ARTIFICIAL INTELLIGENCE IS GOING TO SUPERCHARGE SURVEILLANCE
What happens when digital eyes get the brains to match?
The head of Facebook’s AI research is stepping into a new role as it shakes up management
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.
Facebook: Detectron
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.
China wants to make the chips that will add AI to any gadget
The AI boom offers Chinese chipmakers a chance to catch up after years of lagging behind.
Engineers design artificial synapse for “brain-on-a-chip” hardware
Design is major stepping stone toward portable artificial-intelligence devices.
Announcing TensorFlow 1.5
First off, Eager Execution for TensorFlow is now available as a preview.
The UX of AI
Using Google Clips to understand how a human-centered design process elevates artificial intelligence.
Open-sourcing Psychlab
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.
Spiking Neural Networks, the Next Generation of Machine Learning
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.
How to Hack an Intelligent Machine
AI scientists try to trick smart systems into making dumb gaffes.
Common Misconceptions Executives Have About AI
The message to executives is clear: it’s time to understand and leverage trends in automation and artificial intelligence.
Could the Limits of Physics Soon Affect Cognitive Computing?
Cognitive computing needs will constantly tax current computing power levels. Will this barrier keep us from delivering on its promise in the coming years?
Superconducting Synapse Could Let Neuromorphic Chips Beat Brain’s Energy Efficiency
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.
Introducing RLlib: A composable and scalable reinforcement learning library
RISE Lab’s Ray platform adds libraries for reinforcement learning and hyperparameter tuning.
Tutorial: Implement Object Recognition on Live Stream
The solution is built with TensorFlow, a handy and flexible computing system
A List of Chip/IP for Deep Learning (keep updating)
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.
