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.