Not so long ago, computing was a luxury for the selected few. Just a small number of people had access to a computer and less so, to the internet. This changed dramatically after the release of the smartphone. Computing became more personal and people started using technology more than ever.
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Voice recognition, face recognition, text recognition are only some possibilities that are enabled through Machine Learning. It is a technology that can allow our devices to get a better understanding of our world, our actions and intentions of using them, allowing us that way to design and build better context-aware
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The Human Factors in Human Computer Interaction 2017 conference took place in Denver, Colorado. I was lucky enough to be participating in person this year, with my first ever publication in the field of cross-device interaction with SenseBelt. It was a conference full of inspiring talks, innovative pieces of work,
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My esteemed colleague Flo and I recently worked on a television guide bot using api.ai + Amazon's AWS backend service to experiment with the capabilities of Voice User Interfaces (VUI). In this blog post I’ve covered the design process we followed to enable voice interfaces in an existing product
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You can’t expect a product to be successful unless it solves a problem, big or small. How do you define that problem when you’re working on internal projects? In this blog post, we'll talk about how basic user research helped us to understand the pain points of our
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Android Studio comes with a powerful tool that helps you understand how your layout files are going to be rendered on the user's device. As powerful as this tool can be, it can lead to some misleading errors driving the developer crazy. This post talks about how to get the
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