Contemporary AI systems still lack high-level cognitive and learning skills. With the help of digital neuromorphic chips, scientists now aim to accurately model how humans can quickly and easily learn a cognitive task, such as a new board game.
Originally published June 2017, IEEE Spectrum
Neurotechnologies have reached to a point of interacting with the physical, digital and social world. That fundamental truth has opened a wealth of interest in neuroscience, in leadership sectors far beyond medicine.
Read the rest of this entry…
| M | T | W | T | F | S | S |
|---|---|---|---|---|---|---|
| « Jan | ||||||
| 1 | 2 | 3 | ||||
| 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| 11 | 12 | 13 | 14 | 15 | 16 | 17 |
| 18 | 19 | 20 | 21 | 22 | 23 | 24 |
| 25 | 26 | 27 | 28 | 29 | 30 | |
Exoskeleton Retinal prosthesis human to human interface Connectomics Graph Theory neuroethics tCS CPG Biometrics Plasticity Trajectories systems-neuroscience music recommendation music neuroscience Deep Learning Interpretability Learnable Filters network neuroscience multiplexing Conferences music perception brain networks modularity community detection brain to brain interface transcranial direct current stimulation music Sparse neurons Noise Deep Brain Stimulation LFP Neural coding TMS Computational Neuroscience Brain-inspired Computing Neuroimaging Wavelets Neuro-inspired Computing neuroprosthetics Bionics Machine Learning neural recordings EEG Information Theory Dimensionality Reduction Modelling Neural Networks Clustering Statistical Analysis Neurophysiology Spike Sorting Brain Research Brain Interfaces
WP Cumulus Flash tag cloud by Roy Tanck requires Flash Player 9 or better.
IEEE Spectrum Biomedical
Neurobot via RSS