Computer Vision For All

A decade ago, as I was starting my last computer vision company, one of our investors announced that they had funded another deep tech company. Except this deep tech company seemed to be focused on decidedly old-fashioned tech compared to the futuristic vision-based system we were working on.

At the time (and this was at the beginning of the 2010s), we had just gone through a transformation from Web 1.0 to Web 2.0, where Internet-powered businesses had gone from static to dynamic functionality. The Web was no longer just a mechanism to distribute information; it now had a service layer being built where it could be used to address and control devices and take previously offline processes online.

With that foundation in place, a set of entrepreneurs set out to harness these capabilities to expand what was possible with the Internet. One of these entrepreneurs was a former Amazon engineer who happened to know quite a bit about old-school PSTN technology. If you’re not familiar with what PSTN is, it stands for Public Switched Telephone Network, aka, the world’s already established telephony network.

PSTN was its own arcane technology backwater, and there were very few engineers outside of those who worked at the traditional telecoms who knew how to work with it.

So when Jeff Lawson, that former Amazon engineer, realized that he could combine the power of the new Internet with the capabilities of PSTN, a new company was created: Twilio.

The brilliance of Twilio wasn’t simply that it connected PSTN to the Internet; it was that it lowered the bar for working with PSTN from telecom industry insider to any software or web engineer. Now, anyone who understood how to build with web services could rapidly add PSTN-powered functionality to the product that they were working on. That enabled the creation of tools we now take for granted, like text-message-based two-factor-authentication, and “call me now” customer support services.

The ethos behind Twilio — democratizing access to an otherwise challenging or arcance technology — brings us to my new company, Tangram Vision. Over my past decade of working in computer vision, I’ve witnessed significant progress in the development of tools that are designed to make it simpler than ever to build a vision-powered product or service. Things like:

• Lower cost perception sensors that make it cheaper and simpler to prototype vision-powered products
• Open-source libraries like OpenCV and ROS that provide many of the foundational libraries for building vision-powered products
• Powerful algorithmic tools like TensorFlow and OpenSLAM that provide building blocks for higher-level product functionality

Yet, despite these advancements, building a vision-enabled product is still complicated, and requires specialized understanding of computer vision techniques and engineering approaches. That’s because computer vision has not yet had its Twilio moment. And that is what we intend to change with Tangram Vision.

Our focus at Tangram Vision is to make those sensors and algorithms simple to integrate, and painless to maintain over time. We aim to let any software or web engineer build a computer vision powered product. And, for those who already understand computer vision, we aim to relieve them from the duty of building infrastructure, so they can focus on those higher level tasks that make their products unique.