By John P. Desmond, AI Trends Editor More companies are successfully exploiting predictive maintenance systems that combine AI and IoT sensors to collect data that anticipates breakdowns and recommends preventive action before break or machines fail, in a demonstration of an AI use case with proven value. This growth is reflected in optimistic market forecasts….
By Lance Eliot, the AI Trends Insider We already expect that humans to exhibit flashes of brilliance. It might not happen all the time, but the act itself is welcomed and not altogether disturbing when it occurs. What about when Artificial Intelligence (AI) seems to display an act of novelty? Any such instance is bound to get our attention;…
By John P. Desmond, AI Trends Editor Engineers tend to see things in unambiguous terms, which some may call Black and White terms, such as a choice between right or wrong and good and bad. The consideration of ethics in AI is highly nuanced, with vast gray areas, making it challenging for AI software engineers to…
By John P. Desmond, AI Trends Editor AI is more accessible to young people in the workforce who grew up as ‘digital natives’ with Alexa and self-driving cars as part of the landscape, giving them expectations grounded in their experience of what is possible. That idea set the foundation for a panel discussion at AI World…
Summary This developer code pattern demonstrates how you can create your own music based on your arm movements in front of a webcam. It uses the Model Asset eXchange (MAX) Human Pose Estimator model and TensorFlow.js. Description This code pattern is based on Veremin, but modified to use the Human Pose Estimator model from the…
Summary The introduction of the IBM Model Asset eXchange (MAX) that is hosted on the Machine Learning eXchange has given application developers without data science experience easy access to prebuilt machine learning models. This code pattern shows how simple it can be to create a web app that utilizes a MAX model. The web app…
Summary The IBM Model Asset eXchange (MAX) models that are hosted on the Machine Learning eXchange (https://ml-exchange.org/models/) have given application developers without data science experience easy access to prebuilt machine learning models. This code pattern shows how to create a simple web application to visualize the text output of a MAX model. The web app…
Summary In this code pattern, learn how to build a chatbot that answers a user’s questions by finding the answer in a college biology textbook. Description Ever found yourself wondering what mitochondria are? Perhaps you are curious about how neurons communicate with each other? A Google search works well to answer your questions, but what…
Summary This IBM Developer code pattern explains how to detect human poses in a given image by using the Human Pose Estimator model from the Model Asset eXchange that is hosted on the Machine Learning eXchange. Using coordinates, the pose lines that are created by the model are assembled into full body poses for each…
Summary Whether you are counting cars on a road or people who are stranded on rooftops in a natural disaster, there are plenty of use cases for object detection. Often times, pre-trained object detection models do not suit your needs and you need to create your own custom models. How can you use machine learning…