Stephen Wolfram is giddy with excitement. A long post, but worth a read all the way through.
I’m not sure what is coming, but whatever it is, I am starting to formulate an answer for that inevitable and challenging moment when my daughters ask me why they should bother to learn mathematics.
In fact, with (potentially) big steps forward like this laying a foundation now, maths teaching is going to be revolutionised and the above question will no longer be relevant. After learning the basics, advances of this kind will allow people to see the beauty of mathematics.
The young will grow up with things like this. In the same way they are all “digital natives” now, they will be the first generation to be “computation native” too.
They will grow up appreciating mathematics in a real-world context much more than most people of my (or any previous) generation.
Then they can truly change the world.
• Stephen Wolfram: Something Very Big Is Coming: Our Most Important Technology Project Yet
…recently something amazing has happened. We’ve figured out how to take all these threads, and all the technology we’ve built, to create something at a whole different level. The power of what is emerging continues to surprise me. But already I think it’s clear that it’s going to be profoundly important in the technological world, and beyond.
At some level it’s a vast unified web of technology that builds on what we’ve created over the past quarter century. At some level it’s an intellectual structure that actualizes a new computational view of the world. And at some level it’s a practical system and framework that’s going to be a fount of incredibly useful new services and products.
It’s hard to foresee the ultimate consequences of what we’re doing. But the beginning is to provide a way to inject sophisticated computation and knowledge into everything—and to make it universally accessible to humans, programs and machines, in a way that lets all of them interact at a vastly richer and higher level than ever before.
A crucial building block of all this is what we’re calling the Wolfram Language.
We call it the Wolfram Language because it is a language. But it’s a new and different kind of language. It’s a general-purpose knowledge-based language. That covers all forms of computing, in a new way.
There are plenty of existing general-purpose computer languages. But their vision is very different—and in a sense much more modest—than the Wolfram Language.
And so in the Wolfram Language, built right into the language, are capabilities for laying out graphs or doing image processing or creating user interfaces or whatever. Inside there’s a giant web of algorithms—by far the largest ever assembled, and many invented by us. And there are then thousands of carefully designed functions set up to use these algorithms to perform operations as automatically as possible.
So in a sense inside the Wolfram Language we have a whole computable model of the world.
It can be an array of data. Or a piece of graphics. Or an algebraic formula. Or a network. Or a time series. Or a geographic location. Or a user interface. Or a document. Or a piece of code. All of these are just symbolic expressions which can be combined or manipulated in a very uniform way.
In most languages there’s a sharp distinction between programs, and data, and the output of programs. Not so in the Wolfram Language. It’s all completely fluid. Data becomes algorithmic. Algorithms become data. There’s no distinction needed between code and data. And everything becomes both intrinsically scriptable, and intrinsically interactive. And there’s both a new level of interoperability, and a new level of modularity.
And this is not just a theoretical idea. Thanks to endless layers of software engineering that we’ve done over the years—and lots of automation—it’s absolutely practical, and spectacular. The Wolfram Language can immediately describe its own deployment. Whether it’s creating an instant API, or putting up an interactive web page, or creating a mobile app, or collecting data from a network of embedded programs.
And what’s more, it can do it transparently across desktop, cloud, mobile, enterprise and embedded systems.
It’s been quite an amazing thing seeing this all start to work. And being able to create tiny programs that deploy computation across different systems in ways one had never imagined before.
There’ll be the Wolfram Data Science Platform, that allows one to connect to all sorts of data sources, then use the kind of automation seen in Wolfram|Alpha Pro, then pick out and modify Wolfram Language programs to do data science—and then use CDF to set up reports to generate automatically, on a schedule, through an API, or whatever.
And with our Wolfram Embedded Computation Platform, we’ll have the Wolfram Language running on all sorts of embedded systems, communicating with devices, as well as with the cloud and so on.
I’m very excited about all the things that are becoming possible. As the Wolfram Language gets deployed in all these different places, we’re increasingly going to be able to have a uniform symbolic representation for everything. Computation. Knowledge. Content. Interfaces. Infrastructure.
Just as the lines between data, content and code blur, so too will the lines between programming and mere input. Everything will become instantly programmable—by a very wide range of people, either by using the Wolfram Language directly, or by using free-form natural language.