ABSTRACT: A new conceptual framework is presented that unifies Gödel’s incompleteness theorems with practical physical modeling through information-theoretic analysis. The method of variables with ...

The familiar fight between “mind as software” and “mind as biology” may be a false choice. This work proposes biological computationalism: the idea that brains compute, but not in the abstract, symbol ...

Deep learning emerges as an important new resource-intensive workload and has been successfully applied in computer vision, speech, natural language processing, and so on. Distributed deep learning is ...

Neural Oscillatory Interference Networks for Inherently Interpretable Deep Learning Computation Note: This README is an ultra-condensed summary of the research reports published by Unpatentable.org.

Artificial intelligence is consuming enormous amounts of energy, but researchers at the University of Florida have built a chip that could change everything by using light instead of electricity for a ...

Autograph first extracts loops and builds dependency graphs capturing instruction semantics and data flow, which are then converted into embeddings by Graph Neural Network. These embeddings are then ...

"We have demonstrated that it is impossible to describe all aspects of physical reality using a computational theory of quantum gravity," says Dr. Faizal. "Therefore, no physically complete and ...

Abstract: Vehicular edge-cloud collaborative computing is pivotal for addressing the demands of computation-intensive and latency-sensitive applications in future intelligent transportation systems.