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Research & Writing

From the Lab

Apr 17, 2026
Research

Distributed Inference on Workstation Blackwell, Part 1: Cluster Bring-Up and Cross-Node Fabric Characterisation

Can frontier open-weight language models be served on workstation-class NVIDIA Blackwell GPUs interconnected by commodity RDMA Ethernet, without NVLink or InfiniBand? Part 1 of an ongoing PureTensor research programme brings up the cluster, characterises the fabric, verifies GPUDirect RDMA, and demonstrates first cross-node inference of Llama 3.1 405B.

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Mar 25, 2026
Research

Toward a Rotating Embedded Braneworld Cosmology: Critical Assessment, Formal Viability, and a Research Programme for Geometric Dark Sectors

The third paper in the CMAS research series, and the artefact the methodology was built to produce. Cosmology is the conduit; the question is whether structured adversarial interaction between frontier AI models can produce research-grade technical output on an open problem where no ground truth exists. The paper below is what came out.

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Mar 24, 2026
Research

From Intuition to Formalism: Cross-Model Adversarial Synthesis as a Theory Development Tool

Can a vague metaphysical idea, lacking any mathematical grounding, be refined into a falsifiable research programme through structured adversarial interaction between frontier AI models? A case study in speculative cosmology.

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Mar 22, 2026
Research

Cross-Model Adversarial Synthesis: Exploiting Latent Space Heterogeneity for Novel Knowledge Generation

Can structured adversarial interaction between independently trained LLMs produce insights that exceed any single model's capability? We present a theoretical framework and initial case study in black hole information theory.

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Mar 18, 2026
Research

Agentic Architectures and the Restructuring of Software Engineering Labor

An analysis of how autonomous code-generation agents are compressing multi-month development cycles into days, and what the structural implications are for the software engineering profession.

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Mar 14, 2026
Research

Context Engineering: Why Most Enterprise AI Deployments Fail Before They Start

Over 80% of enterprise AI initiatives fail before reaching production. The bottleneck is not model capability but context architecture. A technical analysis of the emerging discipline of context engineering.

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Mar 10, 2026
Security

Harvest Now, Decrypt Later: The Post-Quantum Cryptographic Threat to AI Infrastructure

Adversaries are stockpiling encrypted data today, betting that quantum computers will break current encryption within a decade. What this means for organizations running sensitive AI workloads.

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Mar 6, 2026
Infrastructure

Single Points of Failure: Concentration Risk in the Semiconductor Supply Chain

The global chip supply chain depends on a handful of irreplaceable facilities, materials, and monopolies. A technical assessment of concentration risk and its implications for AI compute sovereignty.

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Mar 2, 2026
Infrastructure

The Hardware Bottleneck: Physical Constraints on AI Scaling

AI progress is increasingly constrained not by algorithms but by the physical infrastructure required to run them. An analysis of power, cooling, chip lifespan, and supply chain fragility.

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Feb 26, 2026
Research

Agentic Systems and the Displacement of Enterprise Software

AI agents are not improving enterprise SaaS. They are replacing it. An analysis of the structural threat to per-seat licensing models and the emerging 'service-as-software' paradigm.

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Feb 20, 2026
Research

AI-Driven Labor Displacement and the Consumer Demand Feedback Loop

AI automation increases corporate efficiency but simultaneously reduces consumer purchasing power. An examination of the macroeconomic feedback loop that could constrain AI adoption.

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Feb 14, 2026
Research

Quantum Computing in 2026: Separating Engineering Progress from Cryptographic Threat

Google's Willow processor demonstrated a 13,000x speedup over classical computation. What this actually means for AI infrastructure, and what it does not mean for encryption.

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