6 papers
Polysemy of Synthetic Neurons Towards a New Type of Explanatory Categorical Vector Spaces
Michael Pichat, William Pogrund, Paloma Pichat +6
The polysemantic nature of synthetic neurons in artificial intelligence language models is currently understood as the result of a necessary superposition of distributed features w…
Intra-neuronal attention within language models Relationships between activation and semantics
Michael Pichat, William Pogrund, Paloma Pichat +4
This study investigates the ability of perceptron-type neurons in language models to perform intra-neuronal attention; that is, to identify different homogeneous categorical segmen…
Synthetic Categorical Restructuring large Or How AIs Gradually Extract Efficient Regularities from Their Experience of the World
Michael Pichat, William Pogrund, Paloma Pichat +6
How do language models segment their internal experience of the world of words to progressively learn to interact with it more efficiently? This study in the neuropsychology of art…
The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition
Michael Pichat, William Pogrund, Armanush Gasparian +5
This article investigates, within the field of neuropsychology of artificial intelligence, the process of categorical segmentation performed by language models. This process involv…
Neuropsychology of AI: Relationship Between Activation Proximity and Categorical Proximity Within Neural Categories of Synthetic Cognition
Michael Pichat, Enola Campoli, William Pogrund +7
Neuropsychology of artificial intelligence focuses on synthetic neural cog nition as a new type of study object within cognitive psychology. With the goal of making artificial neur…
Psychology of Artificial Intelligence: Epistemological Markers of the Cognitive Analysis of Neural Networks
Michael Pichat
What is the "nature" of the cognitive processes and contents of an artificial neural network? In other words, how does an artificial intelligence fundamentally "think," and in what…