The Best Way To Learn New Things

Science and business seem like two very different disciplines, but is the best approach to learning any different in these two fields?  These areas of life seem so unique, and the people in them can be quite varying (one with the nerdy pocket protector and the other dressed in the well-tailored suit).  However, both science and business require learning, and the best approach to learning in each is really the same.

Businessman-Nerd
The best approach to learning is generally through failure.  For example, Thomas Edison failed an astounding number of times before he invented a working lightbulb, and there are likely thousand of stories about how successes came as a result of many tries and many failures.

In many ways, this is really an application of the scientific method.  I’ve written a number of posts about Stephen Wolfram (such as using Wolfram|Alpha to look at your own social network, his views on big data, computing a theory of everything, and how he created his company).  In the effort to learn even more about how the world works, Wolfram has pushed scientific discovery to the next level, which he’s done with his book A New Kind of Science (NKS for short).

How Wolfram|Alpha Can Help You Discover Your Own Social Network

Ever wonder what your own personal network looks like?  You are likely connected to many different groups (family, friends, community, work), but do you know how they are connected?  Or are they connected at all?  Are you the glue that connects these various groups?

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This is a great age we’re living in, and I’m glad to be involved with developing lots of really advanced technologies.  One of the technology areas that I’m really fascinated with has been pushed forward by Stephen Wolfram.  He created the industry standard computing environment Mathematica, which now serves as the engine behind his company’s newest creation, Wolfram|Alpha.  (I’ve written a few posts on Wolfram|Alpha in the past, and you can read them here and here).

Popular Science: Wolfram on Big Data

I’m a big fan on Stephen Wolfram and his efforts in building Mathematica and pushing forward his approach to scientific discovery, A New Kind of Science.  In a recent post, Popular Science editor Mark Jannot talks to Wolfram about big data, human understanding, and the origin of the universe.

Here’s just on back-and-forth between Jannot and Wolfram:

Jannot:  A couple years ago at TED, Tim Berners-Lee led the audience in a chant of “More raw data now!” so he’s out there trying to create the data Web. And your project in Wolfram Alpha is not to deliver raw data but to deliver the interface that allows for raw data to turn into meaning.

Wolfram:  Yes, what we’re trying to do—as far as I’m concerned, the thing that’s great about all this data is that it’s possible to answer lots of questions about the world and to make predictions about things that might happen in the world, and so on. But possible how? Possible for an expert to go in and say, “Well, gosh, we have this data, we know what the weather was on such-and-such a date, we know what the economic conditions at such-and-such place were, so now we can go and figure something out from that.” But the thing that I’m interested in is, Can one just walk up to a computer and basically be able to say, “OK, answer me this question.”

This part of the Q&A is particularly interesting, since it highlights a difference of approach in what some want in technology.  Berners-Lee seems to want more “raw data”, while Wolfram is highlighting that the data isn’t really important unless you can turn the data into actionable information.  Wolfram|Alpha does just this – the technology uses Wolfram’s understanding of computation (what he built as part of his wildly successful Mathematica product line) and lets us answer questions. 

It’s an incredibly rich article – one worth reading (1) if you’re interested in data and where its taking us, and (2) if you’re interested in Wolfram and his take on science and technology.  I’m interested in both, so I think it’s very worth highlighting…

Here’s the Popular Science article, and another post to Wolfram|Alpha that highlights the history of computable knowledge (you can even order a poster of the timeline here…).   I’ve had a number of other posts on Wolfram and his scientific approach, which might worth looking into as well…

NKS Now Available on the iPad

I really like Stephen Wolfram’s book A New Kind of Science (or NKS for short) – on how simple computational programs can create amazingly complex things.  I’m also really enamored with the iPad (I’ve written about it before a number of times…).

Now, two of my favorite things are coming together – Wolfram’s NKS is now available on the iPad.  It’s available at Apple’s iTunes store for $9.99 – far less than the hardback version and certainly much lighter!…  (Hmmm…  Two things coming together – kind of like chocolate and peanut butter in a Reese’s Peanut Butter Cup…)

I haven’t purchased an iPad yet, but now I’m really excited to think about possibly maybe starting to look into getting one… (or at least window shopping for one…)

Read more about A New Kind of Science for the iPad on Stephen Wolfram’s blog here

Video: Stephen Wolfram – Computing a Theory of Everything

Stephen Wolfram recently gave a talk about his efforts to understand the universe around us through computation.  He’s the CEO and founder of Wolfram Research, creator of Mathematica, and author of A New Kind of Science.  Wolfram recently launches his computational knowledge engine, Wolfram|Alpha (I wrote a post about its launch some time back…). 

Here’s the video of his talk, given at a recent TED conference

Watch and learn!

Wolfram|Alpha Links With Bing

I ran across a post by Erick Schonfeld on TechCrunch about Microsoft’s Bing search engine licensing search data from Wolfram|Alpha.  Might not be much of a big deal, but I think the Wolfram|Alpha concept is pretty cool… 

While Google and Bing provide you websites that have the search phrase that you are looking for, Wolfram|Alpha takes your search and presents you with brand new information.  It actually crunches through what it has access to, and creates new data that isn’t on any website.  I first wrote about the launch of Wolfram|Alpha a few months ago… 

Worth taking a look…

Blaze a New Trail

In our fast paced world, it seems that every new technology gets overturned every few years or so.

Just look at social networking – it used to be MySpace, then Facebook, now it’s Twitter (I’m sure by the time I publish this column, Twitter will even be passé…)

But there has (at least for the time being) been a stable anchor in our technology world – Google.  Everybody knows that you enter what you’re searching for, and Google provides relevant webpages that give you the information you want.  It’s almost as if it’s been around forever (at least in technology years…), and it’s even become a verb – people can actually “google” something…

But now, there is a new knowledge engine on the block, called Wolfram|Alpha (www.wolframalpha.com).  It’s similar to and different from Google in what you can do with it.

You can still enter a search term like “weather new york city”, and Wolfram|Alpha will provide you information.  However, while Google will provide you a list of links to go seek the information you want, Wolfram|Alpha actually calculates new and more immediately relevant information for you – on the fly.

You’ll get the temperature, conditions, relative humidity, and wind speed, but Wolfram|Alpha will also generate week histories and forecasts for the temperature and conditions, as well as provide a historic temperature graph for today’s date for the last 40 years.  It will even provide the closest local weather station and compare that with other locations in the area.

It is indeed a new kind of knowledge engine, and an ambitious undertaking.  According to the website, “Wolfram|Alpha’s long-term goal is to make all systematic knowledge immediately computable and accessible to everyone.”

But none of this is surprising, coming from its creator, Stephen Wolfram.

Born in 1959, Wolfram studied at Eton, Oxford, and Caltech.  His first scientific paper, called “Hadronic Electrons?”, was accepted for publication when he was just 15, and he graduated for Caltech with a PhD in theoretical physics at 20. 

His work had such a profound impact on the physics community (one of his widely-cited papers on heavy quark production was published at the age of 18) that he joined the Caltech faculty immediately upon receiving his doctoral degree.  A year later, Wolfram became the youngest recipient of the MacArthur Prize Fellowship.

While at Caltech, he began the creation of SMP, the first modern computer algebra system, which was commercially released in 1981.  He spent the next several years in academia, first at Caltech, then at Princeton, and finally at the University of Illinois.  However, his scientific pursuits did not follow the standard track for a physicist – he set out on his own path toward finding the fundamental origins of complexity.

After publishing numerous classic papers on simple computational systems known as cellular automata, he went on to found his own company called Wolfram Research.

There he created Mathematica, probably the most significant achievement in technical computing to date (I even used an early version of Mathematica to perform a little of my thesis work…).  Rather than having different toolkits for different technical jobs, such as computer algebra systems, graphing calculators, or 3D visualization, Mathematica creates a unified computational framework for technical development.  It has changed the way scientists and technologists perform their work.

Through the course of his development of Mathematica, learning more and more about how computation relates to the complexity we see in our world, Wolfram embarked upon his most ambitious project – publication of his treatise A New Kind of Science. 

Starting from examination of very simple computer experiments, Wolfram explains in NKS how simple computational programs can generate incredible complexity, debunking the primary scientific belief that only complex models can create such complexity.

Wolfram goes on, as described in the book’s summary, to use his approach “to tackle a remarkable array of fundamental problems in science, from the origins of apparent randomness in physical systems, to the development of complexity in biology, the ultimate scope and limitations of mathematics, the possibility of a truly fundamental theory of physics, the interplay between free will and determinism, and the character of intelligence in the universe.”

Ambitious indeed.

Of course, Wolfram hasn’t stopped there.  He created an application called WolframTones, which uses computational algorithms to generate original music stylings that can be downloaded to cellphone ringtones.  And now, he’s created Wolfram|Alpha, a computational knowledge engine intended to complement (if not rival) Google in its impact.

As we witness the next technological advances, we’ll continue to be amazed by what we enable computers to do.  With Wolfram|Alpha and his other monumental achievements, Stephen Wolfram is blazing a new trail in defining what is possible.

The Launch of Wolfram|Alpha

Today is scheduled to be the day for the launch of Wolfram|Alpha – a new computational knowledge engine based upon some of Stephen Wolfram’s new scientific works.

I personally think that Stephen Wolfram’s ideas are fascinating, and could very well lead to new technologies and a greater understanding of what is possible.  Wolfram represents one of those scientists that really strives to go beyond the envelope…

I’ve included below a message from Stephen Wolfram about the launch of Wolfram|Alpha, and what he hopes to achieve with it. 

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May 14, 2009 marks the 7th anniversary of the publication of A New Kind of Science, and it has been my tradition on these anniversaries to send a short report on the progress of NKS.

It has been fascinating over the past few years to watch the progressive absorption of NKS methods and the NKS paradigm into countless different fields. Sometimes there’s visible mention of NKS, though often there is not.

There has been an inexorable growth in the use of the types of models pioneered in NKS. There has been steadily increasing use of the kinds of computational experiments and investigations introduced in NKS. And the NKS way of thinking about computation and in terms of computation has become steadily more widespread.

Many of the specific investigations made in the NKS book have now been extended and enhanced. And even the results on fundamental physics in the NKS book are now coming closer to the mainstream.

The trickle of academic work aimed directly at pure NKS–the basic investigation of simple programs and the computational universe–has turned into a stream, though tremendous opportunity for growth remains.

And I continue to find it remarkable how many thought leaders that I run across in incredibly diverse areas turn out to have read the NKS book, often in great detail.

In June we’ll be holding our 7th NKS Summer School (this year in Italy–the first time outside the United States). Every year we receive a progressively larger number of highly qualified applications, and this year will be our largest Summer School to date.

http://www.wolframscience.com/summerschool

But for me the biggest thing that’s happened this year is the emergence of Wolfram|Alpha.

http://www.wolframalpha.com

When I was writing the NKS book I kept on wondering what the first “killer app” (to use a phrase from the software industry) for NKS would be.

I tried to think back what one would have imagined in 1936, when the idea of universal computing was introduced. Could one have predicted what the first killer apps for computers would be?

As it was, first there were databases–which drove the mainframe computer industry, and later there were word processors–which drove the personal computer industry.

Despite their tremendous practical importance, databases and word processors are really quite prosaic applications of an idea as powerful as universal computation.

And both of these applications could probably have been done even without the full concept of universal computation.

But the point is that the paradigm of universal computation was crucial in even imagining that either of these applications would make sense.

And so it is now with NKS and Wolfram|Alpha.

Wolfram|Alpha is, I believe, going to be the first killer app of NKS.

And remarkable though Wolfram|Alpha is, it is at some level still prosaic relative to the full power of the ideas in NKS.

Yet without the NKS paradigm, I cannot imagine I would ever have thought that Wolfram|Alpha could make sense.

There is an immensely complex web of systematizable knowledge out there in the world. And before NKS, I would have assumed that to handle something of this complexity would have required building a system that is somehow correspondingly complex–and in practice completely out of reach.

But from NKS we have learned that even highly complex things can have their origins in simple rules and simple programs.

And this is what inspired me to believe that building Wolfram|Alpha might be possible.

As a practical matter, many algorithms in Wolfram|Alpha were found by NKS methods–by searching the computational universe for programs that achieve particular purposes.

And there is a curious sense in which the discoveries of NKS about computational irreducibility are what make Wolfram|Alpha possible.

For one of the crucial features of Wolfram|Alpha is its ability to take free-form linguistic input, and to map it onto its precise symbolic representations of computations.

Yet if these computations could be of any form whatsoever, it would be very difficult to recognize the linguistic inputs that represent them.

But from NKS we know that computations fall into two classes: computationally reducible and computationally irreducible.

NKS shows that in the abstract space of all possible computations the computationally irreducible are much the most common.

But here is the crucial point: because those computations are not part of what we have historically studied or discussed, no systematic tradition of human language exists to describe them.

So when we use natural human language as input to Wolfram|Alpha, we are inevitably going to be describing that thin set of computations that have long linguistic traditions, and are computationally reducible.

Those computations cover the traditional sciences. But in a sense it is the very ubiquity of computational irreducibility that forces there to be only small islands of computational reducibility–which can readily be identified even from quite vague linguistic input.

If one looks at Wolfram|Alpha today, much of what it computes is firmly based on OKS (the “Old Kind of Science”), and in this sense Wolfram|Alpha can be viewed as a shining example of what can be achieved with pre-NKS mathematical science.

And curiously, after all these years, it is also perhaps the first clear consumerized example of universal computation at work. For now, for the first time, anyone will be able to walk up to a computer and immediately see just how diverse a range of possible computations it can do.

So what about NKS? NKS is certainly crucial to the very conceptualization of Wolfram|Alpha.

And even today one can use Wolfram|Alpha to do a little NKS: one can type in “rule 30″, or ask about other NKS systems that can readily be specified in linguistic terms.

But in the future there is tremendous opportunity to do more with NKS in Wolfram|Alpha.

Today, Wolfram|Alpha uses existing models from science and other areas, then does computations based on these models.

But what if it could find new models? What if it could invent on the fly? Do science on the fly?

That is precisely what NKS suggests should be possible. Exploring the computational universe on request, and finding things out there that are useful for some particular specified purpose.

We started a small experiment a few years ago with WolframTones (http://www.wolframtones.com) where we use NKS to invent new musical tunes. But there is vastly more that can be done–directing with ordinary language, but discovering automatically with NKS.

Whether today’s computers are fast enough to do this well I do not know. But perhaps by next year, Wolfram|Alpha will not only be a killer app made possible by NKS–it will also provide an outlet for the full richness of the computational universe that has been revealed to us by NKS.

But for now: tomorrow (May 15) is the day we begin to make Wolfram|Alpha live–the first killer app of NKS.

See the Wolfram|Alpha Blog to follow the launch:

http://blog.wolframalpha.com

– Stephen Wolfram