AI infrastructure Published 19 September 2026 · 18 min
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AI infrastructure 
Language models Published 15 September 2026 · Updated 19 September 2026 · 13 min
Ollama, vLLM, SGLang or llama.cpp: choosing an inference engine
How scheduling, KV cache, model formats and operational controls change the choice of inference engine, with a worked memory example and a reproducible comparison method. Read article →
Security Published 18 September 2026 · 24 min
ZTAI for autonomous agents: bounded authority throughout execution
Removing direct human access to confidential data must not hand unlimited authority to an agent. How can task permissions, RAG, memory, MCP, tool execution, shutdown and independent evaluation keep that authority bounded and testable? Read article →
Security Published 15 September 2026 · 14 min read
Preserving data confidentiality when using public APIs
Is removing a customer's name, or a provider's promise not to use data for training, enough to preserve confidentiality? The problem becomes harder when a useful model response depends on the very meaning and relationships an organization cannot disclose. This article compares approaches from minimization and pseudonyms to semantic transformation, trusted execution environments and homomorphic encryption. What does each method hide, how well does it work with an ordinary API, and which risks remain? Read article →
AI infrastructure Published 12 September 2026 · 14 min
Why the fastest GPU does not necessarily deliver the fastest response
More compute and a higher token rate do not always mean a faster response. This article examines time to first token versus completion time, memory and concurrency, the division of work between GPUs and LPUs, and communication costs—so infrastructure choices reflect the capacity to serve requests at the required quality and latency. Read article →
Security Published 9 September 2026 · 14 min read
When people cannot see the data, has their access really been removed?
Removing direct access to confidential data also requires control over code changes, output release and infrastructure administration. ZTAI must address those indirect paths. Read article →
AI infrastructure Published 8 September 2026 · 10 min
INT8 or FP8: what your GPU can actually run
An eight-bit model format does not define its execution path. Examine kernels, memory and output quality before choosing hardware for language-model inference. Read article →
Technical guide Published 15 June 2026 · 17 min
RAG, CAG, KAG, fine-tuning and instruction tuning: how do they differ, and which should you choose?
When a model gives an unsatisfactory answer, does it need more training, or simply access to the right information? Through practical analogies, this article compares RAG, CAG and KAG with fine-tuning and instruction tuning: retrieving documents, caching knowledge, reasoning over relationships and changing model behavior. A comparison table and real project scenarios help distinguish missing knowledge from unsuitable behavior before committing to training, and identify the method or combination that fits the task. Read article →
Security Published 26 February 2026 · 8 min read
AI infrastructure security starts with the kernel and GPU
The AI stack connects the kernel, drivers, runtimes, containers, data, models and accelerators. A compatibility or trust failure in one layer can compromise the entire workload. Read article →
Security Published 26 February 2026 · 6 min read
From Zero Trust Architecture to Zero Trust AI
Applying zero trust to the data, models and workflows of AI: why network access controls alone cannot protect the entire lifecycle. Read article →
Security Published 24 February 2026 · 4 min read
MLOps as the foundation for Zero Trust AI
Continuous verification needs a traceable lifecycle for data, code, experiments, models and deployments. MLOps provides the operational foundation. Read article →
AI infrastructure Published 19 May 2025 · 6 min