Question to Wolfram Alpha: Will Intuitive Surgical (Nasdaq: ISRG ) outperform the market?
Source: Wolfram Alpha.
Source: Wolfram Alpha.
Were you expecting a stock quote, or perhaps a bunch of opinions? That's because you're thinking like a search engine rather than like a computer. Yet visionary scientist Stephen Wolfram told an audience at last weekend's South By Southwest Interactive conference that computation is the binding element in natural evolution and a model for evolving how we think about data.
He has a point. We're inundated with data from searches, Twitter, Facebook, corporate networks, and the like, but certain of our tools -- *cough* Google (Nasdaq: GOOG ) *cough* -- mostly index the volumes of what we see. There's little meaning or intelligence. Wolfram Alpha, the online computational engine that bears its inventor's name and which powers the iPhone's Siri voice assistant, is taking a stab at solving the problem, but we have a long way to go.
Bridging the data divide -- our biggest opportunity?
In demonstrating what his creation is capable of, Wolfram clarified just how little we understand the data that we swim in daily. Indexing isn't the same as intelligence. Consider the Human Genome Project, which took 10 years to produce the raw data found in one genome.
More than a decade later, we can now produce the same amount of data in a matter of days, but that information is still largely opaque. Early genomic innovator Celera Corporation saw steadily declining revenues as a result, and is today a subsidiary of Quest Diagnostics.
Accumulation has exceeded understanding; reversing this trend will take money, time, and, ultimately, hardware and software.
In other words, it's a massive investment opportunity.
The Big Idea
It's important to remember that while data is everywhere, meaning increasingly comes from software. Think about how iTunes takes ones and zeros (binary information) and turns them into music, which is what that information means. Your DVD player takes similar but slightly different combinations to create movies. The implication? How we manipulate data matters.
And these are simple examples. Websites can tick off petabytes of behavioral information related to when you visited, what you looked at, what tools you used to interact with the site: Data that, when interpreted correctly, describes a lot about your likes and dislikes, your personality -- the wealth of meaning that is you. The success of Facebook's IPO depends on investors buying into the idea that there is power, and meaning, in this sort of data.
Don't think this a real issue? Executives who spent hundreds of dollars to be at SXSW here disagree. At least one SXSW session discussed whether all the data that's in some way associated with you should be preserved beyond death as a sort of archive of the life you've lived.
What we have now
Wolfram's vision for Wolfram Alpha is that it will be an engine to glean meaning from an almost-universal data set -- software that performs the digital equivalent of finding needles in haystacks. But such a large problem more than likely requires lots of smaller solutions. And Wolfram isn't the only one thinking in this direction.
We think several companies are participating in this revolution, and one or more could become leaders:
- Qlik Technologies (Nasdaq: QLIK ) . A leader in transforming data into reports that can be viewed and manipulated on iPhones, iPads, and other mobile devices, Qlik's ability to process data in device memory rather than a database could become a model for on-the-fly computation.
- Informatica (Nasdaq: INFA ) . Data is only as good as its accessibility. Informatica allows clients to combine pools of different data for the purpose of extracting meaning. It's good business; revenue is up roughly 20% annually over the past three years. Diluted earnings per share have improved more than 26% over the same period.
- salesforce.com (NYSE: CRM ) . The company best known for using the Web as a software substitute collects and distributes billions of bits daily. Its Radian6 unit specializes in tracking and responding to meaningful events on social networks.
- LinkedIn. Though known as a social network, LinkedIn is perhaps the most impressive aggregator of employee information in the world. It could take years, but real-time computational tools for understanding LinkedIn's data are a realistic possibility.
- Teradata (NYSE: TDC ) . Another BI provider that's made its name in data warehousing technology, Teradata supplies the sort of data-crunching muscle needed to make Wolfram's vision a reality. We'll need as much horsepower as Teradata can produce. Researcher IDC predicts the market for "Big Data" will expand 40% annually between now and 2015.
What other technologies lead the computational revolution? How will smarter mobile devices play a role? The Motley Fool recently addressed these questions in a special report, "The Next Trillion-Dollar Revolution." The research is free, but only for a limited time. Click here to get started right away.