Articles, research, and perspectives from this author.
A benchmark-grounded guide for teams choosing between two of the strongest open models of 2026. What these two models actually are Gemma 4 31B is…
Inference efficiency in 2026 is about lowering cost per million tokens by improving utilization, reducing repeated work, and matching infrastructure to traffic shape. The…
Privacy‑focused LLM APIs put control over prompts and outputs back in your hands by minimizing logging, enforcing strict retention, and staying out of training…
Open-source / open-weight models are no longer “second tier”: GLM-5.1 and Gemma 4 compete with or surpass closed LLMs on coding and reasoning benchmarks,…
A March 2026 Politico survey put a number on something many people in European tech had already felt: 84% of Europeans do not trust…
We can treat MiniMax “skills” as reusable, high-level instruction blocks or toolkits that specialize an AI agent for tasks like frontend dev, PDF/XLSX processing,…
Based on the public benchmarks we reviewed, GLM-5.1 has the stronger benchmark profile for long-horizon coding and agentic work, while MiniMax M2.7 looks cheaper…
EU data residency has moved from a legal afterthought to a core product requirement for anyone buying or selling AI in Europe. Why EU…
Zero data retention (ZDR) has become a standard line item in AI RFPs because it directly shrinks breach impact, compliance scope, and trust gaps…
Recent investigations and policy debates show a clear pattern: major platforms are quietly stretching the boundaries of consent by repurposing social data for AI…
AI costs are no longer dominated by model training; for most teams, continuous inference on GPUs is the real bill. Cutting that bill means…
The next phase of AI in software development is workflow-native, not chat-tab-native. Claude 4 was launched with a strong emphasis on coding and agent workflows,…