To Speed Up AI, Mix Memory and Processing
New computing architectures aim to extend artificial intelligence from the cloud to smartphones
How Our Company Learned to Make Better Predictions About Everything
Taking a cue from machine learning, Twitch employees train their forecasting powers against real world historical data. Our staff are encouraged to predict quickly and are given immediate feedback so that their forecasts become more accurate. Our goal is to leverage forecasting in order to make the “high-quality, high-velocity” decisions Jeff Bezos calls for in his 2017 letter to shareholders. Through forecasting, we are better equipped to serve the millions of gamers that use our platform every day, while staying ahead of the competition.
Evolution is the New Deep Learning
Over the past few years, the team has focused on developing new methods in Evolutionary Computation (EC), i.e. designing artificial neural network architectures, building commercial applications, and solving challenging computational problems using methods inspired by natural evolution.
AI can spot signs of Alzheimer’s before your family does
Earlier diagnosis could help researchers develop drugs to slow the progress of the disease.
IBM Speeds Up Machine Learning
IBM wants to make machine learning as fast as snapping your fingers. At its own IBM THINK conference this week, IBM Research unveiled a newly published benchmark using an online advertising dataset released by Criteo Labs of more than 4 billion training examples.
Canada’s risky bet on AI
Canada is placing a big bet on artificial intelligence. Last year, the federal government charged the Canadian Institute for Advanced Research (CIFAR) with spearheading the $125-million Pan-Canadian Artificial Intelligence Strategy, and the term appears several times in the recent 2018 federal budget.
The US military wants AI to dream up weird new helicopters
DARPA wants entrants to rethink the way complex components are designed by combining recent advances in machine learning with fundamental tenets of math and engineering.
Understanding deep learning through neuron deletion
“Understanding how deep neural networks function is critical for explaining their decisions and enabling us to build more powerful systems. For instance, imagine the difficulty of trying to build a clock without understanding how individual gears fit together. One approach to understanding neural networks, both in neuroscience and deep learning, is to investigate the role of individual neurons, especially those which are easily interpretable. “
Intelligent to a Fault: When AI Screws Up, You Might Still Be to Blame
Interactions between people and artificially intelligent machines pose tricky questions about liability and accountability, according to a legal expert
It certainly looks bad for Uber
The Tempe police released the poor quality video from the Uber. What looks like a dash-cam video along with a video of the safety driver. Both videos show things that suggest serious problems from Uber, absent further explanation.
How the AI cloud could produce the richest companies ever
Amazon, Google, and Microsoft all want to dominate the business of providing artificial-intelligence services through cloud computing. The winner may have the OS of the future.
What Will Our Society Look Like When Artificial Intelligence Is Everywhere?
Will robots become self-aware? Will they have rights? Will they be in charge? Here are five scenarios from our future dominated by AI.
What is wrong with VAEs?
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.
