Artificial intelligence has not merely accelerated computation or a type automation. It is a new way of thinking and how knowledge, uncertainty, and decision-making are structured. This is a key point I have made in the past through my notion of Cognology: that AI is cognitive compared to technologies as machines.
I believe that the AI advantage translates directly into market power. Firms that learn faster and use probabilities and prediction most efficiently will dominate and slow learners will fail. Think of prediction as a new type of capital.
At Luminalis AI we develop clinical decision resources using advanced machine learning. Our first spin out is Elarin Health, a predictor of falls in the frail elderly, and which offers fully ambulatory autonomy and 24 to 48 hour falls probabilities. We don’t predict falls events, but the constellation of features in an individual’s life that may signal a fall is emerging.
Putting this into the context of the current AI revolution, I suggest we are in the early stages of a Bayesian paradigm shift. This is an epistemic reordering in which probability, prediction, and adaptive learning displace the deterministic logic.
I can betray an interest here. I did my MA thesis on modal logics with a focus on decision making on boundary conditions and under uncertainty. Uncertainty is not a defect, it is a feature.