Nate True
Senior Software Engineer

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Combining AR and AI: Contextual Awareness

There was a lot of excitement for innovation in augmented reality (AR) at CES this year. With the advent of Windows Mixed Reality, the announcement of the Magic Leap One headset, and the HTC Vive Pro’s front-facing cameras, opportunities abound for developers to create compelling AR applications. In previous years, available augmented reality systems lacked the processing power necessary to drive the artificial intelligence engines required to build the engaging experiences that would drive mass adoption. As a result, the experience generally has been limited to projecting screens and objects into space rather than having full contextual awareness of the scene.

Now, however, with further advancements in mobile computing power, combined with aggressive advancements in the fields of machine learning and computer vision, augmented reality developers stand poised to solve long-standing barriers to workplace augmented reality adoption. By integrating artificial intelligence techniques with these more powerful AR platforms, developers will be able to create a new category of enterprise development - namely, the development of fully customized AR applications to train and assist workers as they perform tasks.

Cambridge Consultants and Synapse enjoy a unique position among product development consultants. Our breadth of experience and expertise covers every phase of development from ideation, research, and design to engineering and manufacturing. The augmented reality and AI demos we shared at CES serve to demonstrate our ability to integrate AI into any product and engagement. Using our unique neural computer vision training techniques along with our knowledge of deep learning, we can quickly assemble solutions in a wide variety of situations, ranging from manufacturing and industrial maintenance to training and quality control.


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June 29, 2020

Sidewalk Detection on the Edge and Shared Micromobility: A Solution Analysis

As the only form of public transit that is readily capable of supporting social distancing, shared bikes and scooters will be an essential component of an effective urban economic recovery strategy in the coming months. Prior to COVID-19, the city of San Francisco announced that future shared scooter platforms will be required to have deterrents to riding on sidewalks. Naturally, being both SF residents who will be affected by this decision, and curious engineers with micromobility industry experience, we decided to leverage our expertise in machine learning to explore the specifics involved in implementing a system which can determine if a scooter is riding on a street or a sidewalk.

June 15, 2020

[Download] Do Better. Sustainable Product Design Ebook

As a product development consulting company, we are in a unique position to drive sustainable design across industries—and we don’t intend to stop there. Instead, we are sharing our work to help others design more sustainable products and systems. This ebook abstracts our sustainable design process into easy-to-use tools, which can be applied to any hardware product development.

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December 4, 2019

[Watch] Stop Yelling at Alexa, She Doesn’t Get You…Yet

The recent success of smart speakers has been a great leap in human-digital interaction, but there’s still a lot of space for developers and companies to cover to create smart devices and environments with truly engaging and intuitive interfaces. While voice command technology can handle simple tasks, the interaction can fall short because it has modest understanding of human intent.