URL:http://www.wired.com/design/2013/01/data-viz-ayasdi-iris/
Ayasdi, a company that has developed data visualization software it says uses big data to answer the questions you never thought to ask, has launched in Palo Alto with $10.25 million in funding.
Khosla Ventures and Floodgate are backing Ayasdi, which was founded in 2008 by Gurjeet Singh, Harlan Sexton and Stanford mathematics professor Gunnar Carlsson while researching ways to commercialize Carlsson’s work with scientific data investigation. In 2010, the company received $1.25 million in seed funding to build prototypes of its technology, used with private clients that include US intelligence agency Iarpa, Second Genome, and Darpa to investigate areas such as drug discovery, cancer therapy, fraud prediction and terrorist attack prevention. This latest round of financing officially launches the company into the commercial realm.
Their new product is called the Iris Insight Discovery platform. It’s a type of machine learning that uses hundreds of algorithms and topological data analysis to mine huge datasets before presenting the results in a visually accessible way. Using algebraic topology, the system automatically hunts down data points close in nature and maps these out to reveal a network of patterns for a researcher to decipher — any closely related nodes of information will be connected and clustered together, like how a social network arranges its data according to relationship connections.“The answers to today’s most important scientific, business and social problems lie in data,” Singh, Ayasdi’s CEO, said in a statement. “The biggest challenge in big data today is asking the right questions of data. There are so many questions to ask that you don’t have the time to ask them all, so it doesn’t even make sense to think about where to start your analysis. The power of Ayasdi is its unique ability to automatically discover insights — regardless of complexity — without asking questions. Ayasdi’s customers can finally learn the answers to questions that they didn’t know to ask in the first place. Simply stated, Ayasdi is ‘digital serendipity’.”
It’s a bold statement, however by using algebraic topology Ayasdi has managed to totally remove the human element that goes into data mining — and, as such, all the human bias that goes with it. Instead of waiting to be asked a question or be directed to specific existing data links, the system will — undirected — deliver patterns a human controller might not have thought to look for.
“We don’t necessarily need to treat computers like dumb question-answering machines,” said Singh, “we can actually make them do a lot more work.”
Given backer Khosla Ventures’ background in the healthcare sector, we could see Ayasdi shift to a focus in this area if demand ensues from big pharmaceutical companies. It is already in good standing in the field, with one published example showing it revealed insights within eight hours, rather than the usual 100 plus. It has also been used to discover new patterns in historical data. Derrick Harris of Gigaom saw this first hand and has attested to witnessing datasets from 272 cancer patients involving 25,000 genetic markers be analysed and visualised within seconds. This kind of work stands to dramatically reduce the time new drug therapies and alike take to go from the lab, to clinical trials, to the public.
Explaining how the data maps work, Harris referred to one red cluster that could, for instance, represent cancer survivors, saying “as researchers dig into this area further, they might find, for example, that none of these survivors underwent chemotherapy and all share a rare genetic that might make them particularly well suited to fight off cancer cells.”
The system has also already been tested in areas like sports statistics, however, and has the potential to dramatically overhaul pretty much any field that’s data-based — so, pretty much every field.
Whatever its primary use, the technology has impressive roots and stands to make a big impact in the field. Having spent 12 years in R&D at Stanford University, where researchers combined mathematics, computer science and data visualisation to built it, Ayasdi received hundreds of thousands of dollars in early backing from Darpa. The agency’s former director Tony Tether is calling it “one of the top ten innovations developed at Darpa in the last decade” and “the key to unlocking some of the biggest national security challenges that we face today.” That’s a big thumbs up, considering the astonishing number of inventions and theories put forward by Darpa in recent years.
In a statement, the service also received high praise from the Icahn Institute of Genomics and Multiscale Biology at Mount Sinai and the University of California, San Francisco Brain and Spinal Injury Centre, which have both already used it to uncover data patterns in research.