So, a few days ago, the internet had a new toy: How Old Robot – a very simple website where you can upload a photograph and it will guess your age and gender. For many people the guess was about right, but there were some howlers, with very similar images being uploaded and giving age results differing by (several) decades!
The site doesn’t hide the fact that it’s a learning tool based on Microsoft’s facial recognition technology and is built on the Azure platform as an example of how quickly it is to build and deploy sites using Azure. What started off as a quick demo from the Build conference soon became viral, with people all over the world loading their photos into the app and sharing the results on social media. This is exactly what Microsoft wanted and they’ve been oh so clever with this and here’s why.
This morning I had a tutorial for module MS221 of my OU Maths degree. In addition to complex numbers, groups, and proofs one of the topics we covered was RSA encryption and decryption. As I’m a little behind in my study I’m going to use this post to explain how this type of encryption works (even though this is already covered elsewhere e.g. in wikipedia). You’re going to need a little maths to follow this, but hopefully not too much!
Firstly, a quick recap. Public-private key encryption means that you have a pair of keys – the public one you can give out without a care and anyone can use this to encrypt messages to you. Without the private key to decrypt, it’s practically impossible to decipher the encrypted messages, so as long as you actually keep your private key private, everything is (relatively) safe. As an aside, if your private key is obtained by someone else then they will be able to read your messages and you would never know.
I’m three days in to my new role and, while there is some run of the mill development that I’m managing there’s also a very exciting project just starting that I’ll be taking from the very beginning based on a discussion I had with the CEO on my first day.
This new secret project means I’ve got to become an expert in Deep Learning and also all the changes in AI and since I wrote my own thesis. I discovered very quickly that the way I knew was the “old way” and that machine learning has come on very considerably in a short space of time. So the past few days I’ve regressed into academic mode.
So, most people know by now that in a week’s time I start a new role. After 12 years of working for established business both small and large I am joining a start up in an area at the current edge of what is possible in computer science. I’m very much looking forward to having my technical and scientific abilities stretched as far as they’ll go and, not unsurprisingly, the immersion in a new venture where the focus is on the solution and not why things can’t be done (often the case in established companies).
I have a reading list as long as the references for my own thesis to get through in the next few weeks so I can become an expert in my new field: deep learning and artificial intelligence. One of the first things I’ll be doing is attending the ReWorkDL summit in Boston, MA, which is just a fascinating line up of some of the leading people in this space. All being well I will be presenting at the 2016 summit.
I’ll be tweeting throughout the event with thoughts and comments and will do a summary post afterwards.