Posts

Just as last year , I wrote a PowerShell script using which you can download the PowerPoint decks, and, videos from Microsoft Build’s conference, instead of streaming it (or manually download it one by one). You can choose if you want the decks, or the videos, or both. For the videos you can choose the desired resolution (Low, Medium, High) – of course the higher the resolution, the more space is needed. The script also downloads the description and if there is a session image (if there is one). ...

If you were trying to pull the latest source code on your Raspberry Pi for donkeycar, and get the following error, then probably your clock is off (and I guess some nonce is failing). This can happen if your pi had been powered off for a while (as in my case), and it’s clock is off ( clock drift is a real thing) :). ...

Can #AI make me look (more) presentable? The jury is out I think. This is called style transfer, where the style/technique from a kind of painting (could be a photos too) is applied to an image, to create a new image. I took this using the built-in camera on my machine sitting at my desk and then applying the different kind of ‘styles’ on it. Each of these styles are is a separate #deeplearning model that has learned how to apply the relevant style to a source image. ...

Yesterday it worked Today it is not working #AI is like that #Haiku #GeekyHaiku #GeekyJokes

Rather than a beep Or a rude error message, These words: “File not found.” #Haiku #GeekyHaiku #GeekyJokes

One of the challenges we have with AI is that there isn’t any universal definition - it is a broad category that means everything to everyone. Debating the rights, and, the wrongs, and the should’s and the shouldn’t s is another post though. DARPA outlines this as the “programmed ability to process information” and across a certain set of criteria that span across perceiving, learning, abstracting, and, reasoning. ...

Cognitive Bias

When seeing this #CosmosDB is the first thing that comes to mind :)

What is it? What’s the next big thing in computing? Not the #AI or #blockchain’s of the world, that is starting to happen today (albeit a little early)? Quantum computing is one of those next big things, that is on the horizon (probably in the ~5 years range). Why do I care? Why do I care about quantum? Well, some problems are simply not solvable on convention digital computers – the kind we have today – these are called “classical” machines. Even if Moore’s law did continue (and that is a whole different debate), are the still some problems whose scaling obey a different set of properties and law; and the double of transistors on a chip wont really help. In fact, some of these problems require longer than the lifetime of the universe – and that is with the biggest, and fastest supercomputers available! ...

At a recent internal meeting, we were discussing productivity and the various levels of distractions that one has these days. Did you know that there is a hierarchy of digital distractions (see image below). No wonder, in todays connected, and agile world, for some people why it is so difficult to get any actual work done (that is not to suggest that they are not busy of course). At this meeting, analogy of the distraction was coined as the “monkey” – the monkey that each of us has on our shoulder and the constant attention it demands – I.e. the distraction. And we all know we cannot control this monkey and bottle it up. The idea isn’t to try and bottle it up, which will rattle it more trying to get out and demand more attention – but rather let it out in a controlled manner for some time – similar to how one would take a dog out for a walk (of course different outcomes) ! 😄 ...

Parenting geek

I wakey wakey. Production release today. No breaky breaky. #Haiku #GeekyHaiku #GeekyJokes

Chaos reigns within. Reflect, repent, and reboot. Order shall return. #haiku #GeekyHaiku

Ridiculous mess iOS development conceived by hipsters #Haiku #GeekyHaiku #GeekyJokes

Thinking about #machinelearning? It will be helpful to understand some numerical computations and concepts that affect the #ML algorithm. One might not interact with these directly, but we surely can feel the effect. The things you need to think about are: 1. Overflow and underflow - thinking of them as rounding up or down errors that shift the functions enough, and compounded across the iterations cam be devastating. Of course can also easily get to division by zero. ...

I know I have had to explain this a lot in most #AI related conversations that I have had - and lately those have been quite a lot. In my experience, most people use these terms interchangeably when they are meaning one over the other. Whilst they all are (inter)related and one might help trigger the other, they are still fundamentally different and at some point, it is good to understand the differences. I like the image below ( source ) that whilst on one hand is showing a time graph, the correlation between them and how one is a subset of the other is what is interesting. ...

Update: Modified the script to handle multiple instances but pay heed to the warning here . Similar to last year , I have a PowerShell script that will allow you to download the various PowerPoint decks and videos to watch locally rather than stream. This makes some improvements from the earlier scripts (e.g. if a file is already downloaded it will skip downloading it again) and does the following: ...

In case you did not see Story Remix demos from Build, it is awesome. And here is my first take on it just using the photos that I took at Build 2017. Some of the things you saw at the keynote are not in the RS3 build I am running but interesting possibilities nevertheless. There should have been a video here but your browser does not seem to support it.

There of course are many, but for someone coming from computer science, and, software engineering, where the environment is relatively clean and certain (deterministic), it usually is a leap to understand that Machine Learning (and other elements of #AI) are not. Machine learning, is based on probability theory and deals with stochastic (non-deterministic) elements all the time. Nearly all activities in machine learning, require the ability to factor and more importantly, represent and reason with uncertainty. ...

How to protect your data from what the The Guardian calls as ‘ US border agents are doing ‘digital strip searches’? The only way I think this is possible in a fool-proof way in the near future is that every has to absolutely implement a two-factor-DDA-authentication. There is not better #security today - period! There ain’t no stinking #AI, #RNN, #DNN, or Boltzmann machine in the world, or #Quantum computer worth its #quibits which can crack this - at least not in the near future. ...

When it comes to AI and the limits of human kind, what better example that shows the art of the possible than what Microsoft is doing with special awareness and HoloLens and other sensors. And not only can this replay time and allow you to have a ’living memory’ but it also is mobile. ...

Of course you heard of Neural Networks! In the context of #AI they are all the buzz of course. You might have heard of some such as DFF (Deep Feed Forward) or RNN (Recurrent neural networks)? Or perhaps you meant Recursive neural networks? Irrespective, it can be quite messy as you can see below and it would be somewhat important to have some understanding of the differences. And in case you are thinking, well what good or use is all this? Here is one example ( MarI/O - Machine Learning for Video Games) that shows how a computer learned to play Mario using DeepMind and a Neural network. ...

I have said in the past, Culture eats strategy for breakfast. One cannot fix culture - but rather lead with example and have others follow. This article on how Satya at Microsoft is expecting a culture shock to drive growth at Microsoft is a great example of this. Quite exciting days for Microsoft ahead.

This wired article titled If Xerox PARC Invented the PC, Google Invented the Internet , is an old one - from 5 years ago, but it is still an inspirational read. So many things lined up for Google, to be where they are today. I still get goose bumps reading that article - but then I am a geek, if that wasn’t obvious. Whilst, grid computing with GFS, MapReduce, Hadoop, are still very much relevant and great (and most others still trying to use and understand it); Dynamo (from Amazon) and BigTable lead to NoSQL which is great and still worth spending a lot of time learning, playing, and, experimenting - I would love to hear on what they are doing now with Colossus (think of that as GFS vNext), Caffeine and, Spanner . ...