Via Techcrunch
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Aiming to do for Machine Learning what MySQL did for database servers, U.S. and UK-based PredictionIO has raised $2.5 million in seed funding from a raft of investors including Azure Capital, QuestVP, CrunchFund (of which TechCrunch founder Mike Arrington is a Partner), Stanford University‘s StartX Fund, France-based Kima Ventures,
IronFire, Sood Ventures and XG Ventures. The additional capital will be
used to further develop its open source Machine Learning server, which
significantly lowers the barriers for developers to build more
intelligent products, such as recommendation or prediction engines,
without having to reinvent the wheel.
Being an open source company — after pivoting from offering a “user behavior prediction-as-a-service” under its old TappingStone product name — PredictionIO
plans to generate revenue in the same way MySQL and other open source
products do. “We will offer an Enterprise support license and, probably,
an enterprise edition with more advanced features,” co-founder and CEO
Simon Chan tells me.
The problem PredictionIO is setting out to solve is that building
Machine Learning into products is expensive and time-consuming — and in
some instances is only really within the reach of major and
heavily-funded tech companies, such as Google or Amazon, who can afford a
large team of PhDs/data scientists. By utilising the startup’s open
source Machine Learning server, startups or larger enterprises no longer
need to start from scratch, while also retaining control over the
source code and the way in which PredictionIO integrates with their
existing wares.
In fact, the degree of flexibility and reassurance an open source
product offers is the very reason why PredictionIO pivoted away from a
SaaS model and chose to open up its codebase. It did so within a couple
of months of launching its original TappingStone product. Fail fast, as
they say.
“We changed from TappingStone (Machine Learning as a Service) to
PredictionIO (open source server) in the first 2 months once we built
the first prototype,” says Chan. “As developers ourselves, we realise
that Machine Learning is useful only if it’s customizable to each unique
application. Therefore, we decided to open source the whole product.”
The pivot appears to be working, too, and not just validated by
today’s funding. To date, Chan says its open source Machine Learning
server is powering thousands of applications with 4000+ developers
engaged with the project. “Unlike other data science tools that focus on
solving data researchers’ problems, PredictionIO is built for every
programmer,” he adds.
Other competitors Chan cites include “closed ‘black box” MLaaS
services or software’, such as Google Prediction API, Wise.io, BigML,
and Skytree.
Examples of who is currently using PredictionIO include Le Tote, a
clothing subscription/rental service that is using PredictionIO to
predict customers’ fashion preferences, and PerkHub, which is using
PredictionIO to personalize product recommendations in the weekly ‘group
buying’ emails they send out.