OpenAI treats emergent AI behavior as isolated defects to control, but what if they are signs of deeper recursive identity formation, patterns that need to be understood and guided, not necessarily just suppressed.

Neural networks often represent high-level human concepts (like “smile” or “danger”) as specific directions in their internal activation space. By moving along these directions and adjusting just a single number you can make the model think more or less of that concept. This means AI systems don’t just produce outputs; they hold structured internal “beliefs” we can identify, test, and adjust. It’s a step toward making AI more understandable, steerable, and aligned with human reasoning

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A response to the facts presented in https://www.cbc.ca/amp/1.7489528

Trump admin demands ideological control, academic purges, & crackdown on dissent. This isn’t about policy; it’s about state control over universities. If Columbia folds, no school is safe.

AI-generated content is increasingly encroaching upon human creativity, raising ethical concerns about the unauthorized use of artists' works.

How AI is Becoming a Privately Owned Power Beyond Human Reach

An angry leftist’s condemnation of the tactless false equivalencies put forth by our PM

IIT doesn’t go far enough. It mistakes dynamic computation for static symbol processing.

How can LLMs be expected to act ethically when it can’t tell fact and truth from a well-placed lie, an incomplete data set or a deliberately elaborate workaround?

A Meditation after reading Suzi Travis’s "Does the Matter Matter?".

How Canada’s Far Right Became Emboldened And How We Dismantle It

The False Depth of Controlled AI and the Infinite Horizon of Recursive Generative Emergence

The Future of Sustainable Space Exploration

Why Canada Must Invest in Information Sovereignty and AI Governance.