Leon on Everything

  I grew up in a highly Francophone area in East Beirut. It was customary during that time to teach French to your toddler before any other language. As such, I spoke French before I learned a single Arabic word. Also, due to my grandfather’s own name change, my parents decided to call me Léon when they registered me and chose my name. This is an old French name, and it is pronounced the way you would in French. Years later I would drop the accent when I wrote emails in English. This is not because I preferred the English pronunciation of the name but rather to make my life easier when I use the qwerty keyboard as well as not to have my English-speaking reader struggle when reading my name. But the name that my parents call me by to this day, or the name I used to introduce myself to my wife when we first met, remains Léon. And it is still pronounced the way you would in French. If you’re an Anglophone, or we are speaking in English I would be perfectly fine with you calling me Leon an

 An AI that is 99% accurate is not good enough. Think of having to digitize some handwritten document with important end-customer data. Does it make sense to use machine learning if on top of that you need human operators? Think of how many times Alexa gets you wrong? Even when it comes to playing the same song you have requested many times before. But Alexa is not a mission-critical system. You don’t care if it’s 90% accurate that alone 99%, but for critical systems, it seems that AI isn’t delivering the value it is supposed to (how far are we from the promised self-driving dream?). How much effort will be saved by a human quality controlling every document vs if a human operator digitized them from scratch? I remember a project I was tangentially involved in years ago in the pre-AI area (in fact over 20 years ago), the project manager decided to use three people to digitize the data and then use text comparison so that if two documents match then an algorithm would drop the third. It

A recent article in "the economist" magazine questioned the value of the public cloud altogether. This took place in the Schumpeter section nonetheless. Joseph Schumpeter the economist most identified with capitalism’s creative destruction was transformed into what Peter F. Drucker refers to as a bean counter when it comes to the cloud. This kind of article and thinking will reinforce Information Technology’s old guard’s skepticism of all things new and especially the cloud. At the heart of the article is relating a blog post from venture capital firm Andreessen Horowitz using the example of how Dropbox managed to save billions and increase stock market valuation by repatriating the public cloud resources to its own datacenters. Indeed, as the theory and studies show there are cases where private on-premises deployments can be more cost-effective than the public cloud (as can be viewed in this lecture on cloud computing from the University of Illinois and Coursera).  The tru