tiagoespinha
Joined 13 years ago
Joined 13 years ago
To me it feels like the open standards never really kept up with the times, which in a way paved the way to walled gardens by the giants (and, in case of Slack, not so giants) to fill the gap which the open standards refused to fill.
I mean, sure IRC is awesome, text-only, channels, but emojis are limited to ASCII, inline GIFs are non-existent, and file-sharing (and/or storage) is rather clunky from what I remember from the old times.
And then we have XMPP which doesn't support things like video or voice calling (or at least it didn't last time I checked) and it's not very surprising that companies just capitalize on that and make their own platforms.
Don't take me wrong though... it creeps me out how the company where I work trusts Slack with reams and reams of confidential documents, but I guess it's convenient to an extent which no other platform is.
Just... what's the point of the argument?!
If you want to write a vague and generic piece of code that can figure out by itself what it is that its outputs ought to be with regards to its inputs, you are, with effect, creating artificial intelligence.
This, in turn, requires teaching.
What if suddenly you have new pages on your website? Your AI program thingy wouldn't be able to serve them until you taught it what these pages are and in what situations the end user might be interested in viewing them. Imagine having a 5 year old kid handling your shop's cashier. And now a new product arrived and you have to explain to him/her that there's this new product, what it's called, the price and which types of people are allowed to buy it (e.g., alcohol couldn't be sold to people younger than X years old). If you're really teaching your application with natural language, like you would with a five year old, then the effort it'd take to get that info into your system would defeat the purpose of actually using a computer to do it (computers are good at storing and looking up stuff in large data sets, better than humans for really large data sets).
This whole hype of machine learning is suitable for situations where you have large amounts of data and you want them crunched according to some basic pre-established and non-changing logic without relying on actual human labor. If the logic evolves, you'll always require humans to sit at the helm and steer the right and wrong.
My 2 cents.