Artificial Intelligence in the Second Machine Age
The advancement of artificial intelligence (AI) in this second machine age is, and will continue to be, the defining feature of this age. With smart machines everything changes. This department tracks what is happening on the AI front and how this technology is changing every area of our lives.
UC Berkeley computer scientists develop smarter, enhanced data-driven colorization system for graphic artists.
Method for modeling neural networks’ power consumption could help make the systems portable.
CAMERA researchers capitalize on their Multi-Tiered Iterative Phasing approach to determine molecular structure of proteins and viruses from X-ray free electron laser data.
Click Here to Get Your Copy of This Article Will Robots Ever Achieve Genuine Consciousness? How will we know? Paul L. Nunez Consciousness is the most familiar aspect of our lives, but it is also the most mysterious. One mystery is the question of whether or not we can...
“Emulating Bilingual Synaptic Response Using a Junction-Based Artificial Synaptic Device” – ACS Nano One of the greatest challenges facing artificial intelligence development is understanding the human brain and figuring out how to mimic it. Now, one...
Machine learning to increase efficiency of farming by predicting the interaction between the plant and environment
Machine learning methods will be tested in arable farming, greenhouse cultivation and plant breeding.
A deep-learning algorithm developed by EPFL scientists can generate melodies that imitate a given style of music. The “deep artificial composer” could one day generate convincing music for multiple instruments in real time, with applications ranging from video games to helping composers in the creative process.
Researchers report artificial intelligence systems are able to predict a person’s life span by reviewing CT images of their organs.
NEC and Tokyo Institute of Technology use AI to dramatically increase image clarity under severe conditions: Automatically combines visible and non-visible images.
Neural networks could be implemented more quickly using new photonic technology.
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