A.I. Articles of the Week, Dec. 2017 #2
“In this blog post, I will touch on the most exciting highlights and most promising directions in optimization for Deep Learning in my opinion. Note that this blog post assumes a familiarity with SGD and with adaptive learning rate methods such as Adam. To get up to speed, refer to this blog post for an overview of existing gradient descent optimization algorithms”.
A list of slides of all talks from NIPS 2017
This year’s Neural Information Processing Systems (NIPS) 2017 conference held at Long Beach Convention Center, Long Beach California has been the biggest ever! Here’s a list of resources and slides of all invited talks, tutorials and workshops.
Using Artificial Intelligence to Augment Human Intelligence
By creating user interfaces which let us work with the representations inside machine learning models, we can give people new tools for reasoning.
Designing An Analytics Stack Like We Design Software
Since analytics needs are highly variable across teams and undergo frequent evolution within teams, this article will not attempt to provide guidance on choosing the tools that are right for you. Instead, we’ll shift our focus to understanding the cause of the trends we’re observing, and how embracing this evolution and leveraging its benefits may serve as the catalyst to take our analytical capabilities to the next level.
GOOGLE, AMAZON FIND NOT EVERYONE IS READY FOR AI
Yet as Amazon and Google seek greater riches by infusing the world with artificial intelligence, they’ve started their own consulting operations, lending out some of their prized AI talent to customers. The reason: Those other businesses lack the expertise to take advantage of techniques such as machine learning.
IBM’s new Power9 chip was built for AI and machine learning
In a world that requires increasing amounts of compute power to handle the resource-intensive demands of workloads like artificial intelligence and machine learning, IBM enters the fray with its latest generation Power chip, the Power9.
INSIDE BAIDU’S BID TO LEAD THE AI REVOLUTION
Presumably, Robin Li wanted attention last summer when he decided to launch Baidu’s bid for the future of self-driving cars from the front seat of a car that was driving itself. He wanted to draw attention to Apollo, the company’s new set of artificial intelligence-driven tools, which Li hopes will come to power vehicles everywhere.
Google leads in the race to dominate artificial intelligence
Tech giants are investing billions in a transformative technology
Elon Musk finally admits Tesla is building its own custom AI chips
And gives us the news that god-like machines will take over within a decade
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.
