This mostly cites papers from Berkeley, Google Brain, DeepMind, and OpenAI from the past few years, because that work is most visible to me. I’m almost certainly missing stuff from older literature and other institutions, and for that I apologize — I’m just one guy, after all.
Arm announcement is a bit out of the norm for the company, as it’s the first in a series of staggered releases of information. For this first announcement Arm is publicly unveiling “Project Trillium” — a group of software solutions as well IP for object detection and machine learning.
Stimulating part of the cortex as needed during learning tasks improves later recall. The finding reveals more about the brain’s memory network and points toward possible therapies.
A dazzling review of AI History, from Alan Turing and Turing Test, to Simon and Newell and Logic Theorist, to Marvin Minsky and Perceptron, birth of Rule-based systems and Machine Learning, Eliza — first chatbot, Robotics, and the bust which led to first AI Winter.
Amazon.com is developing a chip designed for artificial intelligence to work on the Echo and other hardware powered by Amazon’s Alexa virtual assistant, says a person familiar with Amazon’s plans. The chip should allow Alexa-powered devices to respond more quickly to commands, by allowing more data processing to be handled on the device than in the cloud.
China’s nationwide pursuit to become the world leader in artificial intelligence (AI) is an attempt to not only match U.S. economic power, but to bypass it geo-strategically.
In this blog post series we will take a closer look at inverse reinforcement learning (IRL) which is the field of learning an agent’s objectives, values, or rewards by observing its behavior. For example, we might observe the behavior of a human in some specific task and learn which states of the environment the human is trying to achieve and what the concrete goals might be.
He Predicted The 2016 Fake News Crisis. Now He’s Worried About An Information Apocalypse.
New chip reduces neural networks’ power consumption by up to 95 percent, making them practical for battery-powered devices.
“In this post, I’m going to argue that training Reinforcement Learning agents to trade in the financial (and cryptocurrency) markets can be an extremely interesting research problem. I believe that it has not received enough attention from the research community but has the potential to push the state-of-the art of many related fields. It is quite similar to training agents for multiplayer games such as DotA, and many of the same research problems carry over. Knowing virtually nothing about trading, I have spent the past few months working on a project in this field.”
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.
Source: Deep Learning on Medium