Alle Posts
Informieren Sie sich ĂĽber unsere Arbeit und die neuesten Nachrichten auf dem Gebiet der datenzentrierten KI, der industriellen KI, der LLMs und mehr.
Matching vibroacoustic test and simulation data with machine learning
Stefan Suwelack
•
5 min read
annotationlabelingmodel evaluation
How to quickly find and correct label errors
Ensuring label consistency is critical for building robust machine learning models. This post shows you how to achieve label consistency in a data centric way.
Daniel Klitzke
•
2 min read
annotationlabelingacoustic event detectionfeatured
Training an acoustic event detection system using Renumics Spotlight
Machine Learning based systems for acoustic event detection typically require a vast amount of training data. Intelligent labeling techniques open up new possibilities for small data scenarios.
Daniel Klitzke
•
5 min read
cadcae
How data-centric ML helps to build reliable models fast
ML researchers typically iterate different model architectures on a fixed dataset that they often know very little about. In real use cases, it is often a good idea to focus most efforts on the data and not on the model.
Stefan Suwelack
•
8 min read
cadcae
Data-centric AI for Engineering and Manufacturing
Data-centric machine learning is an emerging paradigm. Is this a game-changer for ML in engineering and manufacturing?
Stefan Suwelack
•
4 min read
cadcae
The AI-assisted Engineering Canvas
Data-driven methods have arrived and promise to speed up product development. The AI-assisted Engineering Canvas helps to get started.
Stefan Suwelack
•
8 min read
cadcae
What is AI-assisted Design?
Generative ML methods have achieved tremendous success in image and audio processing. Can mechanical engineers benefit from this technology?
Stefan Suwelack
•
6 min read
cadcae
Use Cases for AI-assisted Engineering
During the next decade, machine learning will become an indispensable tool for engineers. But where can the technology provide the most value today?
Stefan Suwelack
•
6 min read