CrowdAI sells artificial-intelligence-as-a-service



Computers aren’t blind, but they can’t see. They can detect objects, but must be trained to understand what those objects are. That takes two things: a ton of example data collected and organized by artificial intelligence, and humans to accurately label and verify that data.

Done right, this process can teach self-driving cars to avoid pedestrians, detect parking lot usage by counting cars in satellite photos, or assess roof damage from drone footage.

This is what CrowdAI does.

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CrowdAI detects parking lots full of cars

Businesses send CrowdAI their autonomous vehicle, satellite, or drone imagery. CrowdAI’s artificial intelligence systems do the grunt work of recognizing objects. And humans confirm everything was properly recognized while looping back to improve the AI. This service lets customers focus on their unique business like building advanced hardware instead of developing AI systems from scratch.

Now the Y Combinator startup has raised $2 million from Susa Ventures, Box Group, SV Angel, Metamorphic, and Yahoo founder Jerry Yang’s AME Cloud. That will fuel CrowdAi’s push to create an instant hybrid workforce of humans and computers that satellite and self-driving car companies can rely on to analyze their data.

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“The world is moving towards automation, robotics, and on-demand services. The biggest barrier to getting there is creating the bridges that allow computers to interact with the world” says co-founder Nic Borensztein. “There an enormous expansion of the economy that’s going to come next.”

Borensztein previously founded and sold an ad platform called Ember to Adaptive Media. He teamed up with Devaki Raj, who studied stats and machine learning at Oxford before working on Maps and Android at Google. Fellow co-founder Pablo Garcia also worked at Google on the AdWords API team building out data pipelines.

CrowdAI's founders (from left): Pablo Garcia, Devaki Raj, and Nic Borensztein

CrowdAI’s founders (from left): Pablo Garcia, Devaki Raj, and Nic Borensztein

Together, they recognized that computer vision and image recognition would change a huge swath of businesses that might not be able to adapt by themselves.

It helps self-driving car companies identify objects like stop signs, pedestrians, bicycles, and trucks to train their auto-avoidance and navigation algorithms. For satellite imagery companies, CrowdAI labels farms, oil rigs, buildings, cars in parking lots and more, which can help their customers predict output, monitor construction, or estimate the popularity of a business. Drone companies can use CrowdAI to count solar panels or determine the extent of roof damage for insurance claims.

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CrowdAI will have to show it can perform better than its competitors with different methods. Services like CrowdFlower and Mechanical Turk rely solely on human labor that can be expensive. Meanwhile, Clarifai and the Google Image API depend on computers, which aren’t always accurate enough to create training data for AI algorithms. CrowdAI’s most direct competitor Orbital Insight has raised over $28 million, but focuses exclusively on satellite imagery.

The massive market could also bring in more deep-pocketed players that could box out the startup. But by merging the scalability of computers with the intuition of humans, CrowdAI believes it can earn the trust of customers without a margin for error.



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