What happens when digital eyes get the brains to match?
Facebook has replaced the man Mark Zuckerberg recruited to run its artificial intelligence research, filling the role with an outsider who will take a bigger role at the company as it puts more AI into its News Feed and other products.
Detectron is Facebook AI Research’s software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework.
The AI boom offers Chinese chipmakers a chance to catch up after years of lagging behind.
Design is major stepping stone toward portable artificial-intelligence devices.
First off, Eager Execution for TensorFlow is now available as a preview.
Using Google Clips to understand how a human-centered design process elevates artificial intelligence.
DeepMind: Consider the simple task of going shopping for your groceries. If you fail to pick-up an item that is on your list, what does it tell us about the functioning of your brain? It might indicate that you have difficulty shifting your attention from object to object while searching for the item on your list. It might indicate a difficulty with remembering the grocery list. Or it could it be something to do with executing both skills simultaneously.
Everyone who has been remotely tuned in to recent progress in machine learning has heard of the current 2nd generation artificial neural networks used for machine learning. These are generally fully connected, take in continuous values, and output continuous values. Although they have allowed us to make breakthrough progress in many fields, they are biologically inn-accurate and do not actually mimic the actual mechanisms of our brain’s neurons.
AI scientists try to trick smart systems into making dumb gaffes.
The message to executives is clear: it’s time to understand and leverage trends in automation and artificial intelligence.
Cognitive computing needs will constantly tax current computing power levels. Will this barrier keep us from delivering on its promise in the coming years?
Scientists at the U.S. National Institute of Standards and Technology, in Boulder, Colo., have developed a superconducting device that acts like a hyperefficient version of a human synapse.
RISE Lab’s Ray platform adds libraries for reinforcement learning and hyperparameter tuning.
The solution is built with TensorFlow, a handy and flexible computing system
Machine Learning, especially Deep Learning technology is driving the evolution of artificial intelligence (AI). At the beginning, deep learning has primarily been a software play. Start from the year 2016, the need for more efficient hardware acceleration of AI/ML/DL was recognized in academia and industry. This year, we saw more and more players, including world’s top semiconductor companies as well as a number of startups, even tech giants Google, have jumped into the race. I believe that it could be very interesting to look at them together. So, I build this list of AI/ML/DL ICs and IPs on Github and keep updating. If you have any suggestion or new information, please let me know.