A huge shift is taking place in the business software market, and Dropbox CEO Drew Houston knows it: Software needs to be smarter and more predictive. According to a report in The Information, Houston reiterated this notion at the annual Allen & Co.
“This machine learning strategy has nothing to do with natural intelligence, but it does have similarities with the processes that occur in the human brain when we control the muscles in our bodies. Children have to learn to pick up their feet when walking in the woods so as not to trip over roots or stones.
For more than a decade the company formerly known as Google, latterly rebranded Alphabet to illustrate the full breadth of its A to Z business ambitions, has engineered an annually increasing revenue generating empire which last year pulled in ~$75 billion. And it’s done this mostly by mining user data for ad targeting intel.
Have you ever wondered what’s the magic behind the tutorials on Large-scale Linear Models and Wide & Deep Learning? I hope this post would at least point you to the right direction. Please take a look at my previous blog posts to understanding some basics of TensorFlow Learn and its integration with other high-level TensorFlow modules.
When it comes to privacy controls, we may now have too much of a good thing. Smartphone owners must now make more than 100 privacy decisions about how how much data their apps can share on Apple’s iOs and Google’s Android operating systems. That number will only climb as privacy settings affect more of our devices and software.
DeepMind is an artificial intelligence lab in London that creates what are known as general purpose self-learning algorithms. The company, acquired by Google in 2014 for a reported £400 million, is best-known for creating software “agents” that have mastered games like Go and Space Invaders but it also wants to apply its technology to healthcare.
Graduate shows 2016: Central Saint Martins student Charlotte Nordmoen has designed a robotic potter that anticipates a time when human labour is no longer needed (+ movie). The prototype device has a “human finger” made from silicone attached to a mechanical arm. The implement is used to shape clay in much the same way a real finger would.
This post was first published on my Linkedin page and posted here as a contributed post. In the last few months, I have had several people contact me about their enthusiasm for venturing into the world of data science and using Machine Learning (ML) techniques to probe statistical regularities and build impeccable data-driven products.
The Sunway TiahuLight machine is the fastest supercomputer in the world running on the 10 million-core with a peak of 125 petaflops. The TaihuLight supercomputer is being harnessed for some interesting work on deep neural networks. What is fascinating here is that currently, the inference side of such workloads can scale to many processors, but the training side is often scale-limited hardware and software-wise.
One great promise machine learning holds for the network security industry is the ability to detect advanced and unknown attacks, particularly those leading to data breaches. Unfortunately, machine learning is quickly becoming a popular marketing term and vendors use it in very different ways, thus obscuring whether real benefits are being introduced.
