Welcome to the Blog on Machine Learning and Artificial Intelligence!
In this section, you find blog posts written by the scientists of the Lamarr Institute as well as contributors from partner organizations and guest authors. We invite you to discover exciting posts for beginners, experts, users from practice and everyone who is curious about the topics of Machine Learning and Artificial Intelligence.
Self-organization is an important skill in many industries. This is especially the case in research, where multiple projects often need to be managed without predetermined tasks. The process of researching a topic in particular has the potential to be an endless task. To streamline this process, we present some tricks...
Deep Neural Networks (DNNs) have shown phenomenal performance, reaching or surpassing human expert-level performance in various domains. Computer vision, which is essential for the success of technologies like autonomous driving or automated medical diagnosis, uses a version of DNNs called Convolutional Neural Networks (CNNs). CNNs have replaced classical Machine Learning...
As a form of computer vision data, point clouds are widely used in the navigation as well as the localization of self-driving cars and robots due to their excellent representation of 3D scenes. In these fields, security and reliability is a high-profile issue: Accidents caused by AI manipulation need to...
A large part of running a business is record keeping and reporting. Among these records and reports, financing is arguably one of the most important areas. All companies must keep detailed information of finances, capital, investments, spending, and the like. These are usually for legal reasons but can also be...
Everyday we spend a large part of our time waiting for one thing or another. We wait to get bread at the bakery every morning. We wait every time we go to see our doctors. We wait to reach our destination during a taxi ride, or for our contacts to...
The bin packing problem is one of the hardest problems for digital computers known in computer science. It goes as follows: Given a set of objects of a certain size and a set of containers of a certain volume. Is it possible to fit all the given objects into the containers? Although...
Computer vision systems are trained on large datasets composed of hundreds of thousands of images. Many of these images have been previously interpreted, classified, and labeled by human data annotators. Through data annotation, humans set the tone of what machines will learn to “see“ and how they will interpret the...