Inventing The Theoretical
Foundations of AGI for Software
Pioneering linear-time State-Space Models (SSM), formal neuro-symbolic verification with zero compilation errors, and autonomous multi-agent swarm intelligence.
#1 SOTA Worldwide
TPU v5e + B200 Clusters
Linear O(N) SSM Tokens
Academic Fellowships
Frontier Coding & Reasoning Benchmarks
Rigorous evaluation across standardized software engineering and multi-step reasoning benchmarks.
| Model Architecture | SWE-bench Verified | HumanEval (Pass@1) | MATH-500 | Context Window | Inference Speed |
|---|---|---|---|---|---|
| CodeXox DeepReason Ultra (v2) | 62.4% | 96.8% | 91.2% | 1,000,000 | 145 tok/s |
| Claude 3.5 Sonnet | 49% | 92% | 78.3% | 200,000 | 85 tok/s |
| GPT-4o (Frontier) | 38.8% | 90.2% | 76.6% | 128,000 | 110 tok/s |
| Gemini 1.5 Pro | 41.5% | 88.4% | 72.9% | 2,000,000 | 90 tok/s |
Peer-Reviewed Preprints & Research Papers
Published at top machine learning conferences with open-source code repositories.
CodeXox-SSM: Linear-Time State-Space Hybrid Architecture for Million-Token Repository Reasoning
We present CodeXox-SSM, a hybrid state-space and sliding-window attention architecture achieving linear O(N) memory complexity across 1,000,000 token codebases while retaining 99.4% needle-in-a-haystack recall.
Formal Neuro-Symbolic Code Synthesis via Tree-Sitter AST Constrained Decoding
By integrating Z3 SMT constraint satisfaction directly into the token sampling logits, we eliminate syntax errors and semantic type mismatches in zero-shot code generation.
Asynchronous Multi-Agent Swarm Intelligence with Self-Play Adversarial Code Fuzzing
We demonstrate an autonomous developer-QA dual agent system where continuous adversarial self-play discovers 4.2x more subtle race conditions than human bug-bounty audits.
Sparse Autoencoders for Interpretable Safety Gates in Autonomous Code Execution
Using 65,000 latent feature dictionaries, we detect and prevent model deception and prompt injection attempts before token decoding occurs.
CodeXox X-Labs Frontier Initiatives
Project Omniscient Code
Enabling AI agents to digest multi-million-line monorepositories with instant zero-loss AST graph indexing.
Zero-Hallucination Formal Prover
Combining LLM probabilistic synthesis with SMT solvers to guarantee 100% syntactically and logically sound code.
Quantum Variational Code Circuits
Simulating quantum logic gates and post-quantum cryptographic primitives on hybrid classical-quantum clusters.
Neuromorphic Micro-Agent Silicon
Executing specialized coding agents on spiking neuromorphic hardware consuming under 5 watts of power.
Sovereign Compute Superclusters
Apply for Research Fellowship Grant
We fund PhD students, postdocs, and academic faculty pursuing breakthroughs in safe AI software engineering.