How to know which AI/ ML algorithm to apply to which business problem?
This is a common question
Ajit Jaokar found a good reference for it – Executive’s guide to AI by Mc Kinsey
He summarizes the insights in this post: Read More
Daily Archives: December 17, 2019
Can we build artificial brain networks using nanoscale magnets?
Artificial intelligence software has increasingly begun to imitate the brain. Algorithms such as Google’s automatic image-classification and language-learning programs use networks of artificial neurons to perform complex tasks. However, because conventional computer hardware was not designed to run brain-like algorithms, these machine-learning tasks require orders of magnitude more computing power than the human brain does. The brain, and biological systems in general, are able to perform high-performance calculations much more efficiently than computers, and they do it quickly and with minimal energy consumption
Building artificial neural networks is an emerging field of research in bio-inspired computing. Read More
LUKE Arm — a prosthetic arm controlled with your mind
Breakthrough Research In Reinforcement Learning From 2019
Reinforcement learning (RL) continues to be less valuable for business applications than supervised learning, and even unsupervised learning. It is successfully applied only in areas where huge amounts of simulated data can be generated, like robotics and games.
However, many experts recognize RL as a promising path towards Artificial General Intelligence (AGI), or true intelligence. Thus, research teams from top institutions and tech leaders are seeking ways to make RL algorithms more sample-efficient and stable.
We’ve selected and summarized 10 research papers that we think are representative of the latest research trends in reinforcement learning. Read More
Rick's Cafe AI 