Aug 16, 2017 | deep learning, ecology, energy efficiency, problem solving, science

The Hidden Cost of Deep Learning Anyone who has worked with deep learning knows that some of the models/model configurations require tremendous amounts of computing power. Given the opportunity, few will turn down the option of working with a high power cloud instance...
Aug 12, 2017 | creativity, data scientists, deep learning, learning, skill

Let’s imagine someone just died, it should not be too hard given that every 2 seconds someone does die[1]. It was a data scientist, a great one. We’ll refer to this data scientist as ‘she’ for the remainder of the post. We’re going to perform an...
May 16, 2017 | deep learning, learning, nature, problem solving, science

We have to re-think the way we think about solving problems. As the problems we deal with increase in complexity, so must the methods we use to solve those problems evolve. And how do we do that? By turning to nature, as the great masters of the past did to unravel...
Sep 16, 2016 | number theory

How to Randomness When we say “pick a random number” the obvious problem is that randomization is not possible. So you’re stuck with pseudo randomization, and this is not all, there is another problem as well. if I pick a random number and...
Apr 6, 2014 | algorithm, autonomy, computer science, future

Moore’s law gives us 2x more computational output every 18 months. To say accurately, the transistor density in the processing unit doubles every 18 months. Basically that is the pace of r&d Intel is committed to. They’re doing a good job, actually an excellent...