TightWind is written by Kyle Baxter. Stay Hungry. Stay Foolish.

Rather than review iOS 5, I want to write a little about why I think Siri is important and what it means for the future of computing and the web. If you’d like to read a great iOS 5 review, Shawn Blanc will have you covered, I bet.

Every few months, I re-watch Apple’s 1987 Knowledge Navigator video, a concept for what computing should be like. I watch it because it reminds me what technology is about: making people’s lives dramatically better, and creating a sense of magic or wonder in doing so.

In the video, there is a tablet device that uses touch input, recognizes natural language and acts on behalf of the user (e.g., “Call Diana at home”), and has networked data stores that allow people to find data with no effort searching for it (e.g., “Get data on the deforestation of the Amazon rainforest from 1992-1995″).

That video was incredibly forward-looking and insightful, but with iOS 5 and the iPhone 4S, Apple is finally releasing the Knowledge Navigator. Its name is Siri. It isn’t as powerful, but we’re almost there. For me, this may be the most exciting thing Apple’s ever done, because it is moving toward realizing one of my favorite dreams.

Most articles about Siri have focused on Siri’s natural language recognition and how revolutionary it is. While it is integral, it is not the important part. It is the means, not the end. Focusing on Siri’s natural language recognition is like focusing on the original iPhone’s multitouch input; while it is what allows the iPhone’s magic, it is not the magic itself.

What is magical about Siri is that it allows people to talk to a device and it does what they tell it to. You can now ask your iPhone, “How many ounces are in three gallons?” and get an answer. You can tell our phone to schedule dinner at Chego in Los Angeles with your wife at 7pm on Friday and it will tell you that you already are going to see “50/50″ at that time. You can ask it if you’ll need an umbrella tomorrow, and it will tell you that, yes, you do.

What really excites me about this is not that I will be able to more easily create reminders, appointments and respond to text messages. (Although I am pretty excited about that.) What excites me is that this is the first version of what we saw in the Knowledge Navigator video: a device that I can ask for any kind of information, and because it (1) understands what I am asking for and (2) connects to different online services which provide data, it can give me that information. This is not just a vision for the future of computing devices, but the future of the web, too.

Interconnected and Semantic Magic

Currently, while the web contains an overwhelmingly-large amount of data, it is basically disparate and in silos. To find Microsoft’s financial performance in 1995, for example, I have to use a search engine to find a website that has that data and, if I can’t find one, I have to compute it myself using their financial statements (which I have to find as well). Siri is a dramatic step away from this.

All that data is there, but we have to work to find it. What we are moving toward, though, is not having to find it at all. Instead, because that data is made available through APIs,1 I can simply ask it for data, and it won’t just return a source, but it will return the data itself in a useful format.

Let’s use Microsoft as an example again. Right now, if I wanted to see their operating profit as a percentage of sales from 1995-2005, I would need to find their financial statements, locate the data contained in them, and make the calculations myself. If I wanted to do anything useful, I would have to import it into a spreadsheet application (most likely by hand). Rather than doing this myself, though, I could just ask a future version of Siri for Microsoft’s operating margin between 1995 and 2005, and it would return that data to me in a table and chart.

Then I can ask it to compare Microsoft’s operating margin over that period compared to Hewlett-Packard’s, Dell’s and Apple’s.

That’s a big deal. That’s what happens when natural language recognition is integrated with web services. And that’s why Siri is important: it is a large step toward the future Apple’s Knowledge Navigator video envisioned, where not only do we have access to the greatest source of information in the history of the world, but we can we can access that data simply by asking for what we want to see, and we can manipulate the data just as easily.

We have all of the world’s data available, and there is no good reason we shouldn’t be able to access it effortlessly. Making that reality will make our lives easier, but more importantly, it will allow us to be even more imaginative and insightful, because the cost of getting data to analyze and compare and find patterns will be much lower than it is now.

I love business and technology because they are where philosophy, literature, art and science intersect to push us forward. Philosophers tell us what the good is, writers and artists tell us what the beautiful and inspiring is, scientists make it technically possible, and business make it economically feasible. Without science and business, philosophy, literature and art are only ideas in our minds; without philosophy, literature and art, scientists and businesses are directionless as to what they should do. But together, they change the world.

Siri is a wonderful example of this, and it’s why I love what Apple’s doing. They are not just creating the future. They are creating a better future for us all based on a beautiful vision they believe in. What’s more exciting than that?

1. Or, more preferably, some kind of service that centralizes data from across the web and makes it all available through an API that returns it based on natural language. E.g., if I ask it for the United States’s tax revenue-to-GDP ratio from 1930-2005, it will connect to the different data stores it works with, find the appropriate source, and return the data in a useful format. This kind of service will require common data formats to be used and a way to semantically understand the data itself, which people are really good at, but computers just aren’t quite yet. [↩]