A Dating Site for Algorithms
A startup called Algorithmia wants to connect underused algorithms with those who want to make sense of data.
Easier access to algorithms could make it faster, cheaper, and simpler to get insights from mounds of data.
A startup called Algorithmia has a new twist on online matchmaking. Its website is a place for businesses with piles of data to find researchers with a dreamboat algorithm that could extract insights–and profits–from it all.
The aim is to make better use of the many algorithms that are developed in academia but then languish after being published in research papers, says cofounder Diego Oppenheimer. Many have the potential to help companies sort through and make sense of the data they collect from customers or on the Web at large. If Algorithmia makes a fruitful match, a researcher is paid a fee for the algorithm’s use, and the matchmaker takes a small cut. The site is currently in a private beta test with users including academics, students, and some businesses, but Oppenheimer says it already has some paying customers and should open to more users in a public test by the end of the year.
“Algorithms solve a problem. So when you have a collection of algorithms, you essentially have a collection of problem-solving things,” says Oppenheimer, who previously worked on data-analysis features for the Excel team at Microsoft.
Oppenheimer and cofounder Kenny Daniel, a former graduate student at USC who studied artificial intelligence, began working on the site full time late last year. The company raised $2.4 million in seed funding earlier this month from Madrona Venture Group and others, including angel investor Oren Etzioni, the CEO of the Allen Institute for Artificial Intelligence and a computer science professor at the University of Washington.
Etzioni says that many good ideas are essentially wasted in papers presented at computer science conferences and in journals. “Most of them have an algorithm and software associated with them, and the problem is very few people will find them and almost nobody will use them,” he says.
One reason is that academic papers are written for other academics, so people from industry can’t easily discover their ideas, says Etzioni. Even if a company does find an idea it likes, it takes time and money to interpret the academic write-up and turn it into something testable.
To change this, Algorithmia requires algorithms submitted to its site to use a standardized application programming interface that makes them easier to use and compare. Oppenheimer says some of the algorithms currently looking for love could be used for machine learning, extracting meaning from text, and planning routes within things like maps and video games.
Early users of the site have found algorithms to do jobs such as extracting data from receipts so they can be automatically categorized. Over time the company expects around 10 percent of users to contribute their own algorithms. Developers can decide whether they want to offer their algorithms free or set a price.
All algorithms on Algorithmia’s platform are live, Oppenheimer says, so users can immediately use them, see results, and try out other algorithms at the same time.
The site lets users vote and comment on the utility of different algorithms and shows how many times each has been used. Algorithmia encourages developers to let others see the code behind their algorithms so they can spot errors or ways to improve on their efficiency.
One potential challenge is that it’s not always clear who owns the intellectual property for an algorithm developed by a professor or graduate student at a university. Oppenheimer says it varies from school to school, though he notes that several make theirs open source. Algorithmia itself takes no ownership stake in the algorithms posted on the site.
Eventually, Etzioni believes, Algorithmia can go further than just matching up buyers and sellers as its collection of algorithms grows. He envisions it leading to a new, faster way to compose software, in which developers join together many different algorithms from the selection on offer.