We will discuss word embeddings this week. Word embeddings represent a fundamental shift in natural language processing (NLP) ...
For more than 50 years, scientists have sought alternatives to silicon for building molecular electronics. The vision was ...
These are not “nice-to-haves”; they are prerequisites for distributed cognition, operating at machine speed. As Tatipamula and Cerf point out, the network can no longer simply host intelligence. It ...
Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
1 Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, School of Computer Science, Shanghai Jiao Tong University, Shanghai, China 2 National Key Laboratory of ...
Abstract: Recent advancements in deep learning for semantic communication have been significant, yet fixed-length encoding techniques struggle to capture the complex and variable nature of semantic ...
This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...
If you want to improve the way Windows Search works on your computer, we recommend you use Semantic Search. It is a new feature introduced in Windows 11, allowing Windows to leverage AI to search ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback