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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);
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