Advanced Machine Learning Company Osaro Captures $3.3 Million

Advanced Machine Learning Company Osaro Captures $3.3 Million

Osaro, a new, San Francisco-based startup that’s developing advanced machine learning known as deep reinforcement learning, has raised $3.3 million in seed funding to take its technology to market.

The money comes from Scott Banister, Jerry Yang’s AME Cloud Ventures, and Peter Thiel, for whom Osaro cofounder Derik Pridmore once worked (first at Thiel’s hedge fund, Clarium Capital, and later as a principal at his venture firm, Founders Fund).

Why it’s interesting: Osaro’s machine intelligence software combines perception (which we’ve seen plenty of in the past, including with image identification) with decision-making abilities that will ostensibly help computer and robotic systems teach themselves to act more efficiently through trial and error (which we’ve seen more infrequently).

We talked with Pridmore yesterday to learn more about the nine-person startup. Our chat has been edited for length.

TC: You don’t have any customers yet, but one of the commercial areas you’re exploring is industrial robotics. Why should these companies pay attention to Osaro?

DP: First, industrial robots aren’t what the average person thinks they are. They don’t have brains. They really just have very precise motors that are controlled by software. But every time you need to do something new, it needs to be reprogrammed by a person. The robots aren’t flexible.

That trend used to work, but what used to take a year for a robot to make now takes a month [in many cases], and if it takes a month to set up a robot and the robot runs [that task] for just one month, that’s inefficient. [Our technology] enables you to grab a robot and train it a few times and let it start training itself from there. You only have to tell it when it’s successful or it fails by giving it a score.

TC: Do you have beta customers we could name for readers?

DP: We’re working on a pilot right now. These are complex solutions, so we need to partner with people to show that we can handle technical requests that others can’t.

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