Beyond the GPU Barrier
The architectural shift from GPU-centric to CPU-first AI systems.
The Algorithmic Revolution
Probabilistic sparsity, SLIDE, and the BOLT engine for sub-linear deep learning.
High-Fidelity Runtimes
Computational sovereignty and running BF16 full-precision on CPUs with Ziroh Labs.
Quantization & Democratization
The impact of llama.cpp, GGML, and GGUF on local AI accessibility.
Rust for Systems ML
Memory-safe, high-performance frameworks like Candle and Burn.
Silicon Giant Optimizations
How Intel and AMD are baking AI acceleration (AMX, ZenDNN) into the processor.
Efficient ML Trends
A survey of modern inference runtimes, compilers, and low-level libraries.
VSA & HDC
Algebraic reasoning and neuro-symbolic computing in high-dimensional spaces.
BitNet & 1.58-bit LLMs
The radical shift to ternary weights and the elimination of multiplication in AI.
CNL & Formal Semantics
Bridging natural language ambiguity and formal logic for auditable agent reasoning.
AI-Native Languages
Rethinking programming paradigms for probabilistic, agentic, and self-optimizing systems.
Brain-Inspired Computing
Jeff Hawkins' Thousand Brains Theory and Numenta's path to biological intelligence.
Liquid Neural Networks
MIT CSAIL and Liquid AI's continuous-time systems for adaptive and efficient intelligence.
Neuromorphic Computing
Event-driven AI and Spiking Neural Networks (SNNs) for extreme energy efficiency.
Active Inference
Karl Friston's Free Energy Principle and the mathematical foundation for proactive agents.
Energy-Based Models
Yann LeCun's alternative to probabilistic modeling through compatibility functions.
World Models & JEPA
Predictive architectures for autonomous agents that learn, reason, and plan in latent spaces.
KAN Networks
A radical alternative to MLPs using learnable activation functions on weights for better interpretability.
Neuro-Symbolic AI
The convergence of connectionist pattern recognition and symbolic logical reasoning.
Conceptual Spaces
Geometric information representation bridging the gap between neurons and symbols.
Ontologies & KG
Structured knowledge and common-sense reasoning via Cyc, WordNet, and SUMO.
Formal Logic & Solvers
Deterministic reasoning using SMT solvers like Z3 and description logics.
Theorem Proving
Integrating AI with formal proof assistants like Lean, Coq, and Isabelle.
Verification Languages
Proving system correctness using TLA+, Alloy, and formal methods.
Causal Inference
Moving beyond correlation to causal reasoning and counterfactuals with Judea Pearl's theories.
Cognitive Architectures
Unified models of the mind like SOAR and ACT-R for integrated intelligence.
Probabilistic Programming
Codifying uncertainty and Bayesian inference using Stan, Pyro, and Edward.
Geometric Deep Learning
Unifying AI architectures through symmetry, invariance, and graph-based representations.
Physics-Informed AI
Integrating physical laws as hard constraints into neural network training (PINNs).
Program Synthesis
Automatically constructing provably correct code from high-level specifications.
Differentiable Logic
Merging logical operations with gradient descent via Logical Neural Networks (LNN).
Explainable AI (XAI)
Creating trust through transparency, auditable reasoning, and interpretability.
Verifiable Computing
Cryptographic proofs (ZKPs) and zkML to ensure AI computation integrity and privacy.
Small Language Models
Model distillation and specialized 3B-parameter "reasoning kernels" for edge deployment.
Decentralized AI (DeAI)
Removing centralized gatekeepers via Bittensor, Petals, and federated learning protocols.
Formal AI Safety
Moving beyond RLHF to mathematical alignment guarantees and safety shielding.
Multi-Agent Systems
Formal coordination, consensus protocols, and epistemic redundancy in agent ecosystems.
Information Theory
Intelligence as compression: Kolmogorov complexity and the bedrocks of universal induction.
European Initiatives
Key research groups and projects in Switzerland and Europe focused on efficient and neuro-symbolic AI.