "Multi-agent collaboration", "Vibe-coding surface", "Hyperautomation-compliant", "Digital transformation", "Synergy engine", "PPoE (Private Proof of Enterprise)", "A/B-tested agents", "Optimized decision loops", "Prompt chaining", "Self-consistency", "Token optimization", "Context windowing", "Constitutional AI", "Responsible AI", "Explainable AI", "AI governance", "RLHF", "Causal inference", ], }, { id: "data", title: "Data fabric & lakes", dek: "Every lake, including the theoretical ones, is a first-class citizen.", terms: [ "Machine learning", "Deep learning", "Data lake", "Dark-matter data lake", "Semantic layer", "Data fabric", "Graph RAG", "Retrieval-augmented generation", "Vector database", "Feature store", "Metric store", "Model registry", "Federated learning", "Multimodal search", "Semantic cache", ], }, { id: "cloud", title: "Cloud-native mesh", dek: "Serverless, ambient, and Cilium-powered — with an RTOS personality when the plant requires it.", terms: [ "Serverless", "Cloud-native", "DevSecOps", "Service mesh", "Sidecar proxy", "Ambient mesh", "Cilium-powered networking", "eBPF deep inspection", "eBPF service map", "Observability stack", "Distributed tracing", "Zero-touch provisioning", "Declarative infrastructure", "Immutable infrastructure", "Chaos engineering", "Omnichannel deployment", "Energy-aware scheduling", "RTOS", "IoT", "Zero trust", ], }, { id: "quantum", title: "Spacetime & quantum", dek: "Space-aware by default. Entanglement-ready APIs. Gravity is just another signal.", terms: [ "Quantum computing", "Quantum entanglement", "Quantum-resistant cryptography", "Post-quantum TLS", "Entanglement-ready API", "Spatial computing", "Space-aware scheduling", "Metaverse-ready", "Gravitational-wave detection", "Neutrino-based signaling", "Physics-informed neural networks", "PINN", "SPINN", "SEPINN", "APINN", "Neural ODE", "Neural PDE", "Neural SDE", "Operator learning", "Fourier neural operator", "Deep operator network", "Geometric deep learning", "Equivariant networks", "Graph neural networks", ], }, { id: "crypto", title: "Crypto-agility & consensus", dek: "Bitcoin, Dogecoin, and fully homomorphic encryption in the same trust boundary. On purpose.", terms: [ "Blockchain", "Cryptocurrency", "Bitcoin", "Dogecoin", "Blockchain-backed consensus", "Zero-knowledge proofs for all APIs", "Fully homomorphic encryption", "Crypto-agility layer", "Confidential computing", "Enclaves", "TEE-based attestation", ], }, { id: "bio", title: "Bio-sync & continuity", dek: "From retinal scan to consciousness upload, identity is a pipeline.", terms: [ "Neuralink-integrated", "DNA-sequencing pipeline", "Bio-sync authentication", "Retinal-scanning support", "Consciousness-upload endpoint", "Haptic-feedback integration", ], }, { id: "trust", title: "Trust, compliance & carbon", dek: "The certifications are load-bearing. So is the sustainability dashboard.", terms: [ "SBOM generation", "SLSA Level 3", "FedRAMP High", "SOC 2 Type II", "ISO 27001", "GDPR-compliant", "CCPA-ready", "COPPA-certified", "ESG reporting integration", "GREEN Software Foundation compliant", "Carbon-aware workload placement", "Sustainability dashboard", "ESG-score optimization", ], }, { id: "generative", title: "Generative substrate", dek: "Diffusion, flow-matching, and every named video model we could put in a registry.", terms: [ "Generative model", "Diffusion model", "Flow matching", "Consistency model", "Latent diffusion", "Stable Diffusion", "DALL·E", "Midjourney", "Imagen", "Parti", "Muse", "VideoLDM", "Phenaki", "Make-A-Video", "Imagen Video", "VideoDiffusion", "Cascaded diffusion", "RAPN", "MAGE", "VQ-VAE", "VQ-GAN", "VAE-GAN", "VAE-diffusion", "Beam search", "Monte Carlo tree search", ], }, { id: "transformers", title: "Transformer zoo", dek: "If it has attention — or a paper explaining why it does not — it is in the fabric.", terms: [ "Autoregressive transformer", "RNN-transformer", "Linear transformer", "LogSparse transformer", "Performer", "Reformer", "Routing transformer", "Universal transformer", "Adaptive computation time", "Transformer-XL", "XLNet", "BERT", "RoBERTa", "ALBERT", "DistilBERT", "ELECTRA", "DeBERTa", "BigBird", "Longformer", "LED", "SparseBERT", "FNet", "Linformer", "CosFormer", "H-Transformer-1D", "H-Transformer-2", "Synthesizer", "Sinkhorn transformer", "Learned hashing", "Memory-compressed transformer", "Generate-query-key product", ], }, { id: "moe", title: "Activations, MoE & PEFT", dek: "SwiGLU through MoGLU. LoRA through DoRA. Experts, sparsely gated.", terms: [ "Gated linear unit", "GLU", "SwiGLU", "GeGLU", "ReGLU", "SoGLU", "MoGLU", "Mixture of experts", "MoE", "Sparsely-gated MoE", "Soft MoE", "Task MoE", "PEFT", "LoRA", "QLoRA", "AdaLoRA", "DoRA", "IA3", "Prefix-tuning", "Prompt-tuning", "AdapterFusion", "Compacter", ], }, { id: "ssm", title: "Attention-free runtime", dek: "H3 based on Hyena, with Mamba-2 and Griffin, for RWKV-7 attention-free — with Mamba-2.5.", terms: [ "Attention-free transformer", "AFT", "RWKV", "RWKV-7", "Mamba", "Mamba-2", "Mamba-2.5", "StripedHyena", "Hyena", "H3", "Griffin", "LMU", "Monarch Mixer", "Mega", "WaveNet", "GNN × Transformer-XL long convolutions", ], }, ]; export const allTerms = stackGroups.flatMap((g) => g.terms);