As developers and designers, we are creating new things every day. I like to say that we are really good at making the impossible possible. In fact, some of us are so good at it, that we actually do it unintentionally. These unintentional outcomes that occur when we are creating code are called “impossible states.”
“Smart” technology is quickly emerging in all areas of our lives. From smartphones to smart televisions, refrigerators, watches, and even dog collars, it seems like everything around us is being connected to the internet. This phenomenon is known as the Internet of Things (IoT).
We are not strangers to the unprecedented ways that new technological devices can reshape society. In the last decade, we have witnessed how things like smart phones and social media have dramatically altered how we, as humans, interact.
One of the major technological advances that will likely continue to shape our human interactions is brain computer interface (BCI) technology. In this post, I am going to delve into the history of the BCI and look at some of the current developments happening in the realm of BCI technology.
It may seem strange to bring up textiles when discussing computer programming. However, my interest in the correlation between the two was piqued last week when my friend sent me a question currently circulating on the internet: Is it possible to knit DOOM? Thinking about this question led me to consider the immense influence that the textile industry has had on computer science and modern technology.
Creating a successful application isn’t just about ensuring that all of the components work; the layout and design of the application are also crucial. The design must be professional and engaging, and the layout should be easy for users to navigate. Design components, such as animations and navigation transitions, can also enhance the usability of the application.
When you think about the future of artificial intelligence (AI) technology, it’s likely that you don’t think of auto-completion. However, you probably should. In July 2020, OpenAI released a beta testing version of GPT-3, a new auto-completion program that could very likely define the next decade of AI programming.
There have been countless books written on talent, we know talent when we see it, and we can sense talent in people around us. While most of us have a fundamental understanding of what the word “talent” means, most of us would have a hard time clearly defining it.
Since COVID-19 began, all of us have been looking for good alternatives to our traditional in-person get-togethers with family and friends. In this post, I’m going to be talking about my most recent side project creating a virtual baby shower.
User flow testing, also known as workflow testing, analyzes how an application is performing from the standpoint of the user. In this post, I am going to talk about some of the challenges with automating these types of tests and how we’ve addressed these challenges on several recent projects.