Well, it looks like the Jetstream has fritzed out because the Artic is way warmer than it usually is at this time of year. It is an icy week this week in London. It was just snowing in Camden Passage!
I’ve been playing more with Neural-Style Transfer. It’s fun to play with, but with the code I’m using, I’m struggling to get results I can use. I was trying to merge the style of a Platon photo with a photo taken of me (when I was growing a beard). It was weird what information the neural net decided to take from the style photo.
I just started experimenting with Image-Style Transfer. I’ve been excited about it for a long time, but reading this code on Nvidia’s latest paper prompted me to start playing with it in earnest. Of course, in the Coursera Deep Learning courses we studied this as well. As I don’t have an Nvidia card installed on my notebook, I started off with this Torch Implementation.
There is a great graph-filled post over at Slate Star Codex called Technological Unemployment – much more than you wanted to know. After analysing a lot of data from the US economy, the author arrives at some tentative conclusions: The main point seems to be that the evidence for large-scale technological unemployment is mixed. There is evidence of technological underemployment however. There are signs that people are now struggling to adjust. The final paragraph is:
“This is a very depressing conclusion. If technology didn’t cause problems, that would be great. If technology made lots of people unemployed, that would be hard to miss, and the government might eventually be willing to subsidize something like a universal basic income. But we won’t get that. We’ll just get people being pushed into worse and worse jobs, in a way that does not inspire widespread sympathy or collective action. The prospect of educational, social, or political intervention remains murky.”
Today we walked along the canal in London from Angel to Camden. We didn’t actually make it to Camden as they have blocked off the towpath just before Camden Town as they are building residential apartments along there. It was a lovely day (for winter). 10C and reasonably sunny.
I read this post on QUIC over at LWN. QUIC is a protocol that multiplexes network connection streams on top of UDP (to get through routers). I had no idea that it was actively used in production with YouTube! Apparently the YouTube mobile app uses QUIC for streaming videos. According to Jana Iyengar (from Google) around 35% of outbound traffic is happening using QUIC.
I’ve started studying daily using Anki Flash Cards to revise. Every day I add at least one card to my study deck. Every day the study deck gets more valuable to me.
Today I discovered the sheer awesomeness that is Emacs with EIN. This lets my Emacs environment to to Jupyter Notebooks. Through it, I have the power of Emacs Python completion and editing while writing iPython functions. It works really well! I can display matplotlib graphs inline in my Emacs buffer. There is even symbolic computation via the sympy package! Bliss!
Today I was thinking about creating a mathematical model to represent my own personal “Klout” score. Instead of providing a measure of social influence, it would actually be a day-to-day score of how social I had been. Lately I have been quite reclusive. Other than Helen, I haven’t had much contact with people. I have also been a lurker on social media, such as Twitter and Facebook. In order to encourage more social interaction, my score would keep track of how many interactions I have. Whether the people I interact with are new people to me, or whether they are friends. If I construct the model properly and use it on a daily basis with an aim to improving my score, it should get me out of this reclusive rut I am currently in.
I have been studying continuously for many years now. I am still refining my studying technique though. One of the things that I am being forced to do with the maths I am doing at the moment, is to read and re-read the course materials over and over again. My workflow at the moment is:
- Skim the chapter. Scan the headings and sub-headings and try to build up the outline in my head.
- Skim through the problems within the chapter.
- Speed read the chapter. Get more of an idea of what is going on.
- Read through the problems and the answers.
- Read the chapter more thoroughly. Try and get a good understanding.
- Work through the problems.
- Repeat 5 and 6 until either clarity or the exam arrives!